New Energy Vehicle Powertrain Technologies and Applications 9811995656, 9789811995651

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Key Technologies on New Energy Vehicles

Yong Chen

New Energy Vehicle Powertrain Technologies and Applications

Key Technologies on New Energy Vehicles

Key Technologies on New Energy Vehicles publishes the latest developments in new energy vehicles - quickly, informally and with high quality. The intent is to cover all the main branches of new energy vehicles, both theoretical and applied, including but not limited: • • • • • • • • • • •

Control Technology of Driving System Hybrid Electric Vehicle Coupling Technology Cross Disciplinary design optimization technology Single and Group Battery Technology Energy Management Technology Lightweight Technology New Energy Materials and Device Internet of Things (IoT) Cloud Computing 3D Printing Virtual Reality Technologies

Within the scopes of the series are monographs, professional books or graduate textbooks, edited volumes, and reference works purposely devoted to support education in related areas at the graduate and post-graduate levels.

Yong Chen

New Energy Vehicle Powertrain Technologies and Applications

Yong Chen School of Mechanical Engineering Guangxi University Nanning, China

ISSN 2662-2920 ISSN 2662-2939 (electronic) Key Technologies on New Energy Vehicles ISBN 978-981-19-9565-1 ISBN 978-981-19-9566-8 (eBook) https://doi.org/10.1007/978-981-19-9566-8 Jointly published with Huazhong University of Science and Technology Press The print edition is not for sale in China (Mainland). Customers from China (Mainland) please order the print book from: Huazhong University of Science and Technology Press. ISBN of the Co-Publisher’s edition: 978-7-5680-8151-1 © Huazhong University of Science and Technology Press and Springer Nature Singapore Pte Ltd. 2023 This work is subject to copyright. All rights are reserved by the Publishers, whether the whole or part of the material is concerned, specifically the rights of reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publishers, the authors, and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publishers nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publishers remain neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer imprint is published by the registered company Springer Nature Singapore Pte Ltd. The registered company address is: 152 Beach Road, #21-01/04 Gateway East, Singapore 189721, Singapore

Committe of Reveiwing Editors

Chairman of the Board Ouyang Minggao, Tsinghua University

Vice Chairman of the Board Wang Junmin, University of Texas at Austin

Members Ma Fangwu, Jilin University Wang Feiyue, Institute of Automation, Chinese Academy of Sciences Wang Jianqiang, Tsinghua University Deng Weiwen, Beijing University of Aeronautics and Astronautics Ai Xinping, Wuhan University Hua Lin, Wuhan University of Technology Li Keqiang, Tsinghua University Wu Chaozhong, Wuhan University of Technology Yu Zhuoping, Tongji University Chen Hong, Jilin University Chen Yong, Guangxi University Yin Guodong, Southeast University Yin Chengliang, Shanghai Jiaotong University Huang Yunhui, Huazhong University of Science and Technology

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Foreword: New Energy Vehicles and New Energy Revolution

The past two decades have witnessed the research and development (R&D) and the industrialization of China’s new energy vehicles. Reviewing the development of new energy vehicles in China, we can find that the “Tenth Five Year Plan” is the period when China’s new energy vehicles began to develop and our nation started to conduct organized R&D of the electric vehicle technology on a large scale; the “Eleventh Five Year Plan” is the period when China’s new energy vehicles shifted from basic development to demonstration and examination as the Ministry of Science and Technology carried out the key project themed at “energy saving and new energy vehicles”; the period of the “Twelfth Five Year Plan” is the duration when China’s new energy vehicles transitioned from demonstration and examination to the launch of industrialization as the Ministry of Science and Technology organized the key project of “electric vehicles”; the period of the “Thirteenth Five Year Plan” is the stage when China’s new energy vehicle industry realized the rapid development and upgrading as the Ministry of Science and Development introduced the layout of the key technological project concerning “new energy vehicles”. The decade between 2009 and 2018 witnessed the development of China’s new energy automobile industry starting from scratch. The annual output of new energy vehicles developed from zero to 1.27 million while the holding volume increased from zero to 2.61 million, each of which occupied over 53% in the global market and ranked first worldwide; the energy density of lithium-ion power batteries had more than doubled and the cost reduced by over 80%. In 2018, six Chinese battery companies were among the top ten global battery businesses, with the first and the third as China’s CATL and BYD. In the meanwhile, a number of multinational automobile businesses shifted to develop new energy vehicles. This was the first time for China to succeed in developing high-technology bulk commodities for civic use on a large scale in the world, also leading the trend of the global automobile development. The year of 2020 marked the landmark in the evolution of new energy automobile. Besides, this year was the first year when new energy vehicles entered families on a large scale and the watershed where new energy vehicles shifted from policy-driven to market-driven development. This year also saw the successful wrapping up of the mission in the Development Plan on Energy Saving and New Energy Vehicle vii

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Foreword: New Energy Vehicles and New Energy Revolution

Industry (2012–2020) and the official release of Development Plan on New Energy Vehicle Industry (2021–2035). At the end of 2020, in particular, President Xi Jinping proposed that China strove to achieve the goal typified by peak carbon dioxide emissions by 2030 and carbon neutral by 2060, so as to inject great power into the sustainable development of new energy vehicles. Looking back to the past and looking forward to the future, we can see even more clearly the historical position of the current development of new energy vehicles in the energy and industrial revolution. As is known to us all, each and every energy revolution started from the invention of power installations and transportation vehicles. On the other hand, the progress of power installations and transportation vehicles contributed to the development and exploitation of energy and led to industrial revolution. In the first energy revolution, steam engine was used as the power installation, with coal and train as energy and transportation, respectively. As for the second energy revolution, internal combustion engine was taken as the power installation, oil and natural gas as energy, gasoline and diesel as energy carrier, and automobile as the transportation vehicle. At the current stage of the third energy revolution, all kinds of batteries are power installation, the renewable energy as the subject of energy and electricity and hydrogen as energy carrier, and electric vehicles as the means of transportation. In fact, the first energy revolution enabled the UK to outperform the Netherlands, while the second energy revolution made the USA overtook the UK, both in terms of the economic strength. The present energy revolution may be the opportunity for China to catch up with and surpass other nations. How about the Fourth Industrial Revolution? In my opinion, it is the green revolution based on renewable energy and also the smart revolution on the basis of digital network. From the perspective of energy and industrial revolution, we can find three revolutions closely related to the new energy vehicles: electrification of power—the revolution of electric vehicles; low-carbon energy—the revolution of new energy; systematic intelligence—the revolution of artificial intelligence (AI). First, electrification of power and the revolution of electric vehicles. The invention of lithium-ion battery triggered the technological revolution in the area of storage battery over the past 100 years. Viewed from the development of power battery and power electronic device, the involvement of high specific energy battery and high specific power electric drive system would contribute to the platform development of electric chassis. The volume power of the machine controller based on new-generation power electric technology has more than doubled to 50 kw. In future, the volume power of the high-speed and high-voltage machine can be nearly doubled to 20 kw and the power volume of the automobile with 100 kw volume power could be no more than 10 L. With the constant decline of the volume of the electric power system, the electrification will lead to the platform and module development of chassis, which will lead to a major change in terms of vehicle design. The platform development of electric chassis and the lightweight of body materials will bring about the diversification and personalization of types of vehicles. Besides, the combination of active collision avoidance technology and body lightweight technology will result in a significant change in automobile manufacturing system. The revolution of power

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electrification will promote the popularity of new energy electric vehicles and will eventually contribute to the overall electrification of the transportation sector. China Society of Automobile Engineers proposed the development goals of China’s new energy vehicles in the 2.0 Technology Road Map of Energy Saving and New Energy Vehicles: The sales of new energy vehicles would reach 40% of the total sale of vehicles by 2030; new energy vehicles would become the mainstream by 2035 with its sale accounting for over 50% of the total sale of vehicles. In the foreseeable future, electric locomotives, electric ships, electric planes, and other types will become a reality. Second, low-carbon energy and new energy revolution. In the Strategy on Energy Production and Consumption Revolution (2016–2030) jointly issued by National Development and Reform Commission and National Energy Administration, a target was proposed that the non-fossil energy would account for around 20% of total energy consumption by 2030 and over 50% by 2050. Actually, there are five pillars aimed to realize the energy revolution: firstly, the transformation of renewable resources and the development of photovoltaic and wind power technologies; secondly, the energy system is shifting from centralized to distributed development, turning every building into a micro-power plant; thirdly, the storage of intermittent energy by way of relevant technologies such as hydrogen and battery; fourth, the development of energy (electric power) Internet technology; fifth, enabling electric vehicles to become the end of energy usage, energy storage, and energy feedback. In fact, China’s photovoltaic and wind power technologies are fully qualified for large-scale distribution, but energy storage remains a bottleneck which needs to be solved by way of battery, hydrogen, and electric vehicles. With the large-scale promotion of electric vehicles, along with the mixture of electric vehicles and renewable energy, electric vehicles will become the “real” new energy vehicles utilizing the entire chain of clean energy. In so doing, it could both solve the pollution and carbon emission problems of the vehicle itself, but could also be conducive to the carbon emission reduction of the entire energy system, thus bringing about a new energy revolution for the entire energy system. Third, intelligent development of system and AI revolution. Electric vehicles have three attributes of travel tools, energy devices, and intelligent terminals. Intelligent and connected vehicles (ICVs) will restructure the industrial chain and value chain of vehicles. Software defines vehicles while data determine value. The traditional vehicle industry will be transformed into a high-tech industry leading the AI revolution. In the meanwhile, let’s take a look at the Internet connection and the feature of sharing regarding vehicles, among “four new attributes”, from the perspectives of both intelligent travel revolution and the new energy revolution: For one thing, the connotation of the Internet pays equal attention to the Internet of vehicle information and the Internet of mobile energy. For another, the connotation of sharing lays equal emphasis on sharing travel and energy storage information. And both stationery and running electric vehicles can be connected to the mobile energy Internet, finally realizing a full interaction (V2G, vehicle to grid). As long as the energy storage scale of distributed vehicles is large enough, it will become the core hub of intelligent transportation energy, namely the mobile energy Internet.

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Foreword: New Energy Vehicles and New Energy Revolution

Intelligent charging and vehicle to grid will meet the demand of absorbing renewable energy fluctuations. By 2035, China’s inventory of new energy vehicles will reach about 100 million. At that time, the new energy vehicle-mounted battery power will reach approximately 5 billion KWH (kilowatt-hours) with 2.5 billion–5 billion KWH as the charging and discharging power. By 2035, the maximum installed capacity of wind power and photovoltaic power generation will not surpass 4 billion KW. The combination of vehicle-mounted energy storage battery and hydrogen energy could completely meet the demand of load balance. All in all, with the accumulation of experience over the past two decades, since 2001, China’s electric vehicles have “shifted to another path and led in the sector of new energy vehicles” worldwide. At the same time, China could build its advantage in terms of renewable resources with AI leading the world. It can be predicted that the period between 2020 and 2035 will be a new era when the revolution of new energy electric vehicles, the revolution of renewable energy, and the revolution of artificial intelligence will leapfrog and develop in a coordinated manner and create a Chinese miracle featuring the strategic product and industry of new energy intelligent electric vehicles. Focusing on one strategic product and sector, such three technological revolutions and three advantages will release huge power, which could help realize the dream of a strong vehicle nation and play a leading role in all directions. With the help of such advantages, China will create a large industrial cluster with the scale of the main industry exceeding 10 trillion yuan and the scale of related industries reaching tens of trillions of yuan. The development of new energy vehicles at a large scale will result in a new energy revolution, which will bring earthshaking changes to the traditional vehicle, energy and chemical industry, thus truly embracing the great changes unseen in a century since the replacement of carriages by vehicles. The technology revolution of new energy vehicle is advancing the rapid development of related interdiscipline subjects. From the perspective of technical background, the core technology of energy saving and new energy vehicles—the new energy power system technology—remains the frontier technology at the current stage. In 2019, China Association for Science and Technology released 20 key scientific and engineering problems, two of them (electrochemistry of high energy and density power battery materials, and hydrogen fuel battery power system) belonging to the scope of new energy system technology; the report of Engineering Fronts 2019 published by Chinese Academy of Engineering mentioned the power battery 4 times, fuel battery 2 times, hydrogen energy and renewable energy 4 times as well as electricity-driven/hybrid electric-driven system 2 times. Over the past two decades, China has accumulated plenty of new knowledge, new experience, and so many methods during the research and development regarding new energy vehicles. The “research series of key technologies on energy saving and new energy vehicles” are based on Chinese practice and the international frontier, aiming to review China’s research and development achievements on energy saving and new energy vehicles, meet the needs of technological development concerning China’s energy saving and new energy vehicles, reflect the key technology research trend of international energy saving and new energy vehicles, and promote the transformation and application of key technologies as regards China’s energy saving and new energy vehicles. The

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series involve four modules: vehicle control technology, power battery technology, motor driving technology as well as fuel battery technology. All those books included in the series are research achievements with the support of National Natural Science Foundation of China (NSFC), major national science and technology projects, or national key research and development programs. The publish of the series plays a significant role in enhancing the knowledge accumulation of key technologies concerning China’s new energy vehicle, improving China’s independent innovation capability, coping with climate change, and promoting the green development of the vehicle industry. Moreover, it could contribute to China’s development into a strong vehicle nation. It is hoped that the series could build a platform for academic and technological communication, and the author and readers could jointly make contributions to reaching the top in the international stage concerning the technological and academic level in terms of China’s energy saving and new energy vehicle. January 2021 (2021年1月)

Minggao Ouyang Academician of Chinese Academy of Sciences Professor of Tsinghua University (THU) Beijing, China

Preface

At present, along with the increasingly prominent world energy crisis and environmental issues, the automobile industry is facing severe challenges. On the one hand, there is a shortage of petroleum resources and automobiles are big consumers of fuel consumption. At present, only 35% ~ 40% of the heat energy generated by combustion of the fuel in the internal combustion engines is used for actual automobile driving. The increasing vehicle holdings aggravate this contradiction. On the other hand, the large use of oil-fueled automotive has aggravated environmental pollution, and the automobile exhaust accounts for 82% of CO, 48% of NOx , 58% of HC, and 8% of particulates in the urban atmosphere. In addition, the large amount of CO2 emitted by vehicles aggravates the greenhouse effect. The automobile carbon emissions are one of the most important components of national carbon emissions, accounting for about 7.5% of national carbon emissions, more than 90% of which comes from the combustion of fossil fuels such as gasoline and diesel fuel consumed during the use of vehicle holdings, accounting for about 80% of the total carbon emissions in the whole transportation field. In 2020, carbon emissions from vehicle use were about 720 million tons. In the face of these challenges, the Chinese government and industry have actively responded to formulate a carbon emission peak action plan by 2030. China’s declaration of carbon peak and carbon neutrality will put forward higher requirements for the low-carbon development of the automobile industry in the new era. New energy vehicles have become a key field for the development of the automobile industry in the twenty-first century in China, a major automobile country that produces 30% of the world’s automobiles. Intelligence, electrification, networking, sharing, and low carbonization are the main development direction of today’s automobile. New energy vehicles are different from traditional energy vehicles mainly in terms of power fuels. Traditional energy vehicles generally use gasoline and diesel, while the power sources of new energy vehicles have gone beyond traditional energy sources, including battery electric vehicles, fuel cell vehicles, hybrid electric vehicles, and hydrogen-powered vehicles.

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Preface

New energy vehicles can be roughly divided into two types: One is completely separated from oil supply to generate power, including battery electric vehicles, fuel cell vehicles, etc.; the other is to use less conventional energy to generate power, including hybrid and ethanol vehicles. With the increasingly stricter regulations on fuel consumption and emission, and the guidance of national strategies and policies, new energy vehicles are developing at a high speed, forming a situation where hybrid, battery electric, fuel cell, and other forms of electrification coexist. The electrification system is developing in a diversified way, and the electrification of the powertrain system has become an inevitable trend. The development of new energy vehicle technology has put forward higher requirements and challenges to the powertrain system. As a key component of the vehicle drive system from power source to wheels, the powertrain is one of the core research objects of vehicle performance development of new energy vehicles. This book is divided into two parts and comprehensively and systematically discusses the basic knowledge and practical cases of the new energy vehicle powertrain. Part I is about Basic Theory and Technology: From the perspective of system development and optimization technology, this part expounds the development trend, structure, and technical characteristics of BEV and HEV powertrain systems, related technologies and methods involved in design and development, as well as the principle and implementation process, energy management method, and strategy of the powertrain based on the battery electric and hybrid modes. Part II is about Engineering Practice and Test: It focuses on NVH test and optimization of the new energy vehicle powertrain, reliability and motor test of the powertrain parts, and the hardware-in-the-loop test technology of new energy vehicle. This book focuses on the combination of research theory and engineering practice. The theory and research experience summarized based on the author’s R&D practice in the mainstream automobile enterprises in Japan, Germany, and China for more than 30 years, and the research and practice in the national key projects of new energy vehicles and the projects of automobile enterprises combining production and study carried out by the author as a professor and doctoral tutor in the university for 7 years, as well as the powertrain R&D cases accumulated and learned by six doctoral students and more than 30 postgraduate students in the author’s research team from a large number of model analysis and experimental studies of more than ten research projects and topics, can provide technical information and reference for engineering technicians in related fields and undergraduate and graduate students in institutions of higher learning. The doctoral students Zang Libin, Qiu Zizhen, Cao Zhan, Li Guangxin, Wei Changyin, postgraduate students Wang Yi, Zhang Liming, Li Yanlin, Jia Jipeng, Zhang Yuquan, and other students of the New Energy Vehicle Research Center in my charge have made outstanding contributions to the content of this book. I would like to express my heartfelt thanks to them.

Preface

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In the process of writing this book, we have reviewed a large number of books, documents, and online materials and have been greatly inspired and developed ideas. I hereby express my deep gratitude to the authors concerned. Due to the author’s limited level, there are inevitably omissions and inadequacies in the book. Please give criticism and correction. Nanning, China February 2022

Yong Chen

Brief Introduction

This book systematically discusses the basic knowledge and engineering practice of the new energy vehicle powertrain. Part I is about Basic Theory and Technology: From the perspective of system development and optimization technology, this part expounds the development trend, structure, and technical characteristics of BEV and HEV powertrain systems, related technologies and methods involved in design and development, as well as the principle and implementation process, energy management method, and strategy of the powertrain based on the battery electric and hybrid modes. Part II is about Engineering Practice and Test: It focuses on NVH test and optimization of the new energy vehicle powertrain, reliability and motor test of the powertrain parts, and the hardware-in-the-loop test technology of new energy vehicle.

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Contents

Part I

Basic Theory and Technology

1 Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.1 Development Trend of New Energy Vehicles . . . . . . . . . . . . . . . . . . . 1.1.1 Types of New Energy Vehicles . . . . . . . . . . . . . . . . . . . . . . . . . 1.1.2 Development Status of NEV Drive Motor . . . . . . . . . . . . . . . 1.2 Classification and Basic Characteristics of New Energy Vehicles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.3 New Energy Vehicle Powertrain Technology Characteristics . . . . . . 1.3.1 New Energy Powertrain Requirements . . . . . . . . . . . . . . . . . . 1.3.2 Development Trend of NEV Drive Technology . . . . . . . . . . . Bibliography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Types and Control Technology of Drive Motors for New Energy Vehicles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2 Structure, Principle and Characteristics of Drive Motors . . . . . . . . . . 2.2.1 Induction Motor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2.2 Permanent Magnet Synchronous Motor . . . . . . . . . . . . . . . . . 2.2.3 Switched Reluctance Motor . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2.4 Wheel Hub Motor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3 Power Electronics and Inverter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3.1 Introduction to Power Electronic Power Devices . . . . . . . . . . 2.3.2 DC Power Supply Conversion . . . . . . . . . . . . . . . . . . . . . . . . . 2.3.3 Inverter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3.4 Practical Problems of Power Electronic Circuits . . . . . . . . . . 2.4 Vehicle Motor Control Technology . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.4.1 Vector Control Technology . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.4.2 Direct Torque Control (DTC) . . . . . . . . . . . . . . . . . . . . . . . . . . 2.4.3 Switched Reluctance Motor Control Technology . . . . . . . . . 2.4.4 Steady State Control Method of Induction Motor . . . . . . . . . Bibliography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Contents

3 New Energy Vehicle Powertrain Technology . . . . . . . . . . . . . . . . . . . . . . 3.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2 Hybrid AMT Technology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2.1 Electric Drive Powertrain . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2.2 Hybrid Powertrain . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2.3 Fuel Cell Powertrain Technology . . . . . . . . . . . . . . . . . . . . . . . 3.2.4 PEM Fuel Cell . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2.5 Audi A7-H-Tron Hydrogen Fuel Cell Vehicle . . . . . . . . . . . . 3.3 BEV AMT Technology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3.1 Development Trend of Electric Vehicle Transmissions . . . . . 3.3.2 Development of Two-Speed Automated Manual Transmission for Electric Vehicles . . . . . . . . . . . . . . . . . . . . . . 3.3.3 Two-Speed AMT Control Technology . . . . . . . . . . . . . . . . . . . 3.4 High-Strength Component Technology of Vehicle Powertrain . . . . . 3.4.1 Vehicle High-Strength Gear Technology . . . . . . . . . . . . . . . . . 3.4.2 Automobile High-Strength Bearing Technology . . . . . . . . . . 3.4.3 New Surface Treatment Technology for Powertrain Parts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.4.4 Influence of Oil on Fatigue Strength Life and Wear of Gear . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Bibliography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Energy Management Strategy Techniques for New Energy Vehicles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1.1 Energy Management Strategies for Battery Electric Vehicles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1.2 Energy Management Strategies for Hybrid Electric Vehicles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2 Powertrain Modeling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2.1 Energy Conversion System Model . . . . . . . . . . . . . . . . . . . . . . 4.2.2 Energy Storage System Model . . . . . . . . . . . . . . . . . . . . . . . . . 4.2.3 Vehicle Dynamic Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3 Feature Analysis of Typical Working Conditions of Key Components Under Different Energy Management Strategies . . . . . 4.3.1 Feature Analysis of Two Cycle Conditions of the Sample Vehicle . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3.2 Feature Analysis of Typical Working Conditions of Key Components Under Different Strategies . . . . . . . . . . . 4.4 Optimal Energy Management Strategies for Hybrid Electric Vehicles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.4.1 Energy Management Strategy Based on Dynamic Programming Algorithm Optimization . . . . . . . . . . . . . . . . . . 4.4.2 Optimization-Based Energy Management Strategies by Pontryagin’s Minimum Principle . . . . . . . . . . . . . . . . . . . .

95 95 100 100 104 125 127 129 129 129 131 145 157 157 167 173 178 180 183 183 183 186 194 194 196 200 205 205 206 213 213 225

Contents

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4.4.3 Real-Time Optimization Energy Management Strategy Based on Approximate Minimum Principle . . . . . . 4.5 Intelligent Energy Management Strategies for Hybrid Electric Vehicles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.5.1 Instantaneous Optimization Energy Management Strategy Based on Online Self-Learning Adjustment . . . . . . 4.5.2 Energy Management Strategy Based on Neural Network Speed Prediction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Bibliography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Part II

231 233 233 237 246

Engineering Practice and Test

5 NVH Test and Optimization for New Energy Vehicle Powertrain . . . . 5.1 NVH Test Technology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.1.1 Foundation of Engineering Noise . . . . . . . . . . . . . . . . . . . . . . . 5.1.2 Powertrain NVH Test Technology . . . . . . . . . . . . . . . . . . . . . . 5.2 NVH Optimization Technology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.2.1 Powertrain NVH Optimization Technology . . . . . . . . . . . . . . 5.2.2 Vibration and Noise Optimization of Electric Drive Powertrain . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.3 Practical Case of Vibration and Noise Optimization of Pure Electric Bus Powertrain . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.3.1 Vehicle NVH Performance Test . . . . . . . . . . . . . . . . . . . . . . . . 5.3.2 Relationship Between Powertrain Parameters and Time in Three Test Solutions of Vehicle Road Test . . . . 5.3.3 Order Analysis of Vehicle Powertrain Transmission and Motor Vibration and Noise . . . . . . . . . . . . . . . . . . . . . . . . 5.3.4 Vibration Test Results and Analysis for Powertrain in Road Test . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.3.5 Interior Noise Test Results in Vehicle Road Test . . . . . . . . . . 5.4 Practical Case of Vibration and Noise Optimization of Two-Speed Automatic Transmission for Battery Electric Vehicles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.4.1 Test Purpose and Preparation . . . . . . . . . . . . . . . . . . . . . . . . . . 5.4.2 Test Procedure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.4.3 Result Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.4.4 Optimization Design of Transmission Gear Micro Modification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.4.5 Transmission Vibration and Noise Simulation and Test Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.4.6 Prediction and Optimization of Transmission Case Radiated Noise . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Bibliography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

251 251 253 254 268 268 275 281 281 288 290 291 293

295 295 298 302 336 345 362 381

xxii

Contents

6 Vehicle Powertrain Reliability Test Technology . . . . . . . . . . . . . . . . . . . . 6.1 NEV Powertrain Reliability Test Technology . . . . . . . . . . . . . . . . . . . 6.1.1 Overview of Test Equipment . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.1.2 Reliability Test of Key Components . . . . . . . . . . . . . . . . . . . . 6.1.3 Shift Performance Test . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.2 Test Technology for Powertrain Components . . . . . . . . . . . . . . . . . . . 6.2.1 Gear Fatigue Test Technology . . . . . . . . . . . . . . . . . . . . . . . . . 6.2.2 Bearing Fatigue Test Technology . . . . . . . . . . . . . . . . . . . . . . . 6.2.3 Tribological Test Characteristics of Parts and Components . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.3 Motor Reliability and Endurance Test Specification . . . . . . . . . . . . . 6.3.1 Reliability Test Specification . . . . . . . . . . . . . . . . . . . . . . . . . . 6.3.2 Endurance Test Specification . . . . . . . . . . . . . . . . . . . . . . . . . . Bibliography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

383 383 383 385 390 392 392 402

7 New Energy Vehicle Hardware-In-The-Loop Test Technology . . . . . . 7.1 HiL Test Platform Architecture of Extended-Range Electric Logistics Vehicle HCU . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.1.1 HiL Test Hardware Platform Building . . . . . . . . . . . . . . . . . . . 7.1.2 HiL Test Software Platform Building . . . . . . . . . . . . . . . . . . . 7.1.3 CAN Communication Diagnostic System Model Based on LabVIEW . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.2 Energy Management HiL and MiL Test . . . . . . . . . . . . . . . . . . . . . . . . 7.2.1 Selection of Driving Cycles . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.2.2 Types of Driving Cycles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.2.3 HiL Simulation Test . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.2.4 MiL Simulation Test . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Bibliography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

425

406 420 420 420 422

425 426 427 427 429 429 429 434 443 446

About the Author

Yong Chen is a professor and doctoral supervisor at the School of Mechanical Engineering, Guangxi University, and a member of the Society of Automotive Engineering of China. He has been engaged in automotive transmission system and automatic transmission research and development for several years, and has worked as a senior technician in automatic transmission research and development at the Technical Center of Nissan Automotive Automatic Transmission Company in Japan for 18 years. After returning to China in 2008, he served as the vice president and chief engineer of Geely Automotive Research Institute, as well as a professor and doctoral supervisor at the School of Mechanical Engineering at Hebei University of Technology. He has presided over one national 863 project and one 12th five-year science and technology support project, and several national key research and development programs. He has published more than 150 articles in international and national technical journals and 165 invention patents, and has also published two academic monograph. He received the China Industry-University Research Cooperation Innovation Award in 2018, First Prize of China Automotive Industry Science and Technology Progress Award, Gold Award at the 48th Geneva International Invention Exhibition, and other awards.

xxiii

Part I

Basic Theory and Technology

Chapter 1

Overview

1.1 Development Trend of New Energy Vehicles With the rapid development of economy, energy shortage, environmental pollution and traffic congestion have seriously affected people’s living standards. With the characteristics of low pollution, low energy consumption and low emission, new energy vehicles have gained the attention of various national governments around the world, and have risen to national strategic level in China. China’s dependence on foreign crude oil is increasing year by year. Data from the National Energy Administration show that in 2020, China’s dependence on foreign crude oil reached 73%, seriously affecting the energy security as it exceeds the internationally recognized red line for energy security of 50%. China has a weakness in energy, and the development of new energy vehicles is of great strategic significance to China. In recent years, China has clearly put forward to the world the national goal of carbon peak in 2030 and the carbon neutrality in 2060. New energy vehicles are the most important link in the sustainable development of the automobile industry. The development of new energy vehicles can alleviate the energy and environmental pressure. In other words, only the large-scale development of new energy vehicles can successfully realize the new energy revolution, and only the realization of the new energy revolution can successfully achieve China’s carbon neutrality goal. New energy vehicle refers to a vehicle with new technology and new structure that uses the unconventional vehicle fuel as the power source (or use conventional vehicle fuel and new on-board power plant) and integrates the advanced technology of the traditional vehicles in the power control and drive. Where, unconventional vehicle fuel refers to fuel other than gasoline, diesel, natural gas, liquefied petroleum gas, ethanol gasoline, methanol and dimethyl ether. New energy vehicles include battery electric vehicle (BEV), extended-range electric vehicle, hybrid electric vehicle (HEV), fuel cell electric vehicle (FCEV), hydrogen-powered vehicle and other new energy vehicles, etc.

© Huazhong University of Science and Technology Press and Springer Nature Singapore Pte Ltd. 2023 Y. Chen, New Energy Vehicle Powertrain Technologies and Applications, Key Technologies on New Energy Vehicles, https://doi.org/10.1007/978-981-19-9566-8_1

3

4

1 Overview

In 2018, under the downward environment of automobile consumption, China’s new energy vehicles reversed the trend and walked out of a beautiful growth curve. The total sales volume of new energy vehicles reached 1.256 million, an increase of 61.7% on year-on-year basis; the sales volume of new energy passenger vehicles was 1.053 million, an increase of 82% on year-on-year basis; the sales volume of new energy commercial vehicles was 203,000, an increase of 2.6% on year-on-year basis. Among them, the sales volume of battery electric vehicles was 984,000, an increase of 50.8% on year-on-year basis, accounting for 78.3% of the total sales; the sales volume of plug-in hybrid electric vehicles was 271,000, an increase of 118% on yearon-year basis, accounting for 21.6%; the sales volume of fuel cell electric vehicles was 1,527. At present, the battery electric vehicles occupy the dominant position of new energy vehicles. Especially in the field of commercial vehicles, the sales volume of battery electric vehicles accounts for 96.6%; in the field of passenger vehicles, the sales volume accounts for 74.8%. In 2020, the production and sales volume of new energy vehicles reached 1.366 million and 1.367 million, respectively, an increase of 7.5% and 10.9% n year-on-year basis, reaching a record high. In 2021, the production and sales volume of new energy vehicles reached 3.545 million and 3.521 million, respectively, and the market share of new energy vehicles reached 13.4%. Similar to traditional fuel vehicles, the extensive use of new energy vehicles needs the construction of a complete energy supply system. A fast, efficient and wide energy supply system is the premise of the large-scale development of new energy vehicles. The energy supply system for electric vehicles at home and abroad has been gradually set up, including two modes, self-charging and battery swap. Self-charging mode is the focus of research in many countries. In terms of technical route, it mainly includes normal charging and quick charging modes: The normal charging mode can make full use of the off-peak hours of power consumption at night and meet the needs of vehicle operation, which is mostly concentrated in the residential areas and office area parking lots; the quick charging mode is a supplement to electric power under special demand, which is mainly built in airports, railway stations, hospitals, shopping centers, gas stations and other public places. The battery swap mode is a way to separate the vehicle and the battery, allowing the user to get the energy supply in time like refueling. Table 1.1 shows the advantages and disadvantages of charging/battery swap of new energy vehicles currently.

1.1.1 Types of New Energy Vehicles According to the current energy types used in the automotive field, the technical routes of new energy in various countries can be mainly divided into three categories, which are introduced in the following order.

1.1 Development Trend of New Energy Vehicles

5

Table 1.1 Advantages and disadvantages of charging/battery swap of new energy vehicles Advantages and disadvantages Charging

Battery swap

Advantages

Supplement the energy using the spare time at night; low standards and interchangeability requirements for batteries; save the energy

Quickly supplement the energy and meet the user’s immediate demands for mileage; no need for large-scale construction of charging facilities; centralized charging in the charging center, with low requirements for battery exchange stores

Disadvantages

Put forward requirements for the construction of the charging network and require interconnectivity between charging piles to ensure convenience; normal charging takes a long time, and quick charging affects battery life

Batteries need to be standardized and serialized, involving a strong push at the national level

1.1.1.1

Battery Electric Vehicle (BEV)

The power of the battery electric vehicles is provided by batteries, so the performance of the vehicles largely depends on the performance of batteries, and battery energy storage will directly affect the driving ability of vehicles. The electric vehicle will produce torque under the joint action of the motor and the control device to directly drive the vehicle. When the vehicle is running, the torque will have a direct impact on the speed, acceleration and tension factors of the vehicle. In addition, electric motors of the electric vehicles have been adjusted and redesigned so that they can produce a high torque even at low running speed, which cannot be realized by traditional internal combustion engines. The development of battery electric vehicles has become the consensus of the world. In 2020, the world’s BEV production was 3.125 million, and China’s BEV production exploded with 1.115 million. At present, the battery electric vehicles in China have basically reached the world’s advanced level in terms of technology and quality. In particular, the key components of the new energy vehicle drive system, such as traction battery, drive motor and control unit, have gone from following to running and even leading. Moreover, with the continuous improvement of the policy system, China’s electric vehicles will reach the world-class level in three to five years. According to the 13th Five-year Plan on Science, Technology and Innovation, during the “13th Five-Year Plan”, China gave priority to and particularly supported the development of battery electric vehicles, broke through core technologies, and significantly increased the sales percentage of battery electric vehicles on the market. According to the Research and Analysis on the Development of China’s Battery Electric Vehicle Industry from 2016 to 2022 and Prediction of Development Trend released by China Industry Research Network, the battery electric vehicles are accelerating to be introduced into the market and will have a relatively large scale from 2020 to

6

1 Overview

2030; the intelligent vehicle, lightweight body, clean power, low price and convenient charging and battery swap will be the development trend of battery electric vehicles in the future. Driven by favorable policies of national goal programming of carbon peak in 2030 and carbon neutrality in 2060, the market demand support, the rapid technological progress, cost price reduction and other factors, China’s battery electric vehicles are undergoing rapid development in the once-in-a-century great change of the world auto industry, and will certainly become an important driving force for the improvement of the global popularity of electric vehicles.

1.1.1.2

Hybrid Electric Vehicle (HEV)

Hybrid electric vehicle (HEV) is defined as a vehicle driven by a variety of energy sources during driving. At present, the main drive mode is fuel and electricity. Although pure electric drive can reduce environmental pollution, many times there will be driving range concerns and significantly decreased driving range in the winter. Therefore, the electricity and fuel are mixed to reduce greenhouse gas emissions and solve the problem of insufficiency battery power and battery carrying capacity. For manufacturers, the development of hybrid electric vehicles is a further extension on the existing development platform, which can realize the full utilization of the existing automobile and parts production lines. As shown in Fig. 1.1, many market users’ familiarity and recognition of existing brands also promote hybrid electric vehicles to occupy an important place in new energy vehicles. At present, the hybrid vehicles used widely on the market are plug-in hybrid electric vehicles, which are not only equipped with the power battery with relatively large capacity, but also with the fuel drive system. When the battery capacity is sufficient, the battery can be used to drive the vehicle. When the battery energy is

Ordinary HEV

PHEV 2017

2018

2019

BEV 2020

Fig. 1.1 Sales proportion of various hybrid and battery electric vehicles from 2017 to 2020

1.1 Development Trend of New Energy Vehicles

7

lower than a certain level, it can be converted to fuel drive. The hybrid electric vehicles are relatively mature in the North American and Japanese markets. After several years of efforts, the hybrid electric vehicles in China have also made great progress in the fields of passenger vehicles and urban public transportation. In the context that the automobile battery technology is not mature enough, the fuel (gas) hybrid electric vehicles (HEV) are a compromise between driving pleasure and emission control. Although they are called transition products, they will surely exist for a long time because they can continue the industrial base of traditional vehicles and become the carrier of the “test field” of electric vehicle technology. The hybrid electric vehicles can take the best advantage of the engine and electric motor to improve the fuel economy and reduce emissions. Compared with conventional vehicles of the same performance, the hybrid electric vehicles are more advantageous in terms of energy efficiency and emission. Compared with the battery electric vehicles, the hybrid electric vehicles have lower costs due to the greatly reduced battery capacity. In the current market, the price of hybrid electric vehicles (HEV and PHEV) is about 20% higher than that of traditional vehicles. Reducing the cost is the main direction to improve the competitiveness of hybrid electric vehicles. Meanwhile, improving the energy recovery efficiency in the process of driving is also the focus of the major vehicle enterprises. With the increasingly severe environmental legislation in various countries, the performance of hybrid electric vehicles is increasingly improved and the cost is constantly reduced, and their market share will gradually increase, with a broad prospect in a considerable period of time. Hybrid electric vehicles have the following advantages: (1) A hybrid electric vehicle has at least two different energy converters (e.g. electric motor and gasoline engine) and two different energy storage systems (e.g. lithium battery pack and fuel tank), which have high energy storage capacity and conversion efficiency. (2) With excellent driving performance, the hybrid electric vehicles have short starting and acceleration time with the help of the electric motor. (3) High fuel economy. Depending on the degree of mixing, hybrid electric vehicles can be classified into weak hybrid, light (medium) hybrid, strong hybrid and plug-in hybrid. 1. Weak HEV Weak hybrid (or called mild hybrid) electric vehicle technology mainly includes startstop, BSG (Belt-driven Starter/Generator) and ISG (Integrated Starter/Generator) technology. The 6 kW motor is still driven by 12 V power supply voltage, which cannot realize pure electric driving. The voltage provided by the motor is mainly used to start the engine. The kinetic energy of the weak hybrid vehicle can be recovered by additional motor. Although the weak hybrid vehicle has limited ability to reduce fuel consumption and improve emissions, it has the lowest cost to transform traditional the internal combustion engine. Figure 1.2 shows the layout of a weak hybrid vehicle.

8

1 Overview

Disconnection control module of 36V battery with a disconnecting switch

36V wiring 12V battery (not shown) Generator control module

36V hybrid electric battery

Starter motor Starter motor

Fig. 1.2 Layout of weak hybrid vehicle

The BSG technology is commonly used in the weak hybrid vehicle, such as BSG model of Chery A5 (10 kW motor), which usually saves less than 10% of fuel. The motor is not directly involved in driving, but mainly used for starting and recovering the braking energy. The weak hybrid vehicle can save 3–6% of fuel. As the hybrid electric vehicle with the lowest transformation cost, it is widely used by various automobile manufacturers. The representative model is 2019 Audi A6 marketed in China, and all its series are equipped with at least a 12 V weak hybrid system. 2. Light (medium) HEV The vehicle can be called a light hybrid vehicle when the power provided by the motor reaches 6–20 kW under the power supply voltage of 42–144 V. Different from the weak hybrid vehicle, the light hybrid vehicle, in addition to automatic start-stop and kinetic energy recovery, is equipped with a motor that can assist the internal combustion engine during startup and acceleration, and can power other electric equipment, such as air conditioning, of the vehicle. However, due to the limited power of the motor, the light hybrid vehicle still cannot achieve battery electric driving. The ISG technology is commonly used in the light hybrid vehicle, such as Buick LaCrosse EcoHybrid (15 kW motor), which usually saves about 20% of fuel. The light hybrid vehicle can save 10–20% fuel. Due to its high fuel economy and low transformation cost, it is also favored by major automobile manufacturers, such as the current popular 48 V light hybrid vehicle and the 90 V light hybrid vehicle launched in the United States.

1.1 Development Trend of New Energy Vehicles

9

Fig. 1.3 Schematic diagram of PHEV

3. Strong HEV and PHEV A hybrid electric vehicle with the motor power more than 40 kW and the power supply voltage of 250 V is a strong hybrid electric vehicle. The strong hybrid electric vehicle is represented by Toyota Prius (50 kW motor), which can save 40% of fuel. The electric motor of the strong hybrid electric vehicle can not only ensure and match the torque output of the internal combustion engine, but also achieve battery electric driving. The plug-in hybrid, on the basis of strong hybrid, can charge the vehicle battery through the grid, and its fuel economy can be as high as 30% to 40%. Figure 1.3 shows the schematic diagram of a plug-in hybrid electric vehicle. The PHEV can provide a better fuel economy ratio, but will consume a certain amount of electrical energy. For example, the Volkswagen Golf TwinDrive (130 kW motor) consumes 8 degrees of electric energy and 2.5L of fuel per 100 km, according to test data.

1.1.1.3

Fuel Cell Electric Vehicle (FCEV)

The FCEV uses the fuel cell, a new technology that is different from rechargeable batteries. During operation, the FCEV mainly relies on the fuel cell system, drive motor, power battery and hydrogen storage system. As the battery works, chemical reactions take place that convert the chemical energy of substances into electric energy, so as to drive the vehicle. At present, the fuel cell widely used is hydrogen– oxygen fuel cell, in which, H2 and O2 oxidize to generate H2 O. This process will generate a lot of heat, which will be collected to form electric energy, and then the vehicle can be driven. There are three hydrogen storage methods in the existing technology, among which, the gaseous and liquid hydrogen storage are the most mainstream. With technological breakthroughs in the future, the hydrogen storage in the solid alloy

10

1 Overview

is expected to become the mainstream hydrogen storage method. Table 1.2 lists the comparison of three hydrogen storage methods: gaseous hydrogen storage, liquid hydrogen storage and hydrogen storage in solid alloy in different aspects. By the conductive ion type, fuel cells can be classified into alkaline fuel cell (AFC), phosphoric acid fuel cell (PAFC), molten carbonate fuel cell (MCFC), solid oxide fuel cell (SOFC) and proton exchange membrane fuel cell (PEMFC). At present, among the five types of fuel cells, the PEMFC has the advantages of operating temperature lower than 120 °C, short startup time, simple structure and the broadest application prospect. It will be the fastest developing fuel cell technology in the future. Table 1.2 Comparison of three hydrogen storage methods Gaseous hydrogen storage Hydrogen storage method

Gaseous hydrogen storage

Liquid hydrogen storage

Hydrogen storage in solid alloy

Storage device

Heavy pressure container

A cooling device is required, equipped with excellent thermal insulation protection layer

Metal hydride hydrogen storage device made of rare earth and other hydrogen storage materials

Technical support

Hydrogen compression Cooling technology and It can reversibly technology adiabatic measures absorb, store and release large quantities of hydrogen gas at a given temperature and hydrogen pressure

Application status

All the FCEVs launched by major companies store the hydrogen by the high-pressure gaseous hydrogen storage method; in contrast, it is more suitable for passenger vehicles

The auxiliary system is relatively large, more suitable for medium and large/heavy vehicles and commercial buses

The hydrogen release process is a chemical reaction process, which requires a certain temperature and pressure environment, so it is not convenient to use

Related companies SinoHytec, Sinoma and Hydrogenious, Furui Jingcheng Special Equipment

ECDOvonic, Whole Win (Beijing)

Development trend Low-cost, simple and feasible and most mainstream hydrogen storage method

High hydrogen storage density and high safety, expected to become the mainstream hydrogen storage method in the future

More rational hydrogen storage method with high hydrogen storage density but high requirements for conditions

1.1 Development Trend of New Energy Vehicles

11

1.1.2 Development Status of NEV Drive Motor At present, the companies in the United States, Europe and Japan that provide the NEV drive systems are growing rapidly and have made great progress in reducing the motor production cost and improving the motor efficiency and the integration of motor/engine. The industrial chain has been gradually improved. In contrast, the permanent magnet synchronous motor, AC asynchronous motor and switched reluctance motor developed independently in China have been used in batches by domestic vehicle enterprises, and the power of the products covers the power demand of the vehicles below 200 kW. The products of some enterprises have been exported to the United States and Europe. Domestic motors are mainly supplied in two ways: first, the drive motor systems are jointly developed by the enterprises such as Siemens, Bosch, Continental and Hitachi with the OEMs in the form of joint venture; second, the motor systems are researched and developed independently by powerful independent motor manufacturers, such as Jing-Jin Electric Technologies, Shanghai Edrive, Broad-Ocean Motor and Tianjin Santroll and provided for the automobile enterprises.

1.1.2.1

Motor Technology Development Status

The drive motors are mainly classified into DC motor, AC motor and wheel hub motor, among which, DC and AC motor can be further classified. Among them, the AC asynchronous motor, permanent magnet synchronous motor and switched reluctance motor attach more attention. Through the comparative analysis of several common motors (see Table 1.3), the permanent magnet synchronous motor, with the characteristics of high efficiency, wide speed range, small volume, light weight. High power density and low cost, becomes the main drive motor in the battery electric passenger vehicle market. In terms of industry matching, the permanent magnet synchronous motor and AC induction motor are mainly used for new energy passenger vehicles, of which, the permanent magnet synchronous motor is used more frequently, with relatively large speed range and relatively high efficiency, but it needs to use expensive permanent magnet material NdFeb; some European and American vehicles adopt the AC induction motor, mainly because of the lack of rare earth resources, and for the purpose of reducing the motor cost. With the disadvantages of small speed interval and low efficiency, the AC induction motor requires a governor with higher performance to match the performance. With the rapid development of the new energy vehicle market, the drive motor market has great potential, which has attracted many enterprises and capital. The parameters of permanent magnet synchronous motors of typical drive motor enterprises at home and abroad are compared as shown in Table 1.4. On the whole, the drive motor in China has made great progress and all kinds of products meeting the requirements of new energy vehicles products have been developed independently. Some main performance indicators have reached the international advanced level of

12

1 Overview

Table 1.3 Comparison of main performance and parameters of several common motors Comparison item

DC motor

AC asynchronous motor

Permanent magnet synchronous motor

Switched reluctance motor

Power density

Low

Medium

High

Relatively high

Power factor/(%)

–

82–85

90–93

60–65

Peak efficiency/(%)

85–89

90–95

95–97

80–90

Load efficiency/(%)

80–87

90–92

85 ~ 87

78–86

Overload capacity/(%)

200

300–500

300

300–500

Speed range/(r/min)

4000–6000

12,000–15,000

4000–15,000

> 15,000

Constant power area

–

1:5

1:2.25

1:3

Overload coefficient

2

3–5

3

3–5

Reliability

Medium

Relatively high

High

Relatively high

Structure robustness

Low

High

Relatively high

High

Volume

Large

Medium

Small

Small

Weight

Weight

Medium

Light

Light

Speed regulating control performance

Very good

Medium

Good

Good

Motor cost

Low

Medium

High

Medium

Control unit cost

Low

High

High

Medium

the same power level, but there is still a certain gap with foreign countries in the peak speed, power density and efficiency. In terms of technical indicators, there are still the following differences between domestic and foreign motors: (1) The peak speed is an important indicator of the driver motor and also the most obvious indicator of domestic motor compared with foreign motor. The peak speed of most domestic permanent magnet synchronous motors is below 14,000 r /min, while of the foreign ones is above 14,000 r/min. (2) Although the domestic motors can basically reach the international level in terms of power, they have certain weight disadvantages under the same power condition. At present, the power density of the permanent magnet synchronous motors in China is mostly in the range of 2–3.5 kW /kg. (3) In terms of motor efficiency, the highest efficiency of domestic motors has reached 94–96%, reaching the level of Siemens, Remy and other enterprises. However, there is still a certain gap in the area of high efficiency area, such as the

1.1 Development Trend of New Energy Vehicles

13

Table 1.4 Comparison of parameters of permanent magnet synchronous motors of typical drive motor enterprises at home and abroad Enterprise

Peak power/kW

Peak torque/(N·m)

Peak speed/(r/min)

Cooling mode

JEE Automation

20

120

5000

Natural cooling

45

170

6000

Natural cooling

50

215

7200

Water-cooled

90

175

14,000

Water + ethylene glycol

103

230

12,000

Water + ethylene glycol

140

270

12,000

Water + ethylene glycol

40

260

7600

Water-cooled

50

200

7200

Water-cooled

90

280

10,000

Water-cooled

72

100

5600

Water-cooled

45

128

9000

Water-cooled

30

160

6500

Water-cooled

Jing-Jin Electric Technologies

Shanghai Edrive

Broad-Ocean Motor

60

200

8000

Water-cooled

Siemens

30–170

100–265

12,000

Water-cooled

Nissan

80

280

9800

Water-cooled

US Remy

82

325

10,600

Water-cooled

US UQM

75

240

8000

Water-cooled

Volkswagen Kassel

85

270

12,000

Water-cooled

proportion of areas with the system efficiency greater than 80%. The proportion of high efficiency area of most motors in China is concentrated in 70–75%, with a few motors basically reaching 80% as foreign motors. (4) The cooling mode of the motor has gradually developed from natural cooling to water cooling. At present, the cooling mode is mainly water cooling in China, while it is developed to oil oiling in foreign advanced motor enterprises. Some domestic motor enterprises, such as Jing-Jin Electric Technologies and Tianjin Santroll, have also developed and mass produced the oil-cooled motors to further improve the cooling efficiency of motors and reach the international advanced level. 1. The permanent magnet synchronous motor becomes the mainstream trend At present, the permanent magnet synchronous motors are used in more than 90% of the new energy vehicles in China, and AC asynchronous motors are mainly used in the American automobile enterprises led by Tesla and some European enterprises. On the one hand, this is related to Tesla’s initial choice of technological path: the AC

14

1 Overview

induction motor is cheap, and its large size does not hinder American vehicles. On the other hand, the high-speed interval efficiency performance of AC motors in the United States is better because of the developed highway network. The permanent magnet synchronous motor is still most widely used for new energy vehicles in other countries, including China and Japan, mainly because it is suitable for the country’s road conditions. The permanent magnet synchronous motor can still maintain high efficiency in repeated start/stop, acceleration and deceleration, which is the best choice for the restricted condition of expressway network. Vehicles mostly travel at medium and low speeds, so it is more suitable to use the permanent magnet synchronous motor with higher efficiency during acceleration and deceleration. Besides, it is also an important factor of rich rare earth reserves in China and supporting basis for rare earth permanent magnet industry in Japan. The permanentmagnet synchronous motor drive systems are basically adopted in the Japanese auto companies like Toyota, Honda, Nissan, such as Toyota Prius and Honda CIVIC. Japan leads the world in the development of hybrid electric vehicles, among which Toyota Prius is the most famous. The rotor of the Toyota Prius motor uses an Interior Permanent Magnet (IPM) system, in which the magnetic pole is embedded in the rotor and an electromagnetic steel sheet is rolled over the rotor to avoid winding on the surface of the electromagnet to reduce the cost. The IPM rotor system can achieve greater torque and higher efficiency by superimposing a hysteresis torque on the electromagnetic torque, and the phase current control helps IPM rotor to achieve higher torque output and efficiency. As shown in Fig. 1.4, the electromagnetic torque is almost proportional to the current. The current phase is controlled to be 90° ahead of the magnetic pole phase to obtain the maximum torque. The drive motor is one of the three core components of new energy vehicles. Compared with traditional industrial motors, new energy vehicles have higher technical requirements for the drive motors. In terms of the comprehensive performance, the permanent magnet synchronous motor is most advantageous and most representative of the development direction of the new energy vehicle drive motors. 2. Development bottleneck of permanent magnet synchronous motor At present, the permanent magnet synchronous motor is considered the main technical route for battery electric passenger vehicles, so how to further improve its performance has become a key issue in the industry. Currently, the permanent magnet synchronous motor is faced with the following technical difficulties. (1) There are two ways to increase the power: increasing the torque and increasing the speed. The main problem of the former is that the overload current increase results in high heating value and brings greater pressure to heat dissipation; the main problem of the latter is high ferromagnetic loss at high speed and it is required to use high-performance low-saturation silicon steel sheet, so as to increase the cost, or to use complex rotor structure, but which can affect the power density. (2) The permanent magnet material is also an important factor that restricts the performance improvement of the permanent magnet synchronous motor. The

1.1 Development Trend of New Energy Vehicles

15

Electromagnetic

Phase advance angle

Reluctance

Salient pole

Magnet

Fig. 1.4 Schematic diagram of magnetic pole moment

permanent magnet NdFeB commonly used at present mainly has the disadvantages of poor temperature stability, irreversible loss, high temperature coefficient and serious magnetic loss at high temperature, affecting the performance of the motor. (3) The difficulty of the permanent-magnet synchronous motor in production process is an important factor that restricts its large-scale application in passenger vehicles. The reliability, consistency and other performance indexes of the motor products of domestic enterprises still have great room for improvement, especially with the expansion of the battery electric passenger vehicle market scale, the annual output of 100,000 class has brought great challenges to permanent magnet synchronous motor enterprises. Some key materials of Chinese motors reply on imports, resulting in high purchase cost. The utilization rate of the permanent magnet motor raw materials is about 10% lower than overseas, which leads to the higher production cost, and it needs to be improved gradually. To sum up, after nearly 20 years of development, the motor system of new energy vehicles in China has made great progress from research and development to mass production and its basic function and performance have been comparable with the international level. However, there is still room for further improvement of some

16

1 Overview

products in the consistency, reliability, technological level and digital production management and the use requirements of automobiles. 3. Development of wheel hub motor In terms of technology status, the wheel hub motor was first loaded into the battery electric vehicles by Porsche in 1900. After more than 100 years of development, many American and Japanese main engine factories increase the development of the wheel hub motor. Moreover, the motor companies (such as UK Protean, French TM4, etc.) and tire enterprises (such as Michelin and Bridgestone) have also developed wheel hub motor products. Domestically, Vie Science and Technology and the UK Protean, Asia Pacific and Slovenia wheel hub motor companies have developed the wheel hub motor products by joint venture. In terms of the overall advantages and disadvantages, most wheel hub motors adopt the permanent magnet synchronous motor. In recent years, domestic and foreign automobile and parts enterprises have made many attempts to drive battery electric and hybrid passenger vehicles with wheel hub motors. The advantages and disadvantages of the wheel hub motor are shown in Table 1.5 after comparison. The main problem in the performance of the wheel hub motor is the influence of the increase of unsprung mass on the comfort and controllability. The deep integration of the hub drive and suspension system as well as the torque vector distribution are also faced with many technical problems. In addition, there are heat dissipation problems and braking energy recovery problems after the integration of the wheel hub motor and the wheel hub, the reliability and durability of the wheel hub motor driving power system under the condition of strong external force and high overload impact, and the resulting cooling, shockproof, waterproof and dustproof problems. Table 1.5 Advantages and disadvantages of wheel hub motor No.

Advantages

Disadvantages

1

High efficiency: Drive wheels directly to avoid transmission loss, improve efficiency and save energy

Increased unsprung mass: affect the control, slow suspension, slow acceleration response and difficult electronic differential braking at high speed

2

Easy control: Direct control of wheel speed and torque can reduce the turning radius and improve the braking energy recovery efficiency

Difficult heat dissipation: a lot of heat will be generated in the wheel hub during braking, which poses a great challenge to the heat dissipation of the built-in motor

3

Excellent space configuration: Integrated with the hub to save the forecabin layout space and save the space of the transmission system

Three prevention challenges: the motor is built into the wheel hub, the working environment is harsh, and the difficulty of shakeproof, waterproof and dustproof is increased

4

Modularization: High integration, easy to realize modularization, able to avoid repeated development, shorten development cycle and reduce costs

High braking energy consumption: With low eddy current braking energy, it needs to work with the mechanical braking system, leading to large energy consumption

1.1 Development Trend of New Energy Vehicles

17

In terms of industry prospect, the development prospect of the wheel hub motor is not ideal due to the different attitudes of different industry subjects. New energy main engine factories mainly wait and see for the wheel hub motor, while traditional motor enterprises have not yet developed and planned the wheel hub motor, lack the support of mature mass produced vehicles and only rely on some motor joint ventures to promote the wheel hub motor. Meanwhile, the problems of high cost and system complexity of the wheel hub motor have not been solved, restricting the development of the wheel hub motor in the field of new energy passenger vehicles. However, it is worth noting that in 2021, China included the development of prototypes of the wheel hub motor for commercial and passenger vehicles in the overall planning for the development of new energy vehicles. The research on new materials and new technology of the wheel hub motor, the deep fusion technology of the wheel hub motor drive system and the application in the vehicle will be fully carried out, which is very consistent with the development direction of electric, intelligent, networked and automatic driving of new energy vehicles.

1.1.2.2

Future Drive Motor Development Trend Analysis

Through the above analysis and combined with market research, it can be seen that on the battery electric passenger vehicle market in the next few years, the permanent magnet synchronous motor will still occupy the mainstream, and the proportion of the AC asynchronous motor will shrink year by year. With the gradual maturity of the wheel hub motor technology and the decline of cost, its matching volume in the battery electric passenger vehicle market will have a certain growth, while the switched reluctance motor is limited by volume and noise problems, so it is less likely to be used in a short time for passenger vehicles. Meanwhile, the driving range of the pure electric vehicles is bound to be an extremely important index, and the high efficiency of the permanent magnet synchronous motor can better improve the driving range. Moreover, the successful development of the NdFeB permanent magnet with high heat resistance and high magnetic properties as well as the further development and improvement of power electronic components make the development of rare earth permanent magnet synchronous motors further perfect. With the rapid development of the new energy vehicle driving technology, many new structures or new concepts of motors have been put into research. Among them, the new permanent magnet brushless motor is one of the most promising motors, including hybrid excitation type, hub type, double stator type, memory type and magnetic gear compound type. In addition, the amorphous motor has also begun to enter the field of new energy vehicles. As a new generation of high-performance motor, it will play a huge role in promoting the development of the new energy vehicle industry with its own advantages. According to the analysis of Energy-saving and New Energy Vehicle Technology Roadmap 2.0 led by China Society of Automotive Engineers, in general, the main development trends of drive motors include the following aspects: integration of

18

1 Overview

power electronic control units and integration of electromechanical coupling; high efficiency to increase power density and reduce cost; cooperation with the control units to continuously improve the intelligent and digital level of the drive system.

1.2 Classification and Basic Characteristics of New Energy Vehicles By the power sources and energy storage device in the process of vehicle running, the new energy vehicles are generally classified into the battery electric vehicle (BEV), hybrid electric vehicle (HEV) and fuel cell electric vehicle (FCEV). The battery electric vehicle is a vehicle driven by an electric motor. The driving electric energy of the motor is derived from the rechargeable battery or other energy storage devices of the vehicle. The hybrid electric vehicle is one that can derive power from at least two types of on-board stored energy: consumable fuel and rechargeable energy. The hybrid electric vehicles are mainly classified into series hybrid electric vehicle (SHEV), parallel hybrid electric vehicle (PHEV) and combined hybrid electric vehicle. The basic feature of the SHEV is that the driving force of the vehicle is derived only from the motor; the basic feature of the PHEV is that the driving force of the vehicle is supplied by the motor and the engine simultaneously or separately; the basic feature of the combined hybrid electric vehicle is that it has both series and parallel driving modes. The fuel cell vehicle is a vehicle that uses fuel cells as the power source.

1.3 New Energy Vehicle Powertrain Technology Characteristics The electric drive transmission technology is a technology in which the electric motor converts the electric energy into mechanical energy and drives the vehicle with the participation of the transmission mechanism. The powertrain system is composed of a motor, a drive mechanism, a control device and a battery. Due to the change of power source, in order to better improve the work and energy-saving efficiency of new energy vehicles, the powertrain has been correspondingly changed to a certain extent on the basis of the traditional automobile powertrain and even changed thoroughly. In addition to the traditional transmission, there are many new drive modes, such as reducer drive, differential drive, motor coupling drive and direct motor drive, which are adapted to the multi-power sources of new energy vehicles.

1.3 New Energy Vehicle Powertrain Technology Characteristics

19

1.3.1 New Energy Powertrain Requirements The drive motor has high efficiency and the single gear reducer can adapt to some models. The high efficiency area efficiency of the drive motor can reach more than 95%, and its low efficiency area efficiency can also reach 70%. Therefore, the efficiency change of the drive motor in its efficiency field is not as obvious as that of the engine, and the proportion of its high efficiency area is much larger than that of the engine; some types of battery electric vehicles can basically meet the dynamic requirements through reasonable design of the motor characteristic curve and equipment with a reducer with a certain speed ratio, in the case of acceleration, climbing, noise and low maximum speed requirements. The multi-speed transmission will enable the drive motor to work in the high efficiency area, taking into account the power and cost performance. The addition of transmission can reduce the working time of the motor in the weak magnetic control area, and make it quickly enter the high efficiency area when the vehicle starts to accelerate, so as to make the motor work in the high efficiency area most of the time, improve the efficiency of the vehicle system, reduce the working current of the drive motor at low speed and large torque, prolong the life of the motor and the control unit, and reduce the cost of the motor and the control unit. In particular, it can also reduce the volume, weight and cost of the drive motor significantly, and improve the overall carrying capacity of the vehicle. The electric vehicle transmission is characterized as follows: (1) Relatively few gears. In order to improve the power performance and fuel economy of the engine, the traditional automobile transmission has 6–9 gears. However, due to good speed regulation characteristics of the motor, the electric vehicle transmission generally has no more than 3 transmissions; otherwise the structure will become complicated, and the transmission efficiency will be reduced. (2) High NVH performance requirements. The electric vehicles require more demanding transmission noise than conventional ones because the motor runs much quieter than the engine. (3) High fatigue life requirement for each gear. Due to the small number of gears and large range of high load (more than 60%), the fatigue life of transmission gears and bearings of the electric vehicles is higher than that of the traditional transmissions. (4) Clutchless intelligent shift technology. Cancel the clutch and realize intelligent shift through the motor speed regulation function.

20

1 Overview

1.3.2 Development Trend of NEV Drive Technology 1. Multi-speed The multi-speed automatic transmission can improve the NEV power performance, extend the NEV driving range, optimize the NEV electric drive system assembly performance; reduce the total weight and cost of NEV; reduce the maximum speed requirements of motor and transmission, reduce the production and processing costs and improve the gradeability. The single reduction gear is difficult to meet consumers’ continuously increasing requirements for driving performance and power performance of new energy vehicles, so it is a trend that a considerable proportion of battery electric vehicles adopt multi-speed automatic transmissions. However, due to the fast response of the motor and its good performance in low speed and heavy load as well as high speed and light load, in general, the multi-speed automatic transmission of battery electric vehicles can have up to three forward gears to well meet the needs for power and gradeability and can further reduce the weight and cost of the electric drive system provided that it achieves the same performance requirements on the whole. 2. High speed By increasing the working speed of the motor, reducing the volume and weight of the motor and adopting appropriate transmission system and control strategy, the allowable range of the regenerative braking can be broadened to adapt to more working conditions, so that the vehicle is more energy-saving and the driving mileage can be extended. The increase in the power density of the drive motor of electric vehicles will inevitably increase the maximum speed of the drive motor. For example, the maximum motor speed of Tesla Motors in the United States reaches 15,800 r/min, while of NIO Automobile in China reaches 15,000 r/min. Then the matching reducer/transmission products also need to meet the maximum speed requirements. In particular, more demanding performance and reliability requirements are proposed for bearings, oil seals and gears. The maximum motor speed of the battery electric passenger vehicle prototypes trial-produced by European AVL has reached 30,000 r/min. With the development of high-speed drive motor, the high-speed drive system of the electric vehicle motor will also become an inevitable trend. 3. Modularization and integration of electric powertrain Integration is to integrate the transmission, motor and motor control unit To make the vehicle more compact in structure and more optimal and reliable in performance to easily control and reduce the cost, the vehicle power and transmission system has developed from the discrete structure to the engine, motor and transmission modularization and integration, mainly including the hybrid powertrain (engine + motor + transmission + control unit) and the electromechanical coupled drive assembly (drive motor + generator + transmission + control unit). Modularization of the integrated design and comprehensive management control of the dynamically coupled system

Bibliography

21

and electromechanical coupled transmission system is the development direction of the motor and vehicle power and transmission system.

Bibliography Bridges H (2015) Hybrid vehicles and hybrid electric vehicles: new developments, energy management and emerging technologies. Nova Science Pub Inc., New York China Automotive Technology & Research Center (2017) Terminology of electric vehicles: GB/T19596-2017. China Standards Press, Beijing Crisostomi E, Shorten R, Stvdli S et al (2017) Electric and plugin hybrid vehicle networks: optimization and control. CRC, Boca Raton Editorial Department of China (2017) Review on China’s automotive engineering research progress 2017. China J Highway Transp 30(6):1–197 Emadi A (2014) Advanced electric drive vehicles (energy, power electronics, and machines). CRC, Boca Raton He R, Zhang K, Zhou Q et al (2020) White paper on the development trend of automobile “New three modernizations” (Part 2). China Inf World 23 Kurokawa Y, Imoto S, Yano T et al (2020) New energy vehicle market dynamics and technology development trends. Autom New Powertrain 3(3):21–27 Laoli N (2019) GAC new energy vehicle technology (III). Auto Maintenance 8:43–47 Ningzhong F (2020) Lightweight design and typical applications of new energy vehicle powertrain system. MW Metal Cutting (cold Working) 4:14–18 Ruimin L (2014) New energy vehicle technology. Electronic Industry Press, Beijing Shengmin C (2016) Analysis of new energy vehicle technology. Chemical Industry Press, Beijing Shuaiwei B, Longhai H, Xia W et al (2020) Research status and development trend of passive safety of new energy vehicles. China Southern Agric Mach 51(13):41 Shuyuan Z (2015) Current situation and development prospect of new energy vehicle industry. Guangdong Economic Press, Guangzhou Xiangyang X (2017) Development of transmission technology for energy-saving vehicles and new energy vehicles. J Autom Saf Energy 8(4):323–332 Yunfeng Z, Wushuang Y, Rongjie L et al (2020) Analysis on development trend of battery electric vehicles in China. Auto Engineer 7:14–17 Zhen W (2019) Discussion on powertrain transmission system technology of new energy vehicles and its application. Scien Technol Inno 31:192–193 Zhichao Z, Dewei Z (2016) New energy vehicle drive motor and control technology. Beijing Institute of Technology Press, Beijing

Chapter 2

Types and Control Technology of Drive Motors for New Energy Vehicles

2.1 Introduction The “Three-electricity” system (battery system, electric drive system and electric control system) is the most important component of a new energy vehicle. Compared with the battery system, which determines the driving distance of the new energy vehicle, the electric drive system composed of the drive motor and the mechanical drive system determines the driving distance of the vehicle, and its power and transmission performance also determines the power performance of the vehicle. In general, the electric drive system is mainly composed of four parts: drive motor, power inverter, powertrain system and control unit, as shown in Fig. 2.1. This chapter focuses on the drive motor as power source and its control technology. Compared with the industrial electric motor, the vehicle drive motor usually needs to meet the requirements of the electric vehicle such as frequent start-stop, instantaneous acceleration/deceleration, high speed range and high torque interval. The specific requirements can be divided into three categories: load demand, power performance and environmental impact. (1) Load demand. To meet the short-time acceleration and climbing property of the electric vehicles, the high torque output at low speed, constant power or low torque output at high speed or cruise mode are required. (2) Power performance. On the premise of priority to meeting the driving range of the electric vehicles, the motor and its control unit are required to have high energy conversion efficiency and transmission efficiency in all speed ranges and achieve energy recovery in the process of vehicle deceleration or braking; under complex operating conditions, the requirements for steady-state precision and controllability are relatively high. (3) Environmental impact. Meet the requirements of electric vehicle installation space; require high volume power ratio and mass power ratio are required; meet the stringent conditions of vehicle running, such as extreme high and © Huazhong University of Science and Technology Press and Springer Nature Singapore Pte Ltd. 2023 Y. Chen, New Energy Vehicle Powertrain Technologies and Applications, Key Technologies on New Energy Vehicles, https://doi.org/10.1007/978-981-19-9566-8_2

23

24

2 Types and Control Technology of Drive Motors for New Energy Vehicles

Other OBU

Power battery

High-voltage power distribution

High-voltage direct current P/N

Vehicle control unit VCU

Battery 13.5V

Control relay

Fuse

Fuse

Three-phase power line U/V/W Motor control unit

Motor Signal line (rotary transformer, temperature)

Coolant

Water pump

Radiator

Fig. 2.1 Frame diagram of electric drive system of new energy vehicle

low temperature environment, high pressure protection, strong earthquake environment, etc.; meet the market economy environment and strictly control the development and manufacturing costs of each component. Through a general survey of the current electric vehicle industry and market situation, the vehicle electric drive system is mainly developed towards integration, drive motor permanent magnetization and control system digitization. Figure 2.2 shows a typical electric drive control unit and power component of the new energy vehicles. At present, the improvement of battery power density has reached the “bottleneck”, and both the battery electric vehicles and hybrid electric vehicles are difficult

Fig. 2.2 Electric drive control unit and power component of new energy vehicles

2.1 Introduction

25

to get a qualitative improvement in a short period of time. Therefore, in order to meet the needs of long driving range, the major vehicle enterprises all adopt the means of stacking more power batteries, which puts forward strict requirements on the assembly space of the powertrain, so that the electric drive system is developed towards higher performance and smaller design size. Various vehicle enterprises and motor manufacturers have invested a large amount of resources in the research and development of small high-power motors. The methods adopted are nothing more than to improve the power density and torque density. The most effective method is to permanently magnetize the drive motor, that is, the use of rare earth magnetic materials will become an inevitable choice. The permanent magnet motor has advantaged resources in China’s development. China’s proved rare earth resources account for about 36% of the world, the export and reserves of rare earth are the world’s first. Moreover, China has listed the rare earth resources as important strategic resources and has restricted their export to foreign countries. In addition, the integration of the electric drive system has gone deep among various parts, which is not only reflected in the integration of the motor and the reducer (transmission) in battery electric vehicles, but also reflected in the integration of different coupling depths of the motor and the engine in hybrid electric vehicles. This enables the development of serialized and modular products for different vehicle platforms, and requires the integration of the motor control unit (DC/AC, MCU), engine control unit (ECU), transmission control unit (TCU) and vehicle control unit (VCU). Relatively mature domestic and foreign products mainly include Toyota THS hybrid system, Honda IMA drive system, Jing-Jin Electric Technologies pure electric drive system and NIO pure electric drive system. DC and AC motors are mainly adopted for the new energy vehicles. The DC motor was widely used in the early stage, but it has been replaced by AC motor because of its defects in the mechanical reversing design, size and maintenance. At present, the brushless AC motors are widely used in battery electric and hybrid electric vehicles, including induction motor, permanent magnet motor and other new motors (such as switched reluctance motor). As shown in Fig. 2.3, the induction motor is characterized by simple structure and good load capacity, as well as low manufacturing cost, easy braking energy recovery, strong environmental adaptability and high reliability. As shown in Fig. 2.4, the permanent magnet motor is designed based on the AC motor. The permanent magnet with high residual flux density is installed on the rotor, which greatly improves the power density of the motor. Under the same volume, the permanent magnet motor can output greater power and torque, and its energy conversion rate is usually between 90 and 95%. However, the disadvantages of permanent magnet motors are also prominent. A large amount of permanent magnets are required to manufacture a high-power motor, and the manufacture of permanent magnets is extremely dependent on the reserves of rare earth resources. Therefore, in general, the permanent magnet synchronous motor costs high, and the cost of the low-power permanent magnet motor is also increased in battery electric vehicles. In addition, under extreme working conditions, especially high temperature, high frequency vibration, high pressure, strong corrosion environment, the irreversible demagnetization is easily

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2 Types and Control Technology of Drive Motors for New Energy Vehicles

Fig. 2.3 Induction motor drive system

Fig. 2.4 Permanent magnet synchronous motor

to occur; the structural design and manufacturing process of surface-mounted and built-in permanent magnet synchronous motors are very complicated. Nevertheless, domestic and foreign automobile enterprises still prefer to use the permanent magnet synchronous motors, such as Toyota Prius, Tesla Model3, BMW i8, domestic NIO es6 performance edition and Xiaopeng G3. With the continuous development of modern power electronic components, motor structure design, motor control theory and digital control technology, the new motors represented by switched reluctance motor have gradually been concerned to by major vehicle enterprises. As shown in Fig. 2.5, the switched reluctance motor has the advantages of induction motor and permanent magnet motor. It combines the advantages of DC motor and AC motor speed regulation mode, optimizes and removes the winding and permanent magnet in the rotor, so that the torque to inertia ratio of the motor is increased; by improving the flux weakening control strategy, the motor has increased speed regulation range in constant power mode and has high fault tolerance. In addition, domestic and foreign researchers are trying to improve the noise and torque ripple of the switched reluctance motor in operation. In summary, this chapter will focus on the AC motor widely used in new energy vehicles and its control methods. It first focuses on the structure and basic characteristics of the AC induction motor, permanent magnet motor and switched reluctance

2.2 Structure, Principle and Characteristics of Drive Motors

27

Fig. 2.5 Switched reluctance motor

motor; then introduces then the principle and structure of the commonly used power electronic devices; finally analyze the control techniques for different motors and their principles.

2.2 Structure, Principle and Characteristics of Drive Motors 2.2.1 Induction Motor 2.2.1.1

Structure and Running Status of Three-Phase Induction Motor

1. Structure of three-phase induction motor The three-phase induction motor consists of three parts: stator, rotor and air gap. (1) Stator The stator is composed of the stator core, stator winding, engine base and end cover. The stator core is a part of the main magnetic circuit to reduce the eddy current and magnetic hysteresis loss caused by the rotating magnetic field in the core. The core is stacked by 0.5 mm thick silicon steel sheets coated with the insulating materials on both sides as the insulation between sheets. The stator core can be installed by external pressing or internal pressing. The former means that the stator core is stacked by the silicon steel sheets, pressed into a whole, and then installed into the engine base; the latter means that the fan-shaped punching sheets are spliced into layers of circles and misplaced and stacked in the engine base by layer. In the stator core, many slots of the same shape are uniformly punched to insert the stator winding. The stator winding is the circuit part of the stator used to input

28

2 Types and Control Technology of Drive Motors for New Energy Vehicles

electric energy from the power supply and generate a rotating magnetic field in the air gap. The small induction motor usually has a semi-enclosed slot and a single-layer winding made of high strength covered wires. The coil is insulated from the core by slot insulation. The semi-enclosed slot can reduce the reluctance of the main magnetic circuit and reduce the excitation current of the motor. In addition, the reduction of the slot opening can also reduce the pulse vibration of the air-gap field, so as to reduce the stray loss of the motor, but it is inconvenient to insert wires. The medium lowvoltage induction motor usually adopts the semi-open slot. The medium and large high-voltage induction motors all use open slots for easy wire embedding. In order to obtain better electromagnetic performance, medium and large induction motors all adopt double-layer short-pitch windings. Medium and small motors are mostly connected in triangle mode, while large high-voltage motors are connected in star mode. Both ends of the engine base are equipped with end covers, which can protect the end of the stator winding and be equipped with bearings to support the rotor. (2) Rotor The rotor is composed of the rotor core, rotor winding and spindle. The rotor core is also a part of the main magnetic circuit, usually stacked by 0.5 mm thick silicon steel sheets. The rotor core is fixed on the spindle or rotor field spider, and the appearance of the core is cylindrical. The electromagnetic torque and mechanical power generated by the rotor are output by the spindle. The rotor winding is the circuit part of the rotor, which is classified into cage type and winding type. The cage winding is a self-closed short circuit winding that consists of guide strips inserted into each rotor slot and the annular end rings at both ends. If the core is removed, the whole winding looks like a “cage”, so it is called a cage winding. In order to save copper and improve productivity, small motors generally use cast aluminum rotors; for medium and large motors, because the quality of the cast aluminum is not easy to guarantee, copper strips are inserted into the rotor slot, and then the end rings are welded at both ends. The cage induction motor is a kind of economical and durable motor with simple structure and convenient manufacture, so it is widely used. The slot of the wound rotor is embedded with a three-phase winding composed of insulated conductors, and the three outlet terminals of the winding are connected to the three collecting rings installed on the shaft, and then led out by the brush. The rotor features an applied resistor that can be inserted into the rotor winding to improve the starting and speed control performance of the motor. Compared with the cage rotor, the wound rotor is complex in structure and high in price and is usually used in the occasions requiring low starting current, high starting torque or speed regulation. (3) Air gap There is an air gap between the stator and rotor. The main air-gap field of the induction motor is generated by the excitation current. Since excitation current is basically reactive current, the larger the excitation current is, the lower the power factor of

2.2 Structure, Principle and Characteristics of Drive Motors

29

the motor will be. In order to reduce the excitation current and improve the power factor of the motor, a small air gap is usually selected for the induction motor, but attention shall be paid to not make the motor assembly difficult and operation unsafe. For medium and small motors, the air gap is generally 0.2–2 mm. 2. Running status of three-phase induction motor The three-phase induction motor generates a air-gap rotating magnetic field through the three-phase current flowing into the stator winding, and then induces electromotive force and current in the rotor winding using the principle of electromagnetic induction. The electromagnetic torque is generated by the interaction between the air-gap field and the rotor induced current, so as to realize the electrical and mechanical energy conversion. Under normal circumstances, the rotor speed of the induction motor is always slightly lower or slightly higher than the speed of the rotating magnetic field (synchronous speed), so the induction motor is also called asynchronous motor. The difference between the rotational speed ns of the rotating magnetic field and the rotor speed n is called slip, represented by Δn, Δn = ns − no. The ratio of the slip Δn to the synchronous speed ns is called slip ratio, represented by s, i.e. s=

ns − n ns

(2.1)

The slip ratio is a basic variable that characterizes the running status and performance of three-phase induction motor. It is not difficult to see that when the rotor speed n = 0, the slip rate s = 1; when the rotor speed is synchronous speed, the slip ratio s = 0. When the load of the three-phase induction motor changes, the rotor speed and slip ratio will change accordingly, so that the induced electromotive force and current in the rotor conductor and the electromagnetic torque acting on the rotor will change accordingly to meet the load demand. According to the positive, negative and size of the slip ratio, the three-phase induction motor can run as a motor, run as a generator or run by electromagnetic braking. (1) Motor running status When the rotor speed is lower than the speed of the rotating magnetic field (ns > n > 0), 0 < s < 1. If the air-gap rotating magnetic field (denoted by N and S) generated by the stator three-phase current rotates counterclockwise, assume that the magnetic field is stationary while the rotor conductor moves in the opposite direction. According to the right-hand rule, the direction of the induced electromotive force in the conductor when the rotor conductor cuts the air-gap field can be determined. Because the rotor winding is short-circuited, there is current flowing through the rotor conductor. The active component of the rotor induced current shall be in the same direction as the rotor induced electromotive force, that is, the current direction in the top conductor is inflow (represented by ⊗ ), while the current direction in the bottom conductor is outflow (represented by Θ). The active component of the rotor induced current interacts with the

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2 Types and Control Technology of Drive Motors for New Energy Vehicles

air-gap field, resulting in electromagnetic force and electromagnetic torque. According to the left-hand rule, the direction of the electromagnetic torque will be the same as the rotor steering, that is, the electromagnetic torque is the driving torque. At this time, the motor inputs electric power from the grid, and the rotor outputs the mechanical power through electromagnetic induction and the motor is running status. (2) Generator running status If the motor is driven by the prime mover and the rotor speed is higher than the rotating magnetic field speed (i.e., n > ns ), then the slip ratio s is less than 0. At this time, the direction of the rotor conductor cutting the air-gap field will be opposite to that in the motor running status, so the induced electromotive force in the rotor conductor and the active component of the rotor current will also be opposite to that in the motor running status, that is, the current direction in the top conductor is outflow, and the current direction in the bottom conductor is inflow; therefore, the direction of the electromagnetic torque will be opposite to the rotating magnetic field and rotor steering, and the electromagnetic torque will become the braking torque. In order to keep the rotor rotating at a speed higher than that of the rotating magnetic field, the drive torque of the prime mover must be able to overcome the electromagnetic torque of the braking. At this time, the rotor inputs mechanical power from the prime mover, the stator outputs the electric power through electromagnetic induction and the three-phase induction motor is in the generator running status. (3) Running status of electromagnetic brake If the rotor rotates reversely (n < 0) against the direction of the rotating magnetic field due to mechanical reasons or other external reasons, then the slip ratio s is greater than 1. At this time, the relative velocity direction of the rotor conductor cutting the air-gap field is the same as that in the motor running status, so the direction of the induced electromotive force and active component of the current in the rotor conductor is the same as that in the motor running status, and the direction of the electromagnetic torque is also the same as that in the motor running status; however, due to the change of rotor steering, the electromagnetic torque will appear as braking torque for the rotor. At this time, the three-phase induction motor is in the electromagnetic braking status, which not only inputs mechanical power from the shaft, but also inputs electrical power from the grid, both becoming the internal loss of the motor. 2.2.1.2

Operating Characteristics of Three-Phase Induction Motor

The relation curve among the motor speed n, electromagnetic torque T e , stator current I 1 , power factor cosϕ1 , efficiency μ and output power P2 in the rated voltage and rated power is called the operating characteristic of the induction motor. The speed of the induction motor is n = ns (1 − s). In no-load condition, P2 = 0, the slip ratio s = 0 and the rotor speed is very close to the synchronous speed ns . As the load increases, in order to make the electromagnetic torque sufficient to

2.2 Structure, Principle and Characteristics of Drive Motors

31

overcome the load torque, the rotor current will increase, and the slip ratio will also increase. Generally, the slip ratio sN is 2–5% in the rated load, that is, the rated speed is 2–5% lower than the synchronous speed. The stator current of the induction motor is I 1 = I m + (−I 2 ). The rotor current I 2 is around 0 at no load, and the stator current is almost the excitation current I m . As the load increases, the rotor current increases and then the stator current will increase. It can be seen from the equivalent circuit that the induction motor is an inductive circuit, so the power factor of the induction motor is always less than 1 and lagged. During no-load operation, the stator current is basically equal to the excitation current (its main component is the reactive magnetization current), so the power factor is very low, 0.1–0.2. With the load, the output mechanical power increases and the active component of the stator current will also increase, so the power factor of the motor will increase gradually; the power factor will reach its maximum value usually near the rated load. If the load continues to increase, due to the large slip ratio, the equivalent resistance R2 /s and the power factor cosϕ2 of the rotor decrease rapidly, so the stator power factor cosϕ1 decreases again. During steady-state operation, the electromagnetic torque T e is Te = T0 + T2

(2.2)

As the no-load torque T 0 can be considered unchanged, the speed of the motor changes very little from no-load to rated load, so T e = f (P2 ) is approximately a straight line. Similar to other motors, the maximum efficiency of the three-phase induction motor usually occurs in the power range of (0.8–1.1)PN . The rated efficiency μN ranges between 85 and 90%, and the larger the capacity, the higher the μN. Since the efficiency and power factor of the induction motor are usually at the maximum value near the rated load, the motor shall be selected to have the capacity match the load, so that the motor can be used economically, reasonably and safely.

2.2.1.3

Single-Phase Induction Motor

The single-phase induction motor is a kind of induction motor powered by singlephase power supply. It is easy to use, so it is widely used in household appliances (such as refrigerator, electric fan, air conditioning plant, washing machine, etc.) and medical devices. Compared with the three-phase induction motor with the same capacity, the single-phase induction motor has slightly larger volume and slightly worse operating performance, so it only has a small capacity of dozens to hundreds of watts. 1. Structural features The stator of a single-phase induction motor is usually installed with two windings internally: one is the main winding, which is used to generate the main magnetic field and the electromagnetic torque in normal operation, and input

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2 Types and Control Technology of Drive Motors for New Energy Vehicles

electric power from the power supply; the other is the starting winding, which is only connected at the start to generate the starting torque to start the motor. When the speed reaches 75% of the synchronous speed, the starting winding is disconnected from the power supply by the centrifugal switch or relay. The stator core of the single-phase induction motor is similar to that of an ordinary three-phase induction motor except that the shaded pole motor usually has a protruding pole. Because the stator has small inner diameter, it is difficult to insert wires and the stator mostly adopts single-layer winding. In order to weaken the space triple frequency harmonic in the stator magnetomotive force to improve the motor starting performance, the double-layer winding or sinusoidal winding is also used. In the capacitor-started single-phase induction motors, the main winding usually accounts for 2/3 of the total slots in the stator, and the starting winding accounts for 1/3. The rotor of the single-phase induction motor is cage rotor. 2. Working principle When the main winding of the stator of a single-phase induction motor is connected to the AC power supply, the main winding will generate a pulse magnetomotive force, which is decomposed into two forward and reverse rotating magnetomotive forces (Ff and Fb ) of equal magnitude, opposite direction and same speed. If the magnetic circuit is linear, the resultant magnetic field and the resultant electromagnetic torque in the motor can be obtained by superimposing the magnetic field produced by the forward and reverse rotating magnetomotive force and the forward and reverse electromagnetic torque produced by the corresponding induced current of the rotor. This is the double-rotating magnetic field theory. 3. Advantages and disadvantages of induction motor Compared with the synchronous motor and DC motor, the cage induction motor has the advantages of simple structure, reliable operation, convenient maintenance and low price, and the disadvantages of power factor constant lag, and very low power factor especially in the light-load operation. The speed control performance of the induction motor has always been a problem in the past. In recent years, due to the introduction of the vector control and direct torque control technology, the speed and torque control of the induction motor have been close to that of DC motor, so it is no longer a major disadvantage. The main analysis method of the single-phase induction motor is the doublerotating magnetic field theory, that is, to decompose the pulse magnetomotive force generated by the stator main winding into forward and reverse magnetomotive forces and magnetic fields, then calculate the rotor reaction generated by the two magnetic fields respectively, perform the frequency reduction and winding reduction on the forward and reverse circuits of the rotor by imitating the treatment method of the three-phase motor, finally obtain the equivalent circuit of the single-phase motor and calculate the required running data and Ts –s curve. The single-phase induction motor itself has no starting torque. In order to solve the starting problem, it is necessary to install the starting winding and take phase splitting measures, so that the main winding and the starting winding

2.2 Structure, Principle and Characteristics of Drive Motors

33

become a two-phase system. The main winding and the starting winding are generally asymmetrical, so the symmetrical component method of two phases or the analysis method of two-phase asymmetric asynchronous motor is usually used to calculate the starting and operating performance. For the wire wound three-phase induction motor, if its rotor winding becomes a single-phase winding due to disconnection of a phase, the electromagnetic torque of the motor will become the single shaft torque. At this time, if the motor is put into the grid to start, the rotor speed will be stagnant around n/2 and cannot reach the normal speed. To this end, it is necessary to eliminate the fault, and then put the motor into the grid and start again. The induction generator is a running status of the induction motor when s is less than 0, and its running data can also be calculated by T-shaped equivalent circuit. In separate operation, the reactive power required for the main and leakage magnetic fields of the induction generator shall be supplied by special capacitors. In addition, the terminal voltage of the generator and the frequency of the unit will change with the load. Therefore, it is necessary to adjust the speed of the generator and the capacitance of the shunt capacitor bank to keep the terminal voltage and the frequency of the unit unchanged. This is its characteristic.

2.2.2 Permanent Magnet Synchronous Motor 2.2.2.1

Structure of Permanent Magnet Synchronous Motor

1. Overall structure of permanent magnet synchronous motor The permanent magnet synchronous motor is also composed of stator, rotor and end cover. The stator is basically the same as that of the common induction motor, and is also of laminated structure to reduce the core loss of the motor during operation. The rotor core can be solid or laminated. Figure 2.6 is the cross section view of a permanent magnet synchronous motor. Stator coil Stator

Rotor Permanent magnet

Fig. 2.6 Cross section view of permanent magnet synchronous motor

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2 Types and Control Technology of Drive Motors for New Energy Vehicles

The armature windings may be in the form of concentrated integral pitch winding, distributed short-pitch winding or unconventional winding. In general, the rectangular wave permanent magnet synchronous motor usually uses the concentrated integral pitch winding, while the sinusoidal wave permanent magnet synchronous motor often uses the distributed short-pitch winding. In some permanent magnet synchronous motors controlled by the sinusoidal current, in order to reduce the spatial harmonics of the magnetomotive force generated by the windings and make it closer to the sinusoidal distribution to improve the performance of the motor, some unconventional windings are adopted, which can greatly reduce the torque ripple of the motor and improve the operation stability of the motor. In order to reduce the stray loss of the motor, the stator windings are usually connected in the star mode. The air gap length of the permanent magnet synchronous motor is a very critical dimension. Although it is not as sensitive to the reactive current of this kind of motor as that of the induction motor, it has a great influence on the quadrature and direct axis reactance of the motor, and then affects other performance of the motor. In addition, the air gap length also has a great influence on the assembly process and the stray loss of the motor. The main difference between the permanent magnet synchronous motor and other motors is the rotor magnetic circuit structure, which is analyzed and discussed in detail below. 2. Rotor magnetic circuit structure of permanent magnet synchronous motor If the rotor magnetic circuit structure is different, the motor operating performance, control system, manufacturing process and application are also different. In recent years, the external-rotor permanent magnet synchronous motor has been widely used in some fields. Its main advantage is that the rotational inertia is larger than that of the conventional permanent magnet synchronous motor, and the armature core diameter can be made larger, so as to improve the efficiency and output power of the motor under unstable load. The external-rotor permanent magnet synchronous motor is the same as the conventional permanent magnet synchronous motor except the structure. Depending on the position of the permanent magnet on the rotor, the rotor magnetic circuit structure of the permanent magnet synchronous motor can be generally classified into: surface type, built-in type and claw pole type. The following is a brief introduction of surface type and built-in rotor magnetic circuit structure. (1) Surface type rotor magnetic circuit structure In this structure, the permanent magnet is usually tile shaped and is located on the outer surface of the rotor core. The permanent magnet provides flux in the radial direction, and the outer surface of the permanent magnet and the inner circle of the stator core are usually only covered with a non-magnetic cylinder for protection, or the surface of the permanent magnet pole is covered with a weft less glass tape as a protective layer. The rotor in Fig. 2.6 is a typical representative of this structure. The permanent magnet poles of some speed regulating permanent magnet synchronous motors are assembled into tiles with many small rectangular strips to reduce the motor manufacturing cost.

2.2 Structure, Principle and Characteristics of Drive Motors

(a) Salient-mounted type

35

(b) Plug-in type

Fig. 2.7 Surface type rotor magnetic circuit structure

The surface type rotor magnetic circuit structure is classified into salient-mounted type (see Fig. 2.7a) and plug-in type (see Fig. 2.7b). For the motor made of rare earth permanent magnetic material, the surface-mounted rotor is of the non-salient pole rotor structure in terms of electromagnetic performance because the relative recoil permeability of the permanent magnet materials is close to 1; there is a ferromagnetic material with high permeability between two adjacent permanent magnet poles of the surface plug-in rotor, so it is of the salient pole rotor structure in terms of electromagnetic performance. (2) The built-in rotor magnetic circuit structure is shown in Fig. 2.8. The permanent magnet of this structure is located inside the rotor. Between the outer surface of the permanent magnet and the inner circle of the stator core is a pole shoe made of ferromagnetic material, in which a cast aluminum cage or copper bar cage with good dynamic and stable performance is placed to play a role of damping or starting. This magnetic circuit structure is widely used in permanent magnet synchronous motors with asynchronous starting capability or high dynamic performance requirements. The permanent magnet in the built-in rotor is protected by the pole shoe. The reluctance torque generated by the asymmetry of the magnetic circuit structure of the rotor is also helpful to improve the overload capacity and power density of the motor, and it is easy to increase the flux weakening speed. According to the mutual relation between the magnetization direction of the permanent magnet and the rotation direction of the rotor, the built-in rotor magnetic circuit structure can be classified into radial, tangential and hybrid types.

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2 Types and Control Technology of Drive Motors for New Energy Vehicles

Fig. 2.8 Built-in rotor magnetic circuit structure

Stator coil Stator

Rotor Permanent

2.2.2.2

Rotation Principle of Permanent Magnet Synchronous Motor

The starting and running of the permanent magnet synchronous motor is realized by the interaction between the magnetic fields generated by the stator winding, rotor cage winding and permanent magnet. When the motor is stationary, the stator winding is fed with three-phase symmetric current to generate a stator rotating magnetic field, which rotates relative to the rotor and generates current in the cage winding to form a rotor rotating magnetic field. The asynchronous torque generated by the interaction between the stator rotating magnetic field and the rotor rotating magnetic field makes the rotor accelerate from rest. In this process, the rotor permanent magnetic field and the stator rotating magnetic field have different speeds, which will produce an alternating torque. When the rotor accelerates to a speed close to the synchronous speed, the rotor permanent magnetic field has close speed as the stator rotating magnetic field, the speed of the stator rotating magnetic field is slightly greater than that of the rotor permanent magnetic field. The fields interact to produce torque to pull the rotor into the synchronous running status. In the synchronous operation, no current is generated in the rotor winding. At this time, only the permanent magnet on the rotor generates a magnetic field, which interacts with the stator rotating magnetic field to produce a drive torque. It can be seen that the permanent magnet synchronous motor is started by the asynchronous torque of the rotor winding. After starting, the rotor winding is no longer functional, and the drive torque is generated by the interaction between the magnetic fields generated by the permanent magnet and the stator winding.

2.2 Structure, Principle and Characteristics of Drive Motors

2.2.2.3

37

Driving Process of Permanent Magnet Synchronous Motor

1. Asynchronous starting The rotor of the asynchronous starting motor is equipped with a permanent magnet as well as a cage starting winding. The three-phase current input to the stator at the starting will generate a rotating magnetic field in the air gap that rotates at a synchronous speed. This rotating magnetic field will interact with the induced current in the cage winding to generate a driving asynchronous electromagnetic torque TM , similar to a common induction motor. When the rotor rotates, the permanent magnet will form another rotating magnetic field with speed of (1 − s)ns in the air gap and induce a set of electromotive force with the frequency of f = (1 − s)f 1 in the stator winding; this electromotive force will generate a set of three-phase current with the frequency of (1 − s)f 1 , which will interact with the magnetic field of the permanent magnet to generate a braking electromagnetic torque T G on the rotor, similar to the three-phase steady-state short circuit of the synchronous generator. The resultant electromagnetic torque T e at the starting is the sum of T M and T G . The motor will start under the action of the resultant torque T e . 2. Hysteresis starting The rotor of a hysteresis starting motor is composed of a permanent magnet and a hysteresis loop made of hysteresis material. When the stator winding is fed with three-phase alternating current to generate an air-gap rotating magnetic field and magnetize the hysteresis loop on the rotor, the rotor magnetic field will be distorted due to the hysteresis effect, so that the magnetic field in the loop lags behind the air-gap magnetic field by a hysteresis angle, and the rotor will be subject to a driving hysteresis torque T h . The size of T h is related to the hysteresis loop area of the material used, but unrelated to the rotor speed. When the supply voltage and frequency are unchanged, T h is a constant value. Under the action of the hysteresis torque Th , the rotor will turn and be pulled into synchronization.

2.2.2.4

Advantages and Disadvantages of Permanent Magnet Synchronous Motor

The traction motor with high density, high efficiency and wide speed regulation as well as its control system is not only the heart of electric vehicles but also one of the key technologies of electric vehicle development. Before the 1980s, almost all traction motors of vehicles were DC motors, because of large starting acceleration traction and simple control system of the DC traction motors. The disadvantage of DC motor is that there is a mechanical commutator, on which the sparks will be produced when running at high speed and large load. Therefore, the running speed of the motor cannot be too high. Because the commutator of the DC motor needs maintenance, and is not suitable for high-speed operation, it is now generally not used except in small cars.

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2 Types and Control Technology of Drive Motors for New Energy Vehicles

Compared with the original DC traction motor system, the permanent magnet motor has obvious advantages such as small size, light weight (its specific mass is 0.5–1.0 kg/kW), high efficiency, basic maintenance free, wide speed regulation range, high power density, small rotational inertia of rotor, small armature inductance, high operating efficiency and no slip ring and brush on the shaft, etc., so it has been widely used in electric vehicles. The permanent magnet motor adopts the permanent magnet materials instead of the traditional motor exciting winding (or rotor winding). The permanent magnet motor is classified into permanent magnet AC synchronous motor and permanent magnet DC motor. If the DC exciting winding of a DC motor is replaced by a permanent magnet, the motor is called a permanent magnet DC motor. In order to overcome the disadvantage of constant flux of the permanent magnet motor, an electromagnetic winding that excites a magnetic field is embedded in the permanent magnet stator of the motor, called permanent magnet compound motor, which is characterized by both permanent magnet and excitation winding. The permanent magnet DC motor is classified into permanent magnet brush DC motor and permanent magnet brushless DC motor. The permanent magnet brush DC motor is widely used in small electrical appliances. With the brush and commutator, the permanent magnet brush DC motor is more complex than the permanent magnet brushless DC motor in maintenance and manufacturing; the sparking on commutator and mechanical noise in the application also make the permanent magnet brush DC motor difficult to use in the harsh environment. Since the permanent magnet brushless DC motor has no brush, which makes up for the defects of the permanent magnet brush DC motor and traditional DC motor, it is more and more used in the servo systems, CNC machine tools, variable frequency air conditioners and electric vehicles.

2.2.3 Switched Reluctance Motor The switched reluctance motor (SRM) is a typical electromechanical motor, also known as switched reluctance motor drive (SRD) system. It is mainly composed of the switched reluctance motor body, power electronic power converter, rotor-position sensor and control unit. The switched reluctance motor has the advantages of simple structure, small rotational inertia of rotor, low cost and fast dynamic response. With the capacity designed to several watts to several megawatts, and a wide speed regulation range, it can run at low speeds or at high speeds (up to 15,000 r/min). In addition, the switched reluctance motor is superior to the induction motor and synchronous motor in terms of operating efficiency and reliability, and can run under poor heat dissipation conditions and chemical pollution. Figure 2.9 shows the basic control block diagram of the switched reluctance motor.

2.2 Structure, Principle and Characteristics of Drive Motors Power electronic power converter

39 Switched reluctance motor body

Control unit Command input Rotor-position sensor

Fig. 2.9 Basic control block diagram of switched reluctance motor

2.2.3.1

Structural Features of Switched Reluctance Motor

1. Structure of switched reluctance motor body The switched reluctance motor body is of the stator and rotor double salient structure with unilateral excitation. That is, only the stator salient pole adopts centralized winding excitation, while the rotor salient pole has neither winding nor permanent magnet. The stator and rotor are laminated by silicon steel sheets, and the poles of the stator winding with opposite radial direction are connected in series to form a phase. Figure 2.10 shows the structure principle of a three-phase 8/6 pole switched reluctance motor. Figure 2.11 shows the stator and rotor of a switched reluctance motor. The stator and rotor of the switched reluctance motor have different phase numbers and can be combined in various ways. The most common ones are three-phase 6/4 salient pole structure, three-phase 8/6 salient pole structure, and three-phase 12/8 salient pole structure, as shown in Fig. 2.12. The three-phase 6/4 salient pole structure indicates that the motor stator has 6 salient poles and the rotor has 4 salient poles. The concentrated windings on the two symmetrical salient poles of the stator are connected in series with each other to form a phase and the number of phases is half of the number of salient poles of the stator. The switched reluctance motor without winding on the rotor and with 6 salient poles on the stator is called three-phase switched reluctance motor, while the switched reluctance motor without winding on the rotor and with 8 salient poles on the stator is called four-phase switched reluctance motor. The more phase number, the smaller step angle, the more stable operation, the more conducive to reducing the torque ripple, but the more complex control, which will lead to the increase of main switching devices and cost. Step angle calculation method: Step angle α = 360° * 2/(number of

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2 Types and Control Technology of Drive Motors for New Energy Vehicles

Fig. 2.10 Structure principle of three-phase 8/6 pole switched reluctance motor

Fig. 2.11 Stator and rotor of switched reluctance motor

(a) Three-phase 6/4 salient pole

(b) Three-phase 8/6 salient pole

Fig. 2.12 Several combinations of switched reluctance motor

(c) Three-phase 12/8 salient pole

2.2 Structure, Principle and Characteristics of Drive Motors

41

stator poles × number of rotor poles). Example: For the four-phase 8/6 pole motor, the step angle α = 360° * 2/(8 × 6) = 15°. The switched reluctance motor with fewer than three phases generally has no self-starting capability, and three-, fourand five-phase structures are more widely used at present. Figure 2.13 shows the schematic sections of the stator and rotor of the switched reluctance motors of three-phase 6/4 salient pole, three-phase 12/8 salient pole (double winding) and four-phase 8/6 salient pole structures. 2. Rotor-position sensor The rotor-position sensor has Hall type, electromagnetic type, photoelectric type and magnetic-sensing type, and is often located at the non-output end of the motor, as shown in Fig. 2.14. The photoelectric position detector is composed of a disk and a photoelectric sensor. The disk, with the same section as the rotor, is mounted on the rotor. The photoelectric sensor is mounted on the stator. When the disk rotates with the rotor, the photoelectric sensor detects the position signal of the rotor teeth.

(a) Three-phase 6/4 salient pole

(b) Three-phase 12/8 salient pole

(c) Three-phase 8/6 salient pole

Fig. 2.13 Schematic sections of the stator and rotor of several switched reluctance motors

Sensor Disk

Fig. 2.14 Position of sensor in switched reluctance motor

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2 Types and Control Technology of Drive Motors for New Energy Vehicles

(a) Structure of position detector

(b) Basic signal of rotor position

Fig. 2.15 Rotor position detection principle

Figure 2.15 shows the rotor position detection principle. Figure 2.15a shows the position detector of a four-phase 8/6 pole motor. Only two sensors, SP and SQ , are set and differ by 15° in space. There are six magnetic slots 30° apart on the disk. The basic signal detected is shown in Fig. 2.15b. The introduction of the position sensor increases the complexity of the switched reluctance motor structure and affects its reliability. Therefore, people are focusing on sensorless solutions to obtain the rotor position information by detecting the phase inductance. This has been recognized as a very meaningful research direction.

2.2.3.2

Rotation Principle of Switched Reluctance Motor

As can be seen from Fig. 2.10, when the current-controlled switches K1 and K2 of phase A winding are closed, phase A is connected to the electric excitation, and the generated magnetic field force makes the rotor rotate to the position where the rotor pole axis aa' coincides with the stator pole axis AA' , thus generating the electromagnetic torque with the reluctance nature. If phases A, B, C and D windings are energized sequentially, the rotor will rotate continuously in the counterclockwise direction; if phases B, A, D and C windings are energized sequentially, the rotor will rotate clockwise. In the actual operation of a polyphase motor, two or more phases of windings are often on at the same time. When the stator windings in a phase are energized once in turn, the rotor will rotate by one rotor pole pitch.

2.2 Structure, Principle and Characteristics of Drive Motors

2.2.3.3

43

System Characteristics of Switched Reluctance Motor

The reason why the speed control system of the switched reluctance motor can rise suddenly in modern speed control systems is mainly because of its excellent system performance, as follows. (1) Simple structure. With simple structure and low cost, the motor can be used for high-speed operation. The structure of the SRD is simpler than that of the squirrel-cage induction motor. Its outstanding advantage is that there is no winding of any form on the rotor, so there will be no poor casting in the manufacturing process and broken bar in the use process of the squirrel-cage induction motor. With extremely high mechanical strength of rotor, the motor can be used for ultra-high speed operation (such as tens of thousands of revolutions per minute). On the stator side, it has only a few concentrated windings, so it is easy to manufacture and the insulation structure is simple. (2) Simple and reliable power circuit. The direction of the motor torque is unrelated to the direction of winding current, that is, only single-direction winding current is needed, so a power switch is feasible for each phase of the power circuit. Compared with the asynchronous motor winding, which requires the bidirectional current flowing through and requires two power devices per phase of the power circuit of the PWM converter, the speed control system of the switched reluctance motor requires fewer power components and has simpler circuit structure. In addition, the two power switch tubes of each bridge arm in the power circuit of the PWM converter are directly bridged on the DC power supply side, which is prone to direct short circuit and burn power devices. In the speed control system of the switched reluctance motor, each power switch device is directly connected with the motor windings in series, which fundamentally avoids the phenomenon of direct short circuit. Therefore, the protection circuit of the power circuit in the speed control system of the switched reluctance motor can be simplified to reduce the cost and achieve high working reliability. (3) High system reliability. In terms of the electromagnetic structure of the motor, each phase of winding and the magnetic circuit are independent of each other, and each produces electromagnetic torque within a certain axis angle range, unlike in general motors, where the motor can operate normally only when each phase of winding and the magnetic circuit generate a rotating magnetic field under the joint action. In terms of the control structure, each phase of circuit supplies power to one phase of winding, and generally works independently of each other. It can be seen that when one phase of winding of the motor or one phase of circuit of the control unit fails, only the phase needs to stop working, and it has no other impact on the motor except for the reduction of the total output power. (4) Large starting torque and low starting current. It is a major feature of this system that the control unit absorbs less current from the power side and obtains larger starting torque from the motor side. The data of typical products are: when the starting current is 15% of the rated current, the starting torque is 100% of the

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2 Types and Control Technology of Drive Motors for New Energy Vehicles

rated torque; when the starting current is 30% of the rated current, the starting torque can reach 250% of the rated torque. Compared with this motor, the other speed control systems have poor starting characteristics. For example, the DC motor needs 100% current, and the squirrel-cage induction motor needs 300% current to obtain 100% torque. The advantages of low starting current and large torque can also be extended to the low-speed operation section, so this system is very suitable for the machinery that needs heavy duty start and long-time low speed and heavy duty operation. (5) Suitable for frequent start and stop and forward and reverse conversion operations. With high starting torque and low starting current, the system has small current impact during starting and the motor and control unit have less heating value than in the continuous rated operation. Many controllable parameters enable the braking operation to have the same excellent torque output capacity and operating characteristics as the electric operation. The result of the combined action of the two inevitably makes it suitable for frequent start-stop and forward and reverse conversion operations up to 1000 times/h. (6) Many controllable parameters and good speed control performance. There are at least four main operating parameters and common methods to control the switched reluctance motor: phase conduction angle, phase turn-off angle, phase current amplitude and phase winding voltage. Many controllable parameters mean flexible and convenient control. Different control methods and parameters can be adopted according to the operation requirements and the condition of the motor, so that the motor can run in the best status (such as maximum output, highest efficiency, etc.) and can achieve a variety of different functions of specific curves, such as exactly the same four-quadrant operating capability, and the highest starting torque and the load capacity curve of the series motor. Because SRD speed closed loop is required, the system has high speed stabilization accuracy and can be easily constructed as an astatic speed control system. (7) High efficiency and low loss. This system is a very efficient speed control system because: on the one hand, there is no copper loss in the motor windings; on the other hand, the motor has many controllable parameters and is flexible and convenient. It is easy to realize efficient optimization control under wide speed range and different loads. Taking a 3 kW SRD as an example, its system efficiency is 87% or more in a wide range, which is not easy to be achieved by some other speed control systems. Compared with the system of the squirrel-cage asynchronous motor using PWM converter, this system has generally 5–10% higher efficiency at different speeds and different loads. 2.2.3.4

Advantages and Disadvantages of Switched Reluctance Motor

The drive system of the switched reluctance motor combines the advantages of the induction motor drive system and DC motor drive system, and is a strong competitor of these drive systems. Its main advantages are as follows:

2.2 Structure, Principle and Characteristics of Drive Motors

45

(1) The switched reluctance motor has a large motor utilization factor, which can reach 1.2–1.4 times of the induction motor utilization factor. (2) The motor has simple structure without any winding on the rotor, and with only simple concentrated windings on the stator, short end and no interphase jumper. Therefore, it has the characteristics of less manufacturing process, low cost, reliable work and small maintenance. (3) The torque of the switched reluctance motor is unrelated to the current polarity, and only requires unidirectional current excitation. In the power conversion circuit, each phase can use only one switching element that is connected in series with the motor windings, so there is no danger of direct connection of two switching elements like the power supply of the PWM converter. Therefore, the switched reluctance motor has simple drive system wiring, high reliability and lower cost than the PWM AC speed control system. (4) The structure of the rotor of the switched reluctance motor has little restriction on the speed, so the motor can be made into a high-speed motor. Moreover, the rotational inertia of the rotor is small, and the size and direction of the phase turn torque can be changed at any time when the current phase is changed each time, so the system has a good dynamic response. (5) The SRD system can obtain mechanical characteristics that meet different load requirements through current conduction, disconnection and amplitude control. It is easy to realize soft start and four-quadrant operation of the system is controlled flexibly. Because SRD system is a self-synchronous system, it will not have instability and oscillation problems at low frequencies like the induction motor powered by frequency conversion. (6) The switched reluctance motor adopts unique structure, design method and corresponding control skills, and its unit processing can be comparable, or even slightly superior, to the induction motor. The efficiency and power density of the SRD system can be maintained at high levels over a wide range of speeds and loads. The main disadvantages of the SRD system are as follows: (1) Torque ripple. It can be seen from the working principle that the torque generated on the rotor of the switched reluctance motor is superposition of a series of pulse torques. Due to the influence of the double salient pole structure and magnetic circuit saturation nonlinearity, the resultant torque is not a constant torque, but has a certain harmonic component, which affects the low-speed operation performance of the switched reluctance motor. (2) The drive system of the switched reluctance motor has larger noise and vibration than the general motor. (3) The switched reluctance motor has many outgoing line ends. For example, the three-phase switched reluctance motor has at least four outgoing line ends, while the four-phase switched reluctance motor has at least five outgoing line ends, with a position detector outgoing line end.

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2.2.4 Wheel Hub Motor The wheeled motor drive used in the electric vehicles belongs to the distributed motor drive mode. The distributed motor drive mode is usually divided into wheel hub motor drive and wheel-side motor drive. The wheel-side motor drive mode means that each driving wheel is driven by a separate motor, but the motor is not integrated in the wheel, but connected to the wheel through a transmission (e.g. transmission shaft). The drive motor of the wheel-side motor drive mode belongs to the sprung mass range, and the suspension system has good vibration isolation performance. However, the motor mounted on the vehicle body has a great impact on the overall layout of the vehicle, especially in the case of rear axle drive. Moreover, due to the deformation movement between the body and the wheel, the motor also has a certain limit on the cardan transmission of the transmission shaft.

2.2.4.1

Structural Form of Wheel Hub Motor

The wheel hub motor power system is usually composed of motor, reducing gear, brake and heat dissipation system. Figure 2.16 shows the wheel hub motor structure of an electric motorcycle. The wheel hub motor power system is mainly classified into inner rotor type and outer rotor type according to the rotor type of the motor, as shown in Fig. 2.17. Usually, the outer rotor type uses a low-speed outer rotor motor, with the maximum speed of 1000–1500 r/min, without any reducing gear. The outer rotor of the motor and the wheel rim are fixed or integrated together and the wheel speed is the same as the motor. The inner rotor type uses a high-speed inner rotor motor and is equipped with a reducer with a fixed transmission ratio. In order to obtain a higher power density, the speed of the motor is usually as high as 10,000 r/min, an epicyclic reduction gear unit with a transmission ratio of about 10:1 is usually used in the reducing gear, and the wheel speed is about 1000 r/min. The advantages of the high-speed inner rotor wheel hub motor are high specific power, light weight, small volume, high efficiency, low noise and low cost, while

Fig. 2.16 Wheel hub motor structure of electric motorcycle

2.2 Structure, Principle and Characteristics of Drive Motors

47

Fig. 2.17 Structural diagram of structure of wheel hub motor power system. 1—Tyre; 2—Spoke; 3—Wheel; 4—Bearing; 5—Epicyclic gear; 6—Encoder; 7—Brake drum; 8—Motor winding; 9—Permanent magnet

(a) Inner rotor type

(b) Outer rotor type

the disadvantages are the need for a reducing gear, reduced efficiency, increased unsprung mass, and limitations on the maximum speed of the motor by coil loss, friction loss and the bearing capacity of the shift gear. The advantages of the lowspeed outer rotor wheel hub motor are simple structure, small axial size, high specific power, ability to control the torque in a wide speed range, fast response speed, direct connection of the outer rotor with the wheel without reducing gear, and high efficiency, while the disadvantages are the need for increase in the motor volume and mass to obtain a large torque, resulting in high cost, low efficiency and large noise during acceleration. Both structures are used in current electric vehicles, but with the advent of compact planetary gear train, the high-speed inner rotor drive system has become more competitive in power density than the low-speed outer rotor drive system. The wheel hub motor power system cannot meet the requirements of the vehicle braking efficiency due to the small electric braking capacity of the motor, so it usually needs to attach a mechanical braking system. The brake in the wheel hub motor power system can be a drum or disc brake according to the structure. The existence of the electric braking capacity of the motor can often reduce the design capacity of the brake properly. Most of the wheel hub motor power systems is cooled by air, and some are cooled by water and oil for the heating parts of the motor and brake, but the structure is more complex.

2.2.4.2

Classification and Characteristics of Wheel Hub Motor

The wheel hub motor can be classified into permanent magnet type, induction type, switched reluctance type and other types according to the working principle. The drive motor of the wheel hub motor system can be classified into radial field motor and axial field motor according to the type of motor field.

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2 Types and Control Technology of Drive Motors for New Energy Vehicles

(1) The axial field motor has a structure conducive to heat dissipation and its stator does not require an iron core. (2) The stress between the stator and rotor of the radial field motor is relatively balanced, and the magnetic circuit is laminated by silicon steel sheets, which is more simple. The characteristics of the wheel hub motor are as follows: (1) The advantages of the induction (asynchronous) motor are simple structure, ruggedness, low cost, reliable operation, small torque ripple, low noise, no need for position sensor, and high speed limit; the disadvantages are complex drive circuit, and compared with the permanent magnet motor, low efficiency and power density. (2) The brushless permanent magnet synchronous motor can be of cylindrical radial field structure or disk axial field structure. With high power density and efficiency and wide speed range, the motor has very broad development prospect and has been used in a variety of electric vehicles at home and abroad. (3) The advantages of the switched reluctance motor are simple structure, low manufacturing cost, good speed/torque characteristics, etc., which is suitable for electric vehicle driving; the disadvantages are difficult design and control and large running noise. The structure of the integrated wheel hub motor designed and manufactured by French TM4 is shown in Fig. 2.18. It adopts an outer rotor type permanent magnet motor. The rotor housing of the motor is directly connected with the rim as an integral part of the wheel rim, and motor rotor is integrated with the brake drum of the drum brake, realizing the integration of three rotatory motion objects, i.e. motor rotor, rim and brake and greatly reducing the mass of the integrated wheel hub motor system. The integration degree is quite high. The permanent magnet brushless DC motor of the integrated wheel hub motor system has the rated power of 18.5 kW, the rated speed of 950 r/min, the highest speed of 1385 r/min, and the average efficiency under rated conditions up to 96.3%.

2.2.4.3

Characteristics of Electric Vehicles Using Wheel Hub Motor Drive System

1. Advantages of distributed motor drive mode The advantages of the distributed motor drive mode are as follows: (1) The electronic differential control technology is used to realize the different rotation speed movement of the inner and outer wheels when turning, and achieve higher precision. (2) The mechanical differential gear is canceled to reduce the mass of the power system, improve the transmission efficiency and reduce the transmission noise.

2.2 Structure, Principle and Characteristics of Drive Motors

49

Fig. 2.18 Structure diagram of TM4 integrated wheel hub motor. 1—Tyre; 2—Rim; 3—Permanent magnet; 4—Motor rotor; 5—Bearing; 6—Motor control unit; 7—Motor stator; 8—Motor winding; 9—Brake shoe; 10-Suspension; 11—Wiring harness

(3) It is helpful to optimize the overall layout of the vehicle and the matching optimization of the vehicle dynamic performance. (4) It can reduce the requirements for the motor performance index and has the characteristics of high reliability. 2. Disadvantages of distributed motor drive mode The disadvantages of the distributed motor drive mode are as follows: (1) In order to coordinate the motion of each wheel, high requirements are presented for the synchronous and coordinated control of multiple motors. (2) Some technical problems, such as structural arrangement, thermal management, electromagnetic compatibility and vibration control, are presented for the decentralized installation of motors. 3. Advantages of wheel hub motor drive mode The advantages of the wheel hub motor drive mode are as follows: (1) The transmission can be completely omitted, and the overall power utilization efficiency is greatly improved. (2) The wheel hub motor makes the overall arrangement of the vehicle in the form of flat chassis structure, and the interior space and layout freedom greatly improved. (3) There are almost no high-power moving parts in the body, and the vibration, noise and comfort of the whole vehicle are greatly improved. (4) It is convenient to realize four-wheel drive, which is beneficial to greatly improve the dynamic performance of the whole vehicle.

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2 Types and Control Technology of Drive Motors for New Energy Vehicles

(5) As the actuator, the wheel hub motor has the advantages of fast response speed and accuracy, which is convenient to realize the integrated control of vehicle dynamics, including drive-by-wire control and drive-by-wire vehicle dynamics control, and improve the active safety of the vehicle. The deep integration of the wheel hub motor with braking, steering and suspension system, and the torque vector distribution based on road condition awareness are one of the most critical technologies for the wheel hub motor drive.

2.3 Power Electronics and Inverter 2.3.1 Introduction to Power Electronic Power Devices The power electronic device, also known as power semiconductor device, is mainly used as high-power electronic device for electrical energy conversion and control circuits of power equipment (usually a device with the current of tens to thousands of amps, and the voltage of more than hundreds of volts). Power devices are used in almost all electronic manufacturing industries, including: laptops, PCs, servers, monitors and various peripherals in the computer field; mobile phones, telephones and other terminals and office equipment in the field of network communication; traditional black and white home appliances and various digital products in the field of consumer electronics; industrial PCs, all kinds of instrumentation and all kinds of control equipment in the industrial control field. In addition to ensuring the normal operation of such equipment, power devices can also play an effective role in energy saving. China’s power device market has been growing rapidly due to the increasing demand for electronic products and energy efficiency. In the 1950s, the power electronic devices were mainly mercury-arc thyratron and high-power tube. The thyristors developed in the 1960s were widely used in power electronic circuits because of its reliable work, long life, small size, fast switching speed and other advantages. In the early 1970s, the thyristors gradually replaced the mercury-arc thyratron. In the 1980s, ordinary thyristors had reached thousands of amps of switching current, and could withstand thousands of volts of positive and reverse operating voltages. On this basis, in order to adapt to the needs of the development of power electronic technology, a series of derived devices such as GTO, bidirectional thyristor, optically controlled thyristor and reverse conducting thyristor, as well as new power electronic devices such as unipolar MOSFET, bipolar power transistor, static induced thyristor, functional composite module and power integrated circuits, have been developed. All kinds of power electronic devices have two operating characteristics: conduction and blocking. The power diode is a two-terminal (cathode and anode) device, whose current is determined by the volt-ampere characteristics. Except for changing

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51

the voltage applied between the two terminals, the anode current cannot be controlled, so the power diode is called an uncontrollable device. The ordinary thyristor is a three-terminal device which be controlled for its conduction but not controlled for its turn-off by its gate signal and is called semi-controlled device. The turn-off thyristor, the power transistor and other devices can be controlled for their conduction and turn-off by their gate signals and called fully-controlled devices. The latter two types of devices, with flexible control, simple circuit and fast switching speed, are widely used in the rectifier, inverter and chopper circuits and are the core components in the power electronic equipment such as motor speed control, generator excitation, induction heating, electroplating, electrolysis power and direct power transmission. The equipment composed of these devices is not only small in size, reliable in work, but also very obvious in energy saving (generally 10–40%). A single power electronic device can withstand a certain amount of forward and reverse voltage, and can pass a certain amount of current. As a result, the capacity of the power electronic equipment composed of a single power electronic device is limited. Therefore, when multiple power electronic devices are connected in series or in parallel to form components in practical applications, their ability to withstand voltage and pass current can be multiplied, so as to greatly increase the capacity of the power electronic equipment. The devices are expected to bear the same forward and reverse voltages when connected in series and share the same current when connected in parallel. However, due to the individual differences of the devices, the devices cannot share the voltage and current completely evenly when connected in series and parallel. Therefore, the voltage equalization measures should be taken when the power electronic devices are connected in series, while the current equalization measures should be taken when they are connected in parallel. The power electronic devices may heat up due to power loss during working. Excess temperature will shorten the device life, or even burn out the devices, which is the main reason to limit the current and voltage capacity of power electronic devices. Therefore, the cooling of the devices must be considered. Commonly used cooling methods are self-cooling, air cooling, liquid cooling (including oil cooling and water cooling) and evaporative cooling, etc. Facts show that whether the power, machinery, mining and metallurgy, transportation, petroleum, energy, chemical, textile and other traditional industries, or communications, laser, robotics, environmental protection, atomic energy, aerospace and other high-tech industries, are in urgent need of high-quality and high-efficiency electric energy. The power electronics is an important means to efficiently convert all kinds of primary energy into the electric energy needed by people to realize energy conservation and environmental protection and improve the quality of people’s lives. It has become an indispensable bridge between weak current control and strong current operation, between information technology and advanced manufacturing technology, between the automatic and intelligent transformation of traditional industries and the construction of high-tech industries. The emergence of new power electronic devices is always accompanied by a revolution in the power electronic

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technology. The power electronic device is like the heart of modern power electronic equipment. It plays an important role in the total value, size, weight, dynamic performance, overload capacity, durability and reliability of the equipment.

2.3.1.1

Classification of Devices

By the extent to which the power electronic device can be controlled by the signal from a control circuit: (1) Semi-controlled devices, such as thyristor; (2) Fully-controlled devices, such as gate turn-off thyristor (GTO), giant transistor (GTR), Power MOSFET and insulated gate bipolar transistor (IGBT); (3) Uncontrolled devices, such as power diode. By the nature of the signal applied by a drive circuit between the control and common terminals of the power electronic device: (1) Voltage driven devices, such as IGBT, Power MOSFET and static induced thyristor (SITH); (2) Current driven devices, such as thyristor, GTO and GTR. By the effective signal waveform applied by a drive circuit between the control and common terminals of the power electronic device. (1) Pulse triggered type, such as thyristor and GTO; (2) Electronic control type, such as GTR, Power MOSFET and IGBT. By the involvement of the internal electron and hole carriers in power electronic devices in the conduction: (1) Bipolar devices, such as power diode, thyristor, GTO and GTR; (2) Unipolar devices, such as Power MOSFET, SIT and Schottky Barrier Diode (SBD); (3) Composite devices, such as MOS Controlled Thyristor (MCT), IGBT, SITH and IGCT. 2.3.1.2

Advantages and Disadvantages of Devices

(1) Power diode: Simple structure and principle and reliable work; (2) Thyristor: Withstand the highest voltage and current capacity of all devices; (3) GBT: Fast switching speed, low switching loss is small, ability to withstand the impulse current shock, low on-state voltage drop, high input impedance, voltage driven and requiring low driving power; but the switching speed is lower than Power MOSFET, and the voltage and current capacity are inferior to GTO; (4) GTR: High voltage resistance, high current, good switching characteristics, strong through-current capability and low saturation voltage; low switching speed, current driven and requiring high driving power, complex drive circuit with the problem of secondary breakdown;

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53

(5) GTO: Large voltage and current capacity, suitable for high-power occasions, with conductivity modulation effect, and strong through-current capability; very small current turn-off gain, high gate negative pulse current when turn-off, low switching speed, requiring high driving power, complex drive circuit and low switching frequency; (6) Power MOSFET: Fast switching speed, high input impedance, good thermal stability, requiring low driving power, simple drive circuit and high operating frequency without the problem of secondary breakdown; However, with the small current capacity and low pressure resistance, it is generally only suitable for the power electronic equipment whose power does not exceed 10 kW.

2.3.2 DC Power Supply Conversion 2.3.2.1

Two-Level VSC Switching Unit

The variable structure control (VSC) has become the preferred implementation object for the following reasons: the VSC has a low system cost due to its simple station allocation; the VSC realizes bidirectional current flow, which is easier to reverse the direction of power flow; the VSC can control the active and reactive power on the AC side; the VSC is not so dependent on AC network as LCC and can supply power to the passive load and has black start capability. Figure 2.19 shows the single-phase structure of a two-level VSC. Using the PWM modulation method to control the on–off of the upper and lower bridge arm devices, the U o can jump between − U d /2 and + U d /2. The waveform of U o is a bipolar PWM wave equivalent to the modulated sine wave U t . Fig. 2.19 Schematic diagram of single-phase structure of two-level VSC

54

2.3.2.2

2 Types and Control Technology of Drive Motors for New Energy Vehicles

Controllable DC Voltage

Assuming that the switching frequency of the converter is f 0 = 1/T 0 , the operation of the converter in one switching cycle is shown in Fig. 2.20, and the width of positive and negative pulses is determined by parameter m. In a switching cycle T 0 , the converter generates voltages + E and − E of a certain width, and the average output voltage is V0 = ⟨(V0 (t))⟩T0 =

  T0 T0 1 −(1 − m) E + (1 + m) E = m E T0 2 2

(2.3)

It can be seen from Eq. (2.3) that the average output voltage is a linear function of m. m directly determines the width of the voltage pulse. If m is changed in the interval [− 1, 1], the average output voltage can be changed in the interval [− E, + E] to realize the linear control of the output voltage. The output voltage is not pure DC voltage, but contains controllable DC voltage component and high-frequency voltage component. If the dynamic of the load powered by this power supply is slow enough, the high-frequency voltage component has no significant impact on the load, and the load voltage is mainly determined by the controllable DC voltage component. For example, in a high-power DC motor, the inertia axis responds only to the average voltage due to the low-pass filter nature of the “slow” mechanical system. Therefore, the motor speed is mainly determined by the DC voltage component (average value) of the output voltage. As long as the minimum time constant of the load is much larger than the switching cycle T 0 , it can be considered that the load has sufficiently slow dynamic characteristics and sufficient damping effect on high-frequency oscillation. Under the action of the high-frequency voltage component (greater than or equal to the switching frequency), the load does not have enough time to change significantly, so it can be assumed that the load only responds to the change in the average voltage component (DC). The following discusses how to generate the drive signals of T 1 and T 2 to obtain the voltage waveform as shown in Fig. 2.21. In Fig. 2.20, the cycle of the triangular wave (carrier signal) is T 0 , and the given voltage corresponds to m. A comparator is used to compare the two signals. When m is larger than the carrier signal, the drive signal that makes T 1 on is generated; otherwise, the drive signal that makes T 1 off is generated. The drive signal of T 2 is complementary (opposite) to that of T 1 . According to the above method, the on–off state as shown in Fig. 2.20 can be obtained. By changing the size of m, the width of voltage pulse can be changed, and then the DC output voltage can be changed. The number of intersections between the carrier signal and the given signal in a period of time is directly determined by the carrier frequency. At every intersection, the on–off state of the switching device changes once. Therefore, the carrier frequency is also known as the switching frequency. When determining the switching frequency, it is necessary to consider the load time constant and the switching loss of the converter.

Given signal

Fig. 2.20 Switching signal that drives the switching unit

Carrier signal

2.3 Power Electronics and Inverter 55

56

2 Types and Control Technology of Drive Motors for New Energy Vehicles Carrier signal

Given signal

Fundamental component

Fig. 2.21 Controllable AC voltage generated using PWM

2.3.2.3

Controllable AC Voltage

To generate a controllable DC voltage, the given signal m is an invariant constant to keep the average output voltage constant. If the given signal m changes slowly with time, its magnitude is basically constant in a switching cycle (carrier cycle) and the output voltage is averaged in a sliding window along the time axis, then the average voltage can be observed to change slowly with the given signal. If the given signal is a sine wave of low frequency (compared to the carrier), the voltage pulse train output by the converter also contains a sinusoidal component of the same frequency, then r (t) = m sin(ωr t)

(2.4)

where wr is the frequency of the output AC voltage, wr 1, there is no longer a linear relationship between the fundamental amplitude and the modulation degree, and when m is very large, it enters the saturation region. In practice, nonlinearity will increase the complexity of the system, so it is necessary to limit the output of the control unit that generates m to avoid the situation that m > 1.

2.3.2.4

Controllable AC Current

The switching unit can be controlled using PWM technology to generate controllable DC or AC voltage. The basic principle of PWM technology is to compare the highfrequency triangular carrier with the low-frequency modulated wave (given voltage signal) and generate an appropriate drive signal according to the comparison results. Regardless of the type of the modulated wave, a PWM controlled switching unit

58 Fig. 2.23 CR-PWM technology

2 Types and Control Technology of Drive Motors for New Energy Vehicles Given current Actual current

Upper limit

Lower limit

can generate a series of voltage pulses with modulated width. The low-frequency component of the output voltage is determined by the modulated wave and is consistent with the given DC or AC voltage. Other frequency components in the output voltage are generated by the PWM itself and not expected. According to the actual needs, these high-frequency components can be filtered out by a filter, or may not be processed. By improving the common PWM technology and using CR-PWM (CurrentReference PWM), the switching unit can also generate controllable AC current. In Fig. 2.23, there is a given current and two envelopes, and the envelope changes with the given current. The basic principle of CR-PWM is to output an appropriate voltage so that the load current is in the two envelopes. If the upper and lower envelopes are sufficiently close to the given current, the tracking of the given current by the load current is considered to be achieved. As shown in Fig. 2.23, the control method used in CR-PWM is as follows: when the current reaches the lower envelope, the switching device T 1 is on, the load voltage is + E, and the load current increases; once the current reaches the upper envelope, the switching device T1 is off, T2 is on, the load voltage is − E, and the load current decreases until the current reaches the lower envelope again. The narrower the bandwidth between the upper and lower envelopes, the closer the load current is to the given current, but the more switching times, the greater the switching loss. Different from PWM, which generates controllable voltage, CRPWM has unfixed switching frequency, which brings difficulties to the design of the harmonic suppression filter. The unfixed switching frequency is a disadvantage of CR-PWM.

2.3 Power Electronics and Inverter

AC-DC converter

Three-phase input

59

DC link

DC

DC-AC inverter

Three-phase output

Fig. 2.24 Structure chart of AC–DC–AC converter

2.3.2.5

AC–DC–AC Converter

AC–DC–AC converter is introduced here on the basis of rectifier and DC–AC converter. As the name suggests, this type of converter consists of two stages. Use a diode or a thyristor three-phase bridge to convert the input alternating current into direct current, and then use a three-phase VSC to generate the required threephase alternating current. To accomplish the above conversion, a DC bus shall be set between two converters, and appropriate DC devices shall be used to filter the harmonics on the DC bus. The commonly used DC devices are filter capacitor and filter inductor. The AC–DC–AC converter can be shown in Fig. 2.24 regardless of the external circuit. Although the AC–DC–AC converter has relatively complex structure, this type of converter has many advantages. The intermediate DC link is used to isolate the threephase input from the three-phase output, so that the dynamic and static characteristics of the two do not affect each other. If the DC link has strong anti-interference capability, the two-stage converter has the characteristics of convenient design, high efficiency and good performance. In particular, it is important to point out that the output stage of the converter (DC–AC part) can be implemented using the PWM technology introduced earlier, and can also be implemented using other control technology with good performance and small harmonics.

2.3.3 Inverter 2.3.3.1

Brief Introduction

The inverter is a DC–AC transformer, which, in contrast to the converter, implements a voltage inversion process. The converter converts the AC voltage of the grid into a stable 12 V DC output, while the inverter converts the 12 V DC voltage output by the converter into a high-frequency high-voltage alternating current. Both parts also use the more widely used PWM technology. The core part is a PWM integrated controller, UC3842 for the converter and TL5001 chip for the inverter. The working voltage range of TL5001 is 3.6–40 V. The inverter is internally installed with an error

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amplifier, regulator, oscillator, PWM generator with dead zone control, low voltage protection circuit and short circuit protection circuit, and is characterized as follows: (1) High conversion efficiency and fast start; (2) Good safety performance: protection against short circuit, overload, over/under voltage and over temperature; (3) Good physical performance: the product adopts all-aluminum shell with good heat dissipation performance, the surface is hard oxidized, with good friction resistance, and can resist a certain external force of extrusion or collision; (4) Strong adaptability and stability with load. The inverter inputs three signals: 12 V DC input VIN, operating enabled voltage ENB, and motherboard current control signal DIM. The VIN is supplied by the converter and the ENB voltage is supplied by the MCU on the motherboard with a value of 0 or 3 V. When ENB = 0 V, the inverter does not work; when ENB = 3 V, the inverter is in normal working status; DIM voltage is provided by the motherboard, and its variation range is between 0 and 5 V. When different DIM values are fed back to the feedback terminal of PWM controller, the inverter will provide different current to the load. The smaller DIM value is, the larger the output current of the inverter will be. The voltage enabled circuit outputs a high voltage to light the backlight tube of the motherboard when the ENB is at high level. The PWM controller provides internal reference voltage and is composed of the error amplifier, oscillator, pulse width modulator, output transistor, etc., with the overvoltage protection, under voltage protection and short-circuit protection functions. The voltage conversion circuit is composed of the MOS switching tube and energy storage inductor. After the input pulse is amplified by the push–pull amplifier, the MOS tube is driven to make on–off action, so that the DC voltage charges and discharges the inductor, and the other end of the inductor can get AC voltage. The LC oscillation and output circuit ensures the 1600 V voltage required for the backlight tube starting, and reduces the voltage to 800 V after the backlight tube starting. The output voltage is to back feed the sampling voltage to stabilize the output voltage of the inverter when the load is working. The variable frequency drive (VFD) is generally used in the motor control and the inverter is the main component of the VFD. The inverter is powered by direct current, while the VFD is powered by alternating current. Both can output the alternating current of variable frequency to regulate the motor speed. The induction motor belongs to the AC motor and its speed depends on the power supply frequency, and is approximately proportional to the power supply frequency. Changing the power supply frequency can change the motor speed. The VFD can output the alternating current of variable frequency, and is used to drive the induction motor. By simply adjusting the frequency of the VFD can the motor speed be conveniently adjusted, which can also play an energy-saving role in many occasions. In addition, the VFD can also effectively reduce the starting current.

2.3 Power Electronics and Inverter

2.3.3.2

61

Classification of Inverters

1. By the wave nature By the wave nature, the inverter can be classified into sine wave inverter and square wave inverter. The sine wave inverter outputs the same or better sine wave alternating current as the power grid we use everyday, because it doesn’t have electromagnetic pollution in the grid. The square wave inverter outputs the square wave AC with poor quality, which occurs almost at the same time from the positive maximum value to the negative maximum value, causing severe unstable influence on the load and the inverter itself. At the same time, the square wave inverter has poor load capacity, only 40–60% of the rated load and cannot bear an inductive load. If the load carried is too large, the third harmonic component contained in the square wave current will increase the capacitative current flowing into the load, and even damage the power filter capacitor of the load. According to the above shortcomings, a quasi-sine wave (or called modified sine wave and simulated sine wave simulation, etc.) inverter is developed and its output waveform has a time interval from the positive maximum value to the negative maximum value, which improves the use effect. However, the waveform of the quasi-sine wave is still made up of broken lines and belongs to square wave, so the continuity is poor. In general, the sine wave inverter can provide high-quality alternating current and drive any type of load, but it has high technical requirements and cost. The quasi-sine wave inverter can meet most of our electricity demand and has become the mainstream product in the market because of its high efficiency, low noise and moderate price. The square wave inverter is made by simple multivibrator, whose technology is at the level of 1950s, and will gradually exit market. 2. By power source By power source, the inverter can be classified into coal power inverter, solar inverter, wind inverter and nuclear inverter. 3. By purpose By purpose, the inverter can be classified into independently controlled inverter and grid-connected inverter. The efficiency of the solar inverters in the world is high in Europe and the United States. The standard is 97.2% but the price is high in the Europe. The efficiency of other domestic inverters is below 90%, but the price is much lower than that of imported inverters. In addition to the power and waveform, the efficiency is also very important when choosing an inverter. The higher the efficiency, the less electric energy will be wasted on the inverter, and the more electric energy will be used for electrical appliances. This is especially important when using low power systems. 4. By source nature By source nature, the inverter can be classified into active inverter and passive inverter. The active inverter is an inverter in which the current in the current circuit is connected to the grid on the AC side, but not directly connected to the load; the passive inverter is an inverter in which the current in the current circuit is not connected to the grid on the AC side, but directly connected to the load (that

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is, the DC is inverted into the AC of a certain frequency or adjustable frequency for the load). 5. By grid-connection type By grid-connection type, the inverter can be classified into off-grid inverter and grid-connected inverter. 6. By topology By topology, the inverter can be classified into two-level inverter, three-level inverter and multilevel inverter. 7. By power level By power level, the inverter can be classified into high power inverter, medium power inverter and low power inverter. 2.3.3.3

Function of Inverter

The function of the inverter is to convert direct current (battery, storage battery) into alternating current (generally 220 V, 50 Hz sine wave or square wave). Popularly speaking, the inverter is a device that converts direct current (DC) into alternating current (AC). It is composed of the inverter bridge, control logic and filter circuit and widely used in automobiles, air conditioning, home theater, electric grinding wheel, electric power tools, sewing machine, DVD, VCD, computer, television, washing machine, range hood, refrigerator, video, massager, fan, lighting fixtures, etc. Simply put, the inverter is an electronic device that converts low-voltage (12, 24, or 48 V) direct current into 220 V alternating current. The inverter is named as it has the contrary function as that the 220 V alternating current is usually rectified into the direct current for use. We are in a “mobile” era of mobile office, mobile communication, mobile leisure and entertainment. The inverter can meet the demand for the low-voltage direct current supplied by the battery or storage battery and for the 220 V alternating current in the mobile state.

2.3.3.4

Common Types

1. Small and medium-sized power type This type of inverter is one of the important links in the household independent AC photovoltaic system. Its reliability and efficiency are crucial for promoting the photovoltaic system, using the energy efficiently and reducing the system cost. Therefore, photovoltaic experts in various countries have been trying to develop the inverter power supplies suitable for household use, in order to promote the industry to develop better and faster. 2. Multiple series type This inverter has many advantages when applied to electric vehicles. The variety of voltage vectors output by the series structure is greatly increased, which enhances the flexibility of control, improves the accuracy of control, and reduces

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63

the fluctuation of voltage at the neutral point of the motor. The bypass feature of the inverter improves the flexibility of charging and regenerative braking control. With the growing concern about the urban environment, the development of electric vehicles has faced a rare opportunity. In the urban traffic, electric buses have become the development priority due to their large carrying capacity and high comprehensive benefits. Most electric buses adopt the three-phase AC motor. Due to the large motor power, the devices in the three-phase inverter need to withstand high voltage and high current stress. Moreover, the high dV/dt makes the electromagnetic radiation serious, and needs good heat dissipation. The high power inverter of multiple series structure can reduce the voltage stress on a single device, reduce the requirement of the device, reduce the dV/dt value, reduce the electromagnetic radiation and greatly reduce the heating of the device. The control performance is better due to the increased variety of output levels. The multiple series inverter is suitable for high-power electric vehicle drive systems. The use of the multiple series structure can reduce the danger of multiple storage batteries connected in series, reduce the switching stress of the device and reduce the electromagnetic radiation, but the number of batteries required has tripled. To maintain the balance of electric quantity of each group of storage battery, the discharge time of batteries shall be kept the same during operation. By bypass mode, the storage batter can be flexibly charged and the torque of regenerative braking can be controlled.

2.3.3.5

Application of Vehicle-Mounted Inverter

The vehicle-mounted inverter is generally powered by the vehicle battery or cigarette lighter. It first converts the low voltage DC into about 265 V DC, and then converts the high voltage DC into 220 V, 50 Hz AC. The vehicle-mounted inverter breaks many limitations in the use of electrical appliances in the vehicle. The vehicle power supply is not only suitable for vehicle-mounted systems and can be used in the occasions with 12 V DC power supply. The vehicle-mounted inverter will shut down automatically in case of overload or short circuit with fully consideration to the external operating environment. The vehicle-mounted inverter is a kind of power supply product which works at high current and high frequency, and its potential failure rate is quite high. Therefore, be careful about the inverter when purchasing. (1) In addition to the price factor, the main factors to consider the vehicle power supply are the requirement for the input voltage and the size of the output voltage. Moreover, due to large difference in the power of various electrical appliances, the vehicle power supply shall be selected according to the usage requirement. (2) Appropriate vehicle power supply is selected according to the different types of electrical appliances used. The square wave, modified wave or sine wave inverter is allowable for daily resistive electrical appliances, while the sine wave inverter must be selected for inductive electrical appliances.

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(3) The square wave/modified wave inverter power supply cannot carry inductive load or capacitive load, cannot drive the air conditioning or refrigerator and is also difficult to power the high-quality audio and televisions. (4) The cigarette lighter fuse in ordinary cars is 10 or 15 A (10 A fuse for old models or original imported models), indicating that power of the vehicle-mounted inverters used in ordinary cars is 120 or 180 W. If a high power inverter (more than 180 or 200 W) is required, be sure to see whether there is a battery conductor holder in the package. There will be restrictions on the use of high-power inverter without a battery conductor holder in a car.

2.3.4 Practical Problems of Power Electronic Circuits 2.3.4.1

Torque Ripple

Torque ripple is the torque ripple of various mechanical transmission shafts during working and is closely related to the working capacity, energy consumption, efficiency, running life and safety performance of power machinery. The measurement of torque is of great significance to the determination and control of the transmission shaft load, the strength design of the working parts of the powertrain system and the selection of the capacity of the prime mover. The torque ripple is mainly affected by the cogging torque, electromagnetic ripple torque, armature reaction and mechanical process. It is precisely because these factors are caused by the mechanical structure of the motor itself that the torque ripple test is particularly difficult, and not precise. Figures 2.25 and 2.26 show the torque ripple trend and test results of the drive motor system respectively. 1. Effect of torque ripple The motor acts directly on the load. In the process of operation, the torque ripple caused by the cogging torque, electromagnetic effect and machining and assembly technology will be directly transferred to the load, thus affecting the system speed stability and control precision. Especially under the condition of light load and low speed, the ripple torque accounts for a relatively large proportion of the motor output torque, and this effect cannot be ignored. Therefore, accurate measurement of the ripple torque becomes a problem to be solved in the practical application of the motor. 2. Principle of generating torque ripple (1) Ideal cogging torque ripple The general structure form of permanent magnet torque motor is that the rotor assembled with the permanent magnet and the stator is slotted. The cogging torque is a kind of ripple torque with an average value of zero produced by the joint action of the permanent magnet and the edge of the stator teeth, which is generated by the change of magnetic field energy during the operation of the motor rotor, as shown in Fig. 2.27.

2.3 Power Electronics and Inverter

Fig. 2.25 Torque ripple trend

Fig. 2.26 Torque ripple test results

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Fig. 2.27 Ideal cogging torque ripple

Permanent magnet

Tooth

Tooth

Tooth

(2) Torque ripple caused by armature reaction Assuming that the magnetic field distribution is not affected by the armature reaction, but the armature reaction will always occur during the operation of the motor, the armature reaction of the quadrature axis will distort the magnetic field and cause the asymmetry of the entire magnetic field distribution, thus changing the counter EMF waveform and generating torque ripple. For the permanent magnet torque motor, the change in the magnetic field distribution by its armature reaction is negligible due to the close permeability of the used permanent magnet material to the air. 2.3.4.2

Switching Loss

The turn-on and turn-off of a power device takes a period of time and is not instantaneous. In a very short switching time, the voltage and current carried by the device can undergo drastic changes. When the device is completely turned off, the current flowing through the device is basically zero, and when the device is turned on, the voltage is also basically zero (which is basically negligible compared with other voltages in the circuit). Therefore, when the device is turned on and off, the loss on the device is very small. And in the switching process, the value of voltage or current is very large, resulting in a large loss, called switching loss. Although the switching time is very short, hundreds or thousands of state changes (depending on the switching frequency) in 1 s can add up to a significant switching loss. The switching loss is generated during turn-on and turn-off of the power device. The switching loss is converted into heat energy, which will increase the temperature of the power device itself and other nearby devices. Increasing the surface area of the power device facilitates heat exchange (natural cooling or forced air circulation) with the surrounding environment. In power electronic circuits, heat sinks are usually used to help dissipate heat from the device. The heat sink can provide a large heat exchange area in a relatively small volume, taking away as much of the heat generated by the power device as possible.

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(a) Inductive load

(b) Resistive load

Fig. 2.28 Oscillogram of current and voltage during load turn-off

Switching loss includes turn-on loss and turn-off loss. In general, the turn-off time t off of most devices is much longer than the turn-on time t on , that is, the turn-off loss dominates the switching loss, and the turn-on loss in a switching is negligible. As shown in Fig. 2.28, it is difficult to accurately solve the integral of the product of instantaneous voltage and current values due to the complex voltage and current waveforms during turn-on and turn-off. Therefore, the current and voltage waveforms within the switching time interval (turn-off time t off or turn-on time t on ) are often processed linearly and approximately in the following way, so as to simplify the calculation process of the switching loss. For inductive load, the current cannot change suddenly, so it can be approximated that the current Ist remains unchanged and the device voltage rises linearly from zero to Us during the whole turn-off period. Thus, it is not difficult to find the turn-off loss, i.e. 

1/ f s

Po f f = f s

 u(t)i (t)dt = f s

0

t1

t2

Us Us Ist to f f f s (t − t1 )Ist dt = to f f 2

(2.6)

where t 2 = t 1 + t off ; Us and I st represent the quiescent voltage and maximum current respectively; fs represents the switching frequency; toff indicates the turn-off time. For resistive load, the current decreases linearly from I st at time t 1 and drops to zero at time t 2 . The device voltage rises linearly from zero at time t 1 to U s at time t 2 . Thus, it is not difficult to find the turn-off loss, i.e. 

1/ f s

Po f f = f s 0



t2

u(t)i (t)dt = f s t1

  Us Ist Us Ist (t − t2 )dt = to f f f s (t − t1 ) − to f f to f f 6 (2.7)

In addition, the turn-on loss Pon is calculated in the similar way to the turn-off loss Poff , and it is only needed to replace t off in the formula with ton . In this way, the switching loss of the device can be obtained by Pon + Poff .

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For some devices, the relation curve of loss and related parameters for a single turn-on and turn-off will be given in the product manual. After finding out the single switching loss corresponding to a specific current in the curve, the corresponding turn-on loss and turn-off loss can be calculated by using Eq. (2.8), i.e. Pon = E on f s

(2.8)

From the above discussion, it can be seen that reducing the switching loss is beneficial to improve the efficiency of the whole system, use smaller and lighter switching devices in the circuit and reduce the volume of the heat sink. Therefore, reducing the switching loss is of great significance to the power electronic circuits. Both efficiency and performance shall be considered in designing power electronic circuits. Generally, the higher the switching frequency, the better the converter performance, but this will increase the switching loss of the system and reduce the system efficiency. The use of fast switching devices can improve the performance of the system, without increasing the loss of the system too much, which makes it possible to further improve the switching frequency of power electronic circuits. Because of the shorter switching time and lower switching loss, the use of fast switching devices is beneficial to improve the system efficiency in the occasions with low switching frequency.

2.3.4.3

Noise and Electro Magnetic Interference

A power electronic circuit operating at a high switching frequency will produce electro magnetic interference (EMI), interfere with other devices (including control system), and may produce noise, which is harmful to people working or living nearby. In order to minimize these side effects while meeting the requirements of relevant application standards, a comprehensive analysis is required on the EMI and noise problems of the power electronic circuits. EMI refers to the outward transmission of electromagnetic energy in the form of electric and magnetic fields when the current or charge changes over time. The alternating electromagnetic field produced by the EMI source can be divided into two parts with different properties: induction field where the electromagnetic field energy flows back and forth periodically in the space around and between radiation sources, without outward emission; and radiation field where the electromagnetic field energy escapes from the radiating body and is emitted outwards in the form of electromagnetic waves. In general, the electromagnetic field is classified into far-zone field and near-zone field according to the difference of induction field and radiation field. The division of the far-zone field and near-zone field is relatively complex and shall be carried out according to different working environments and measurement purposes. Generally speaking, the region centered on the field source and within the range of three wavelengths is called the near-zone field, also called the induction field; and the region centered on the field source and beyond three wavelengths is called the far-zone field, also called the radiation field.

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In the study of radiated interference, the antenna is a radiation source that produces electromagnetic waves, and the electric dipole and the magnetic dipole are the two most basic radiation elements. Many elements in actual power electronic circuits can be equivalent or approximately equivalent to these two radiation elements. The electric dipole, also called current element, is a basic radiation element. The EMI of the electric dipole. Let its length and lateral dimension be much smaller than the wavelength. The circuit carries a high-frequency current I = Im sinωt. Since the length of the electric dipole is much smaller than the wavelength, the current at each point on the dipole can be considered to be in phase with equal amplitude. The electric dipole is the basic component of the wire antenna, which is composed of a large number of basic arrays. In calculating the trajectory of a single circuit on a printed circuit board (PCB), if the trajectory length L is much smaller than the wavelength and field distance, then the EMI of the trajectory of the single circuit on a PCB can be analyzed by using an electric dipole model. Figure 2.29 is the schematic diagram of the radiation field of the current element in the spherical coordinate system. The electromagnetic field in the middle of the electric dipole can be obtained from the Maxwell’s equation   I l cos θ 1 k − jkr e + j 2π ωε r 3 r2   I l cos θ 1 k k 2 − jkr e Eθ = − j +j 2− 4π ωε r 3 r r   k − jkr I l cos θ 1 e + j Hφ = − j 4π ωε r 2 r

(2.10)

E φ = Hr = Hθ = 0

(2.12)

Er = − j

Fig. 2.29 Solve the radiation field of current element

(2.9)

(2.11)

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In Eqs. (2.9) to (2.12): l is the length of the electric dipole; I is the current effective value; r is the distance between the observation point and the origin; k = 2π/λ(rad/m), where λ is the wavelength. According to the distance between the observation point and the origin, the field domain can be divided into three parts, namely, the near-zone field, the middle-zone field and the far-zone field. λ . At this time, the field is mainly induction field, and (1) Near-zone field: r « 2π its field quantity equation is simplified as

Er = − j

I l cos θ − jkr e 2π ωεr 3

(2.13)

Er = − j

I l cos θ − jkr e 4π ωεr 3

(2.14)

I l cos θ − jkr e 4πr 3

(2.15)

E φ = Hr = Hθ = 0

(2.16)

Hφ =

From the derivation of Eqs. (2.13) to (2.16), it can be seen that the near-zone field usually has the following characteristics: in the near-zone field, there is no definite proportional relationship between the electric field intensity and the magnetic field intensity. Generally, for field sources with high voltage and low current (such as transmitting antenna, feeder, etc.), the electric field is much intenser than the magnetic field; for field sources with low voltage and high current (such as the mold of some induction heating equipment), the magnetic field is much intenser than the electric field. The electromagnetic field in the near-zone field is much intenser than that in the far-zone field. From this point of view, the focus of electromagnetic protection should be on the near-zone field. The intensity of the electromagnetic field in the near-zone field changes rapidly with the distance, and the inhomogeneity is larger in this space. λ . This field is the superposition of induction field and (2) Middle-zone field: r ≫ 2π radiation field. λ . At this time, the field intensity changes inversely with (3) Far-zone field: r ≫ 2π the increase of the propagation distance. The field is an radiation field, and its field quantity equation can be simplified as

Eθ = j

I lk 2 cos θ − jkr e 4π ωεr

(2.17)

I lk sin θ − jkr e 4πr

(2.18)

Hϕ = j

Er = E φ = Hr = Hθ = 0

(2.19)

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When the current element is placed in free space, the characteristic impedance of the free space is k Eφ = = W0 = Hϕ ωε

/

μ = 120π(Ω) ε

(2.20)

The radiation field quantity equation can be further rewritten as Eθ = j

60π I l sin θ e− jkr rλ

(2.21)

Il sin θ e− jkr 2λr

(2.22)

Hϕ = j

Er = E φ = Hr = Hθ = 0

(2.23)

The main characteristics of the far-zone field are as follows: all electromagnetic energy in the far-zone field basically radiates in the form of electromagnetic wave, and the attenuation of the radiation intensity of this field is much slower than that of the induction field, that is, the far-zone field is weak and its electromagnetic field intensity is small. Usually, for a fixed electromagnetic radiation source that can produce a certain intensity, the electromagnetic field intensity of the near-zone field is relatively large, so special attention should be paid to the protection of the EMI near-zone field. The protection of the EMI near-zone field is firstly the protection of operators and the personnel in the near-zone field environment, and secondly the protection of various electronic and electrical equipment in the near-zone field. The far-zone field is usually less harmful to people because of the low intensity of electromagnetic field. The frequency bands we are most often in contact with from the short-wave band 30 MHz to the microwave band 3000 MHz are in the wavelength range of 1–10 m.

2.4 Vehicle Motor Control Technology 2.4.1 Vector Control Technology The dynamic mathematical model of the asynchronous motor is a high-order, nonlinear and strongly coupled multivariable system. The basic principle of vector control is that by measuring and controlling the stator current vector of the asynchronous motor, the exciting current and torque current of the asynchronous motor are controlled respectively according to the principle of magnetic field orientation, so as to achieve the purpose of controlling the torque of the asynchronous motor.

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Vector control, also known as field-oriented control (FOC), is a technology that uses a variable frequency drive (VFD) to control the three-phase AC motor. This technology controls the output of the motor by adjusting the output frequency of the VFD, the magnitude and angle of the output voltage. It can control the magnetic field and torque of the motor respectively, similar to the characteristics of the separately excited DC motor. This technology is called vector control as the three-phase output current and voltage are expressed as vector in processing. The vector control is an advanced method to control the AC motor, in which the V/F control aims to maintain the motor flux constant, so that the motor maintains high efficiency. Scope of application of vector control: (1) Vector control can only be used when one VFD controls one motor; (2) The motor capacity can be at most one level different from the motor capacity required by the VFD; (3) The number of magnetic poles of the motor recommended to be generally 2, 4 and 6, and the high-precision vector control can be extended to more than 10 poles; (4) The vector control is not feasible for the torque motor, current-displacement motor, double squirrel cage motor and other special motors. 2.4.1.1

PI Regulator Based Motor Vector Control

The proportional-integral regulator, referred to as PI regulator, is a linear controller that forms the control deviation according to the given value and the actual output value, and linearly combines the proportion and integral of the deviation to form the control quantity to control the controlled object. The regulator control law most widely used in practical engineering applications is the proportional-integralderivative control, also known as PID control, as shown in Figs. 2.30 and 2.31. By carrying out the PID operations on the deviation signal e(t) and weighting the results, the PID controller obtains the output u(t) of the controller, which is the control value of the controlled object. Proportional regulation action: reflect the deviation of the system proportionally. In case of system deviation, the proportional regulation action will be immediately produced to reduce the deviation. Large proportional action can speed up the regulation and reduce the error, but excessive proportion will make the stability of the system decline, even cause system instability. Integral regulation action: eliminate the steady-state error of the system and improve the error free degree. As long as there is error, the integral regulation is carried out until there is no error. Then the integral regulation is stopped, and a constant value is output. The strength of the integral action depends on the integral time constant T i . The smaller T i , the stronger the integral action, and the regulation process may be made tend to be stable in a short period of time to eliminate the deviation as soon as possible. On the contrary, The larger T i , the weaker the integral action and the longer the integration time, increasing the time required for stabilization of the regulation process and resulting in slow deviation elimination. Integral

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Proportional element, P

Integral element, I

Controlled object

Derivative element, D

Fig. 2.30 Block diagram of PID regulating system

Fig. 2.31 Bode diagram of PID regulation

regulation is often combined with two other regulation rules to form a PI regulator or PID regulator. In brief, the actions of the PI regulator in each correction link are as follows: (1) The proportional element reflects the deviation signal of the control system proportionally. In case of a deviation, the regulator immediately produces the regulation action to reduce the deviation. Generally, with the increase of the proportional value, the overshoot of the closed-loop system increases and the response speed of the system accelerates. However, when the proportional increases to a certain extent, the system will become unstable. (2) The integral element is mainly used to eliminate the static error and improve the system’s error free degree (type). The strength of the integral action depends on the integral constant. The larger the integral constant is, the weaker the integral action will be, vice versa. The smaller the overshoot of the closed-loop system is, the slower the response speed of the system will be.

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In general, in the practice of control engineering, the PI regulator is mainly used to improve the steady-state performance of the control system.

2.4.1.2

Motor Vector Control Based on Sliding Mode Control Unit

Sliding mode control (SMC), also known as variable structure control, is a special kind of nonlinear control in essence, and the nonlinearity is manifested as the discontinuity of control. The difference between this control strategy and other controls is that the structure of the system is not fixed, but can be changed purposefully and constantly according to the current state of the system (such as deviation and its derivatives, etc.) in the dynamic process, forcing the system to move along the state trajectory of the predetermined sliding mode. The sliding mode can be designed and is independent of object parameters and disturbance, which makes the SMC have the advantages of fast response, insensitiveness to parameter changes and disturbances, no need for on-line system identification, and simple physical implementation. At present, the traditional PI regulator is widely used for the controller of the PMSM speed control system and has simple algorithm and convenient parameter setting. However, for PMSM, a nonlinear and strongly coupled multivariable system, the traditional PI control method cannot accurately control the PMSM when the control system is affected by external disturbance or when the internal parameters of the motor change with the temperature and component aging. In order to improve the dynamic quality of the PMSM speed control system, a sliding mode controller can be used to reduce the influence of the motor parameter changes, and the sliding mode controller has fast response speed. The SMC is a control strategy of the variable structure control system, which differs fundamentally from the conventional contract strategies in terms of the discontinuity of control, i.e. a switching characteristic that makes the system structure change with time. This characteristic is manifested in that it can make the system fluctuate up and down at a small amplitude and high frequency along the prescribed trajectory under certain conditions, so as to achieve a sliding state. This state can be designed mathematically and is independent of the system parameters and disturbance, which makes the control system very robust. Generally, the nonlinear system function includes state control and time variables. We need to determine the sliding mode surface function and solve the controller function. There are three basic elements in SMC: dynamic existence of sliding mode, accessibility conditions and stable motion in sliding mode. Usually, the motion of the sliding mode variable structure control system consists of two parts: normal motion outside the sliding mode surface, which is the motion approaching the sliding mode surface from the outside; motion near the sliding mode surface. Various reaching law functions are required in the whole motion process to ensure the quality of the normal motion stage. Common reaching laws include isokinetic reaching law, exponential reaching law, power reaching law and general reaching law.

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In recent years, the sliding mode variable structure method has attracted more and more attention because of its excellent characteristics. By designing the required sliding mode surface and equivalent control law, this method can quickly respond to the input transformation, has good robustness and simple physical fabrication but is insensitive to the parameter transformation and disturbance. For most control systems using the sliding mode variable structure method, the idea of combined sliding mode observation and sliding mode control is not required to design robust solutions. The sliding mode variable structure control has attracted more and more attention from scholars. The biggest advantage of the SMC is that the sliding mode is completely adaptive to the disturbance and perturbation of the system. Moreover, once the system enters the sliding mode motion, it converges to the control target quickly, which provides an effective way for the robust design of the time-delay systems and uncertain systems. The biggest problem of the sliding mode variable structure control is the jitter in the system controller output.

2.4.2 Direct Torque Control (DTC) 2.4.2.1

DTC Principle of Motor

Compared with the vector control technology, the direct torque control (DTC) system has simple structure, fast torque response and good robustness. The basic idea of DTC mode is to control the torque by adjusting the rotation speed for the torque angle adjustment while maintaining the stator flux linkage amplitude unchanged, and then control the speed of the motor. It directly controls the switching state of the inverter using the space vector analysis method, stator flux orientation, and the PWM signal generated by Bang-Bang control. The application of this control mode to PMSM for electric vehicles has a broad prospect and will further improve the power performance and reliability of electric vehicles. 1. Torque equation in stator coordinate system To derive the PMSM electromagnetic torque in the stator coordinate system, the coordinate system as shown in Fig. 2.32 is established. In the figure, α–β is a stator reference coordinate system of stationary two-phase stator, where the axis α coincides with the axis of the stator phase a winding; x–y is the reference coordinate system of the synchronous rotating two-phase stator; d–q is a rotating rotor coordinate system, and axis d is the flux axis direction of rotor permanent magnet; δ is the torque angle. The stator flux linkage and current follow the following transformation from the d–q coordinate system to the stator x–y rotating coordinate system: 

   ϕx cos δ sin δ id ϕd = − sin δ cos δ i q ϕy ϕq

(2.24)

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Fig. 2.32 Coordinate system for DTC

Since the stator flux linkage is positioned on the axis x, the following relationship exists:    ix cos δ sin δ id = (2.25) − sin δ cos δ i q iy According to Fig. 2.32,

φx = |Ψs | φy = 0

(2.26)

where Ψs represents the amplitude of the stator flux linkage. By integrating Eqs. (2.24) to (2.26), we can obtain: Tem =

3 p|Ψs | [2Ψ f L q sin δ − |Ψs |(L d − L q ) sin 2δ] 4L d L q

(2.27)

where T em is electromagnetic torque; Ψ f is the permanent magnet flux linkage. It can be seen that the electromagnetic torque includes permanent magnet torque and reluctance torque. The required torque can be obtained as long as the amplitude and torque angle of the stator flux linkage are adjusted according to certain rules. 2. Generation of voltage space vector Figure 2.33 shows the wiring method of the PMSM powered by a voltage source inverter. The power device is in 180° conduction mode. That is, only three switching signals S a , S b and S c are required to uniquely determine the working status of the inverter. S a = 1 is defined to switch on U dc ; otherwise, switch on 0. S b is defined similarly to S c . The basic voltage space vector us is defined as us =

2 (u a + u b e j (2/3)π + u c e j (4/3)π ) 3

(2.28)

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Fig. 2.33 Wiring method of PMSM powered by a voltage source inverter

where ua , ub and uc are the instantaneous phase voltage values of three phases. It can be seen that the three-phase output voltage is a function of the switching quantities S a , S b and S c , and the output phase voltage of the inverter can be expressed as ⎡ ⎤⎡ ⎤ ⎤ 2 −1 −1 Sa ua ⎥⎢ ⎥ ⎢ ⎥ 1⎢ ⎣ u b ⎦ = ⎣ −1 2 − 1 ⎦⎣ Sb ⎦Udc 3 −1 − 1 2 uc Sc ⎡

(2.29)

where U dc is the DC power supply voltage. 3. Flux linkage and torque control In the α–β coordinate system, the relationship between the stator flux linkage and the input voltage is  Ψs =

(u s − i s R)dt

(2.30)

If the influence of the stator resistance is ignored, then  Ψs =

u s dt

(2.31)

Equation (2.31) is discretized to obtain Ψs = u s t + Ψs0 t

(2.32)

where Ψs0 is the initial value of flux linkage. This indicates that the amplitude, rotation direction and speed of the stator flux linkage can be precisely controlled by controlling the input voltage vector us of the PMSM, as shown in Fig. 2.34. When the PMSM system is in a transient state, the stator and rotor flux linkages rotate at different speeds, and the angle δ between the stator and rotor flux linkages changes. When the system is in steady state, the stator and rotor flux linkages are rotating at synchronous speed and δ is a constant value. Since the electrical time constant is much smaller than the mechanical time constant, the change of the electromagnetic torque can be controlled by changing the rotation speed of the stator flux linkage.

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Fig. 2.34 Effect of voltage vector on stator flux linkage

Considering that different voltage vectors have different effects on the flux linkage and torque, in order to effectively select the on–off state of the inverter, the α–β coordinate plane is equally divided into six areas, as shown in Fig. 2.35, and the voltage space vector U 1 is taken in the same direction as the axis α. After the voltage space vector plane is partitioned, the appropriate voltage space vector can be selected according to the flux linkage and torque changes at any time to complete the control process. For example, when the torque is less than the reference value, the selected voltage vector should enable the stator flux linkage to accelerate the rotation along the original direction; on the contrary, when the torque increases too fast, the voltage vector that causes the stator flux linkage to rotate in the opposite direction is selected. By choosing the voltage vector reasonably and keeping a certain switching frequency, the trajectory of the stator flux linkage can be close to a circle, and its rotation direction is determined by the output of the torque hysteresis controller. In a practical system, the switching signal is obtained by hysteresis comparison of the error between the given value of torque and stator flux linkage and the feedback Fig. 2.35 DTC voltage vector plane partition

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Speed controller

79

Torque regulation

On-off state selection

PWM inverter

Magnetic flux adjustment

Motor model

Code

Fig. 2.36 Structure block diagram of PMSM direct torque control system

value, indicating whether the effect of the chosen voltage vector is to increase or decrease the actual torque and flux linkage. The closed-loop control can be realized after the observed value of the stator flux linkage and the feedback value of electromagnetic torque are obtained. The structure block diagram of the PMSM direct torque control system is shown in Fig. 2.36.

2.4.2.2

SMC Based Direct Torque Control

1. Overview SMC is a control method of the variable structure control (VSC) system. Different from most methods, SMC achieves strong robustness based on discontinuous control, during which the structure of the SMC system is constantly changed. In other words, the control structure will change constantly according to the current state of the system, so that the system will keep moving in the previously set sliding mode. The SMC has sliding characteristics, so it is also called sliding mode control. The period from 1957 to 1962 was the primary development stage of VSC. The VSC was proposed by Soviet Union scholars Utkin and Emelyanov, who studied the secondorder linear systems at that time. From 1962 to 1970, researchers used the high-order linear systems as controlled objects, but they were still single-input single-output systems. It was not until 1970 that the VSC study on linear systems was carried out in linear space. In 1977, Utkin published a review paper on VSC and explained VSC and SMC. Therefore, a large number of researchers initiated the study with the multidimensional VSC system and multi-dimensional sliding mode as controlled objects, and the exploration of VSC system was extended from the previous specification space to the more common state space.

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SMC has now become an important branch system of control science. Because the sliding mode can be set in advance and is independent of the internal parameter perturbation and external interference of the controlled object, SMC has fast response ability and strong robustness. When the controlled object of the system is a nonlinear system, SMC still has excellent control effect, so the control method has been widely used in robot, aircraft, switching converter, servo system and other fields. After the SMC enters the sliding mode motion stage, it is difficult to strictly slide along the preset sliding mode surface to the origin, sometimes shuttling repeatedly on both sides of the sliding mode surface, which leads to buffeting. Buffeting will not only bring some burden to the controller, but also reduce the control effect and even activate the unmodeled high-frequency components. Therefore, how to reduce the buffeting induced by SMC and better play the advantages of SMC has become a hot topic discussed by a large number of researchers at home and abroad in recent years. 2. Theoretical principle SMC is a kind of nonlinear control with switching effect, which is also different from other methods. SMC enables the system to regularly switch back and forth between different logics along the pre-designed trajectory. At this time, SMC is in the sliding motion stage, insensitive to the unknown interference inside and outside the system and other unclear factors, and has good robustness. In general, for the following nonlinear system: x˙ = f (x) x ∈ R n

(2.33)

There is a sliding mode surface s(x) = s(x 1 , x 2 , …, x n ) = 0, which divides the state space into the part with s > 0 part and the part with s < 0, as shown in Fig. 2.37. At the same time, the motion points have the following forms: (1) Point A, as shown in Fig. 2.37, moves from one side of the sliding mode surface to the sliding mode surface and then flies to the other side. Such point is a normal point; (2) Point B, as shown in Fig. 2.37, flies from both sides of the sliding mode surface to the sliding mode surface. Such point is the termination point; Fig. 2.37 Characteristics of motion points on switching surfaces

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(3) Point C, as shown in Fig. 2.37, flies out from around the sliding mode surface to both sides. Such point is the starting point. In all three cases, the motion points like points A and C are not of much significance. The significant points are termination points like point B. If any point around the sliding mode surface is the termination point, as long as there are motion points, they will be “attracted” here, so the area with the function of “attracting” is called the sliding mode area, and the motion in this area is the sliding mode motion. Figure 2.38 is the schematic diagram of SMC. SMC generally needs to combine with the dynamic characteristics of the target in designing the sliding mode surface. The sliding mode controller is designed to force the motion point to move towards the sliding mode surface. Once the motion point reaches the sliding mode surface, the SMC will make the system move towards the origin along the sliding mode surface. Thus it can be seen that the sliding mode motion generally consists of reaching and sliding stages. The so-called reaching is the motion from outside s = 0 towards s = 0, which ensures that the system can reach the sliding mode surface from any initial position, or it can be said to be a finite number of motions through s = 0; sliding is the motion on the sliding mode surface, and the motion at this stage has good robustness to the interference inside and outside the system and other unclear factors. To realize the SMC, the following three elements shall be satisfied: (1) Existence of sliding mode If the motion points move towards the sliding mode surface from the distance on both sides of s = 0, then they enter the sliding mode area. It is known that the motion points with these characteristics are the termination points, and will move along the sliding mode surface, so there must be lim+ s˙ ≤ 0 and lim− s˙ ≥ 0, equivalent to s→0

s→0

lim s s˙ ≤ 0

y→0+

In practical application, s s˙ = 0 is on the sliding mode surface, i.e. Fig. 2.38 Schematic diagram of SMC

(2.34)

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lim s s˙ ≤ 0

s→0

(2.35)

is a sufficient condition for SMC sliding mode to exist. (2) Accessibility of sliding mode The motion points can be at any position in the state space initially. When the initial position is far away from the sliding mode surface, if the system state can reach the sliding mode surface in a finite time, the accessibility condition is satisfied, and lim s s˙ ≤ 0

s→0

(2.36)

The Lyapunov accessibility condition can be constructed as V (x) =

1 2 s < 0, V˙ (x) < 0 2

(2.37)

(3) Stability of sliding mode motion When the above two requirements are met, the SMC motion needs to be asymptotically stable after the system enters the sliding mode area to ensure that the SMC motion cannot escape from the sliding mode area and has excellent dynamic quality.

2.4.3 Switched Reluctance Motor Control Technology In the early development of the switched reluctance motor drive (SRD) system, in order to improve its performance, the research on SRD mainly focused on improving the structural design and power converter circuit design of the switched reluctance motor (SRM), while the research on SRD control technology was based on the linear mathematical model of SRM, and the linear control technology was applied to realize the SRD operation control. The switched reluctance motor is more and more popular in the market because of its simple and strong structure, low cost, many control parameters, high efficiency and suitability for high speed and harsh environment, but the nonlinearity and large torque ripple of the motor itself limit its wide application in the industrial field. With fast response speed, the speed control system of the switched reluctance motor, rich I/O ports and can generate 16 PWM signals. It has simple hardware structure and excellent performance. The switched reluctance motor has many controllable parameters and flexible control. After a linear model is established for the switched reluctance motor, the motor can be divided into three different control modes according to the excitation modes: current chopping control (CCC), chopping voltage control (CVC) and angular position control (APC).

2.4 Vehicle Motor Control Technology

2.4.3.1

83

Structure and Characteristics of SRD System

The switched reluctance motor drive system, referred to as SRD system, consists of the switched reluctance motor, power circuit, controller and position and current detection devices. SRM is a component that realizes electromechanical energy conversion in the SRD system. The power circuit converts the alternating current into pulsed direct current acceptable to the motor. In the SRD system, the power circuit plays a very important role. The controller, as the brain of the SRD system, analyzes and processes the feedback information provided by the current sensor and position sensor, and judges the IG-BT on–off in the circuit accordingly, so as to realize the control of SRM. The current detection device is used to detect the current of the motor phase winding and generate the current feedback information of the system. The position detection device uses an absolute encoder to detect the relative position of the stator and the rotor to provide signals for the controller to change phase and calculate speed.

2.4.3.2

Inherent Mechanical Properties of SRM √ Ω = Us F/Tav

(2.38)

where Ω is the angular velocity of rotor rotation; U s is the phase voltage at both ends of the winding; Tav is the motor torque; F is a function with the motor structural parameters (m, N r , θ 2 , L max , L min ) and control parameters (θ on , θ off ) as variables. For a given motor, its structural parameters are fixed. If U s , θ on and θ off are fixed, the inherent mechanical properties of the motor are Tav = k/ Ω2

(2.39)

P = k/Ω

(2.40)

where k = Us · F; P is the output power of the motor. The intrinsic mechanical characteristics of the motor can be shown in Fig. 2.39. The inherent mechanical characteristics of the reluctance motor are similar to the series excitation characteristics of the DC motor. For a given motor, there is a critical angular speed at the maximum voltage Us and the maximum allowable current, that is, the highest angular speed at which the SRM obtains the maximum torque, called the base speed. The driving operation and torque angle characteristics of the reluctance motor can be shown in Figs. 2.40, 2.41 and 2.42.

2.4.3.3

Three Control Modes

The switched reluctance motor has many controllable parameters, including motor phase voltage Us , phase current Is , turn-on angle θon and turn-off angle θoff . According

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2 Types and Control Technology of Drive Motors for New Energy Vehicles

Constant torque area CCC mode

Constant power area APC mode

Series characteristic area θc fixed

Fig. 2.39 Intrinsic mechanical characteristics of motor

Current chopping controllable area

Starting chopping

Fixed angle chopping Variable angle chopping

APC control

Variable angle running area

Fig. 2.40 Reasonable selection of control mode

Conducting phase control

Fig. 2.41 Torque angle characteristics of four-phase switched reluctance motor

2.4 Vehicle Motor Control Technology

85

Conducting phase control

Fig. 2.42 Torque angle characteristics of two-phase switched reluctance motor

to the excitation modes, the motor is generally divided into the following three control modes: current chopping control (CCC), chopping voltage control (CVC) and angular position control (APC). Different control modes are used at different speeds. The realization methods of the three control modes are detailed below. 1. Current chopping control (CCC) When the motor starts or runs at low speed, the counter electromotive force is small, and the motor winding current rises quickly and reaches the peak quickly. In order to avoid damage to IGBT and motor windings caused by excessive current, it is necessary to limit the peak current. In this case, the CCC mode can be used to obtain the mechanical characteristics of constant torque at low speed. CCC control method: The upper limit I max and lower limit I min of the phase current, as well as corresponding voltage values U max and U min are set. Then, the current value obtained by Hall sensor is converted into voltage signal by corresponding signal conditioning; the collected voltage signal is compared with the set upper and lower voltage limits. If the voltage value is greater than the set lower voltage limit, the corresponding power switch of the power circuit will be on. At this time, the current will increase, and the voltage will also increase; during the period when the voltage signal increases, the voltage signal is fed back to the circuit. When the voltage is greater than U max , the power switch on the power circuit is turned off, the current starts to decrease, and the voltage decreases accordingly. In this way, the voltage value is limited between the maximum value and the minimum value by repeated turn-on and turn-off of the IGBT, and the corresponding current is limited between the set upper and lower limits. As long as the speed is limited to our design requirements, a current chopping pattern will be formed. The commutated winding is still subject to the current chopping control, as shown in Figs. 2.43, 2.44 and 2.45. For the current chopping control below base speed, a constant torque is output and the controllable quantities are U s , θ on and θ off . When the inductance is very small, the winding is turned on and the current rises rapidly. To prevent excessive current from damaging the motor, when the current reaches the maximum value I max , the

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2 Types and Control Technology of Drive Motors for New Energy Vehicles

Fig. 2.43 Current chopping control

Fig. 2.44 Chopping diagram of upper and lower amplitude of current

winding is turned off and the current begins to decay. When the current decays to Imin , the windings is turned on again. The winding must be turned off before the maximum inductance occurs to prevent the current from extending to the negative torque area. Control method 1: Fix θ on and θ off and limit the current through the current chopping to obtain a constant torque. Control method 2: Fix θ on and θ off and modulate U s according to the difference between the set speed and the actual value to change the torque.

2.4 Vehicle Motor Control Technology

87

Fig. 2.45 Chopping diagram of upper current limit and turn-off time

2. Chopping voltage control (CVC) The CVC is a control mode in which the turn-on angle θon and the turn-off angle θoff are constant and the power switching device IGBT adopts PWM working mode. In this way, the pulse cycle is kept unchanged, and the average voltage applied at both ends of the winding is adjusted by adjusting the duty cycle, so as to change the effective value of the winding current, as shown in Fig. 2.46. Increasing the pulse frequency will make the current waveform smoother, increase the motor output and reduce the noise, but the operating frequency of the power switching device will be more and more demanding. In the system, the rotor position signal collected by the Hall sensor is transmitted to the controller through the signal conditioning circuit. The controller calculates the current speed according to the Hall signal as the feedback of the inner loop, then judges the on/off state of three phases A, B, and C in the next stage, and calculates the turn-on angle and turn-off angle accordingly. The output signal of the outer speed Fig. 2.46 PWM chopping voltage controlled current waveform

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2 Types and Control Technology of Drive Motors for New Energy Vehicles

Fig. 2.47 Relationship between T av and θ on , θ off during APC operation

Increase

loop is used as the input signal of the inner current loop, and the collected current signal is sent to the DSP controller as the real-time input signal of the speed closed loop. The PI output of the system will eventually change the pulse width of the PWM wave, so as to change the effective value of the phase current of the motor winding. 3. Angular position control (APC) APC is to change the winding power-on and power-off time and adjust the phase current waveform by changing the turn-on angle θ on and the turn-off angle θ off under a certain winding voltage, so as to realize the speed closed-loop control. Detect the jump edge of the motor position signal using DSP timer capture unit, calculate the signal cycle and motor speed according to the captured signal and output the control pulse of the angular position signal according to the set angle without interruption using the DSP comparator. For the Hall sensor, the transmitted position signal is particularly important. Firstly, the position signal shall provide the initial signal for the angular position control, and the calculation of motor speed by DSP is also achieved by capturing the position signal of a cycle, so the angular position control especially depends on the real-time performance of the position signal, as shown in Fig. 2.47. The APC is used above the base speed and the constant power is output, as shown in Fig. 2.48. At high speed, due to the large counter electromotive force, the current is limited and rises slowly. When the current reaches the maximum value, the current decreases as the inductance increases. Similarly, to prevent the current from extending to the negative torque area, the winding shall be turned off before the inductance reaches its maximum value. The higher the speed, the sooner it turns off. The CCC is suitable for low speed motor running stage and is simple, direct and controllable. Compared with the CVC mode, the CCC has less switching loss, stable and reliable torque, and is suitable for the torque regulation system. Its disadvantage is obvious: the chopping frequency is not fixed and changes with the winding current error, which is not conducive to the elimination of the electromagnetic noise.

2.4 Vehicle Motor Control Technology

89

Fig. 2.48 Angular position control

The CVC is suitable for high speed and low speed operation, and will make fast dynamic response in case of load disturbance of the system. The disadvantage is large torque ripple at low speed. The APC is not suitable for low speed operation and is generally suitable for higher speed control. The APC has large torque regulation range and the motor can maintain at high efficiency under different loads through angle optimization.

2.4.4 Steady State Control Method of Induction Motor 2.4.4.1

Brief Introduction to Control Method and Principle

The main function of the AC induction motor control system is to provide variable voltage and variable frequency power supply for the motor, and its voltage and frequency can be adjusted according to a certain control strategy, so that the drive system has good torque-speed characteristics. The basic equation of AC induction motor speed control is n = n s (1 − s) =

60 f (1 − s) p

(2.41)

The motor speed can be adjusted by changing s, p and f , so the basic speed control mode of the AC induction motor can be classified into three types accordingly:

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2 Types and Control Technology of Drive Motors for New Energy Vehicles

variable voltage control, pole changing speed control and variable frequency speed control. Changing the input power voltage of the induction motor for speed control is called variable voltage control, which is a variable slip speed control mode; changing the magnetic pole number of the induction motor to change the speed of the synchronous rotating magnetic field is called pole changing speed control, and its speed presents step changes; changing the input power frequency of the induction motor to change the speed of the synchronous rotating magnetic field is called variable frequency speed control, its speed can be changed uniformly.

2.4.4.2

VVVF Control

The VVVF speed control system of the asynchronous motor is commonly referred to as variable frequency speed control system. Because the slip ratio does not change with the speed and the speed range is wide and the efficiency is high whether at high speed or low speed, the system can achieve high dynamic performance comparable to the DC speed control system after taking certain technical measures, so it is used widely. An important factor to be considered in the motor speed regulation is the desire to keep the magnetic flux Φm per pole in the motor constant at the rated value. It is a waste that the motor core is not fully utilized when the magnetic flux; if the magnetic flux is increased excessively, it will make the core saturated, resulting in excessive exciting current and even damaging the motor due to overheated winding. For the DC motor, the excitation system is independent and it is easy to keep the magnetic flux constant as long as there is proper compensation for the armature reaction. In the AC asynchronous motor, the magnetic flux Φm is generated by the synthesis of the stator and rotor magnetic potential, so it is more complicated to keep the magnetic flux constant. The stator electromotive force per phase is E g = 4.44 f 1 N1 k N 1 Φm

(2.42)

the air-gap flux in each phase of the stator, in V; f 1 is the stator current frequency, in Hz; N 1 is the number of series turns of each phase winding of the stator; k N1 is the fundamental winding coefficient; Φm is the air-gap flux per pole, in Wb. According to Eq. (2.42), as long as E g and f 1 are well controlled, the purpose of magnetic flux Φm control can be achieved. In this regard, two cases below the fundamental frequency (rated frequency) and above the fundamental frequency should be considered. 1. Speed regulation below fundamental frequency To keep the magnetic flux Φm constant, Eg must be lowered simultaneously when the frequency f1 is adjusted downward from the rating f1N , so that

2.4 Vehicle Motor Control Technology

91

a-without compensation b-with stator voltage drop compensation

Fig. 2.49 Constant V/F control characteristics

Eg =c f

(2.43)

However, at low frequency, when both Us and Eg are relatively small, the component of the stator impedance voltage drop is more significant and cannot be ignored. In this case, the voltage Us needs to be artificially raised to approximately compensate for the stator voltage drop. As shown in Fig. 2.49, the constant V/F control characteristics with the stator voltage drop compensation are shown in line b, and the control characteristics without compensation are shown in line a. 2. Speed regulation above fundamental frequency In the speed regulation above fundamental frequency, the frequency rises upward from f 1N , but the stator voltage U s cannot exceed the rated voltage U sN and can only maintain U s = U sN at most, which will force the magnetic flux to decrease inversely with frequency, equivalent to the case of DC motor flux-weakening speed up. Figure 2.50 shows the control characteristics of the two cases below the fundamental frequency and above the fundamental frequency.

2.4.4.3

Constant V/F Control

The voltage/frequency ratio (V/F) control, as shown in Fig. 2.51, is a method to control the magnetic flux. The V/F can be preset in the system to maintain the magnetic flux at a certain level. It is mainly applied in the VFD to save the energy consumption of the motor. If the motor voltage is constant and only the frequency is reduced, then the magnetic flux is too large, the magnetic circuit is saturated, and the motor will

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2 Types and Control Technology of Drive Motors for New Energy Vehicles

Speed control by constant torque

Speed control by constant power

Fig. 2.50 VVVF speed control characteristics

VFD

Inhibition link

Fig. 2.51 V/F control diagram

be burned in serious cases. Therefore, the frequency and voltage shall be changed proportionally, that is, the VFD output voltage shall be controlled while changing the frequency, so as to keep the magnetic flux of the motor constant and avoid the phenomenon of flux weakening and magnetic saturation. The V/F control is based on this idea to ensure that the output voltage is controlled proportionally to the frequency. It is generally used for fan and pump motor load. The vector control is shown in Fig. 2.52. Compared with V/F control, the vector control has larger torque and is suitable for heavy load occasions and low-frequency occasions where torque is to be guaranteed. At present, the vector control of the domestic motors is not perfect, which cannot be reflected in practical application, or cannot be adjusted automatically according to the load. At present, the V/F control is more commonly used in the market, and the factory default V/F parameter can be basically used in general occasions. Some manufacturers list the corresponding parameter setting methods for heavy load, light load and different loads, and most VFDs allow users to customize the V/F curve to adapt to different occasions.

Bibliography

93

Permanent magnet synchronous motor

Vector change

Rotation angle θ

Stator current

Vector change

Fig. 2.52 Vector control diagram

Bibliography Andersson A, Lennstrom D, Nykanen A (2016) Influence of inverter modulation strategy on electric drive efficiency and perceived sound quality. IEEE Trans Transp Electr 2(1):24–35 Besnerais JL, Lanfranchi V, Hecquet M et al (2009) Characterization and reduction of magnetic noise due to saturation in induction machines. IEEE Trans Magn 45(4):2003–2008 Boldea I, Tutelea LN, Parsa L et al (2014) Automotive electric propulsion systems with reduced or no permanent magnets: an overview. IEEE Trans Ind Electron 610:5696–5711 Gieras JF (2015) Noise of polyphase electric motors. CRC, Boca Raton Hannan MA, Ali JA, Mohamed A et al (2017) Optimization techniques to enhance the performance of induction motor drives: a review. Renew Sustain Energy Rev 81(2):1611–1626 Holmes DG (2003) Pulse width modulation for power converters: principles and practice. IEEE Xplore Islam R, Husain I (2010) Analytical model for predicting noise and vibration in permanent-magnet synchronous motors. IEEE Trans Ind Appl 46(6):2346–2354 Iyer NPR (2019) AC to AC converters: modelling, simulation, and real-time implementation using simulink. CRC, Boca Raton Krishnan R (2012) Permanent magnet synchronous and brushless DC motor drives [Feng C et al., trans.]. China Machine Press, Beijing Lin F, Zuo S, Deng W et al (2016a) Modeling and analysis of electromagnetic force, vibration and noise in permanent magnet synchronous motor considering current harmonics. IEEE Trans Industr Electron 63(12):7455–7466 Lin F, Zuo S, Wu X (2016b) Electromagnetic vibration and noise analysis of permanent magnet synchronous motor with different slot-pole combinations. IET Electric Power Appl 10(9):900– 908 Nam KH (2015) AC motor control and electrical vehicle applications. CRC, Boca Raton Singh J, Singh B, Singh SP et al (2012) Performance investigation of permanent magnet synchronous motor drive using vector controlled technique. In: The 2nd international conference on power, control and embedded systems. IEEE, Allahabad, India Zhang B, Qiu D (2019) M-mode SVPWM for multilevel inverter. In: M-mode SVPWM technique for power converters. Springer, Berlin Zhu ZQ, Howe D (1993) Instantaneous magnetic field distribution in permanent magnet brushless DC motors IV magnetic field on load. IEEE Trans Magn 29(1):143–151

Chapter 3

New Energy Vehicle Powertrain Technology

3.1 Introduction Depending on the types of new energy vehicles, the new energy vehicle powertrain can be classified into BEV powertrain, HEV powertrain and FCEV powertrain. The electric vehicle has a variety of powertrain architectures, the connections between the motor and the transmission or other drive mechanisms are diverse. The common battery electric vehicle structure and its powertrain system are shown in Fig. 3.1. In Fig. 3.1, D is the differential mechanism, FG is the reducer with fixed gear ratio, GB is the transmission, M is the motor, and VCU is the vehicle control unit. The HEV powertrain is mainly classified into: series hybrid powertrain, parallel hybrid powertrain and combined hybrid powertrain. The series hybrid powertrain is driven by a motor, and the engine is only used as an energy storage system. The energy generated by the engine is stored and used to run the motor, as shown in Fig. 3.2. The engine is not directly involved in driving, but theoretically the operating point of the engine can be in any low fuel consumption area or low emission area. The engine and motor of the parallel hybrid powertrain can drive the wheels jointly or independently, with the structure shown in Fig. 3.3. The parallel hybrid powertrain reduces the loss of energy conversion, but the operating point of the engine cannot theoretically be in any low emission area or low fuel consumption area. The combined hybrid powertrain is shown in Fig. 3.4. The power of the engine can be transmitted in two routes, i.e. to drive the wheels through the mechanical path or to be converted into electric power. The convergence of the electric power and mechanical power can be realized through a dynamic coupling device. Compared with traditional vehicles, the FCEV has relatively slow dynamic response and output characteristics of fuel cells cannot meet the vehicle driving requirements in starting, rapid acceleration or climbing. In practice, the FCEV often

© Huazhong University of Science and Technology Press and Springer Nature Singapore Pte Ltd. 2023 Y. Chen, New Energy Vehicle Powertrain Technologies and Applications, Key Technologies on New Energy Vehicles, https://doi.org/10.1007/978-981-19-9566-8_3

95

96

3 New Energy Vehicle Powertrain Technology Front wheel

Rear wheel

Rear wheel

DFG M (c) Drive system integration

Front wheel

Rear wheel

(e) Dual-motor and fixed-gear direct drive

Front wheel

Rear wheel

(b) Multi-speed drive

(a) Single-speed drive

Front wheel

Front wheel

Rear wheel

(g) Dual-motor four-wheel drive

Front wheel

Rear wheel

(d) Fixed drive ratio drive of two-wheel motor

Front wheel

Rear wheel

(f) Dual-hub motor drive

Front wheel

(h) Four-hub motor drive

Fig. 3.1 Common battery electric vehicle structure and its powertrain system

Rear wheel

3.1 Introduction

97

Fig. 3.2 Series hybrid powertrain

Fig. 3.3 Parallel hybrid powertrain

needs to use the fuel cell hybrid electric vehicle design method. That is, an auxiliary power device (battery, supercapacitor or battery + supercapacitor) is introduced to be grid-connected with the fuel cell through the power electronic equipment to provide the peak power, in order to make up for the deficiency of the fuel cell output power in acceleration or climbing. In addition, when the power of the fuel cell is

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3 New Energy Vehicle Powertrain Technology

Fig. 3.4 Combined hybrid powertrain

greater than the driving power of the vehicle under idling, low speed or deceleration conditions, the excess energy can be stored, or the braking energy can be absorbed and stored during regenerative braking, so as to improve the energy efficiency of the whole power system. The FCEV power system is classified into direct fuel cell hybrid system and parallel fuel cell hybrid system by structure. The direct fuel cell hybrid system is shown in Fig. 3.5. The motor control unit is used as the power electronic equipment in this system. The fuel cell and the auxiliary power unit are directly connected to the entrance of the motor control unit. In the design, a bidirectional DC/DC converter can be added between the auxiliary power unit and the DC bus of the power system. As the bidirectional DC/DC converter can better control the voltage or current of the auxiliary power unit, it is also an execution unit of the system control strategy, which makes the charging and discharging of the auxiliary power unit more flexible. The parallel fuel cell hybrid system is shown in Fig. 3.6. In the parallel fuel cell hybrid system, a DC/DC converter is usually installed directly between the fuel cell and the motor control unit. The terminal voltage of the fuel cell is matched to the voltage level of the system DC bus through the boost or buck of the DC/DC converter. This power system is designed without consideration to the energy feedback recovery, so the system is simple but inefficient. Usually, a DC/AC converter is also required for the AC motor drive system to maintain the voltage of the system DC bus within the optimal voltage range for the motor system operation.

3.1 Introduction

99

Vehicle accessories

Fuel cell pile system Reducer

Motor

Fuel cell energy Energy from auxiliary energy storage system Energy from vehicle feedback

Auxiliary energy storage

Fig. 3.5 Direct fuel cell hybrid system

Wheel

Drive motor

Fuel cell pile system

Control signal Electric energy Mechanical energy

Fig. 3.6 Parallel fuel cell hybrid power system

Battery

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3 New Energy Vehicle Powertrain Technology

3.2 Hybrid AMT Technology 3.2.1 Electric Drive Powertrain Through a general survey of the development of multi-speed AMTs at home and abroad, in 2010, Zeroshift developed a 3-speed AMT; in 2011, German IAV developed a 2-speed planetary variable speed electric drive Drivepacev80 (2AT) and Graziano developed a 2-speed AMT (2AMT) for passenger vehicles and light commercial vehicles; in 2012, Hyundai and Sungkyunkwan University jointly designed a multi-axis 2-speed automatic variable speed electric drive assembly (2DCT) similar to DCT, Schaeffler developed a 2-speed DCT, and Dutch Antonov developed a 3-speed DCT (3DCT); in 2013, Oerlikon Graziano developed a 4-speed DCT (4DCT). Schaeffler (China) Co., Ltd. has developed a 2-speed planetary AMT for HEV 48 V systems. As shown in Fig. 3.7, the 48 V bridge hybrid solution consists of an electric motor, a two-stage planetary gear and an electro-mechanical gearshift. Gear 1 can achieve pure electric starting acceleration to 20 km/h and Gear 2 can reach the electric cruise speed up to about 70 km/h (constant vehicle speed). The transmission is driven by the HEV rear axle, which cannot drive the vehicle in full working condition. The maximum speed ratio of the planetary gear system is limited by the diameter of the sun gear and gear ring, so the wide speed ratio cannot be achieved. Schaeffler 2-speed rear-axle transmission is currently available on both Great Wall Motor WEY P8 and Changan CS75 PHEV models. GKN has developed a double-speed Axle drive system, as shown in Fig. 3.8, for BMW PHEV i8 models. The transmission is of the structure of automated manual transmission (AMT). In order to reduce the size of the system, the synchronizer gearshift is arranged on the input shaft. With the maximum speed of 14,000 r/min, the input shaft can be smoothly coupled with the synchronization system through the accurate speed control of the motor. The transmission matched motor is installed with the front axle of i8, and the rear axle is equipped with the three-cylinder engine and transmission. Subject to the hybrid system, it adopts pure electric drive at low speed, and the engine is involved in the drive at high speed to meet the needs of low speed power and high speed endurance economy. Jiangxi GETRAG, a domestic joint venture, has developed a 2eDT transmission for middle-sized and hybrid vehicles, as shown in Fig. 3.9. The motor power is transmitted to the two axle shafts through a two-stage spur gear and a differential mechanism with a speed ratio of 2.06 in Gear 1 and 8.61 in Gear 2. A synchronizer system is used to complete the shift action, and an electromechanical actuator is used to realize the shift and parking. This transmission is applied to middle-sized low-speed commercial vehicles, with low drive motor speed, low requirements for shift comfort, vibration noise and key transmission components and low difficulty in control strategy development. The two-speed AMT developed by Shanghai UCAS Electric Vehicles Co., Ltd. is of the mechanical transmission structure, as shown in Fig. 3.10, with an electronic

3.2 Hybrid AMT Technology

101 Synchronizer

1/2 driven gear

Pinion shaft Planetary gear set

1/2 drive gear

Drive gear of final reduction drive Input shaft

Intermediate shaft

Driven gear of final reduction drive

Differential mechanism

Fig. 3.7 Schaeffler 48 V bridge solution

actuator to realize the shift and parking functions of the synchronizer. The drive motor is directly connected to the input shaft of the two-speed AMT, and the clutch component is removed. The speed ratio range is limited to 5.50–9.07. This product is used in commercial vehicles, has low requirements for the electric control shift performance and easy to have abrupt shifting. In 2010, BorgWarner developed the eGearDrive for Tesla, Ford, etc. The eGearDrive is characterized as follows: (1) High-efficiency helical gear pair transmission, small backlash in circular tooth, and transmission efficiency greater than 97%; (2) Compact design and light weight, effectively reducing the weight of the vehicle; (3) Flexible motor interface and offset angle design; (4) Integrated electronic parking actuator; (5) Improved driving range and vehicle adaptability; (6) The peak input torque is 300 N·m, and the maximum input speed is up to 14,000 r/min. The EVD1, an electric drive device developed by ZF for small and compact vehicles, is designed to meet the needs of future urban transportation, as shown in Fig. 3.11. The EVD1 uses the induction motors with a maximum continuous power output of 30 kW, a maximum power output of 90 kW, and a maximum speed of

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3 New Energy Vehicle Powertrain Technology

Synchroniz

Electronic shift system

Two-stage deceleration, with Breather plug

the idler on the input shaft

Front and rear cases, passively lubricated

Differential

Fig. 3.8 BMW i8 double-speed Axle drive system

Input shaft

Intermediate shaft

Differential mechanism

Fig. 3.9 Jiangxi Getrag 2eDT transmission

up to 21,000 r/min. The reduction ratio is 16:1 and the reducer adopts two-stage deceleration, with the stage 1 of planetary gear train and the stage 2 of helical gear. There is no seal between the motor and the reducer. The shortcomings of domestic electric vehicle transmissions are mainly manifested in the following aspects:

3.2 Hybrid AMT Technology

103

Fig. 3.10 UCAS two-speed AMT

Fig. 3.11 ZF EVD1

(1) (2) (3) (4) (5)

Low degree of integrated design; Large noise vibration; Low maximum speed; Compact structure, low torque and power density; Some products do not have the parking gear.

There is a huge technological gap in the multi-speed AMT for domestic passenger electric vehicles that needs to be filled. Therefore, there is a broad market space for development of two-speed AMT for electric vehicles with leading domestic technology level. There are many cases of the electric drive transmission technology, such as FEV BEV powertrain (see Fig. 3.12), FEV and YASA electric variable two-speed electric drive device (see Fig. 3.13).

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3 New Energy Vehicle Powertrain Technology

Fig. 3.12 FEV BEV powertrain

Gear with parking lock

Parking lock system

Fig. 3.13 FEV and YASA electric variable two-speed electric drive device

Porsche Tayncan is a four-door speedster. In terms of power, it is equipped with two front and rear permanent magnet synchronous motors with an integrated power of 390 kW, a total torque of 640 N·m, a 100 km acceleration time of 3.5 s, and a maximum speed of 250 km/h. The transmission independently developed by Porsche on Tayncan weighs about 70 kg. As shown in Fig. 3.14, the transmission consists of a planetary gear set and two clutches, one for normal shift action and the other for separating the rear axle motor from the entire rear axle. There is only one shift actuator in the whole transmission. By controlling the opening and closing of two clutches, all gears can be realized: Gear 1, Gear 2, reverse gear, neutral gear and P gear.

3.2.2 Hybrid Powertrain By the power transmission route, the hybrid powertrain can be classified into series type, parallel type and combined type. In the series hybrid system, the internal combustion engine directly drives the generator to generate electricity. The electric energy generated is transmitted to the battery through the control unit, and then

3.2 Hybrid AMT Technology

105

Fig. 3.14 Porsche Tayncan transmission

transmitted by the battery to the motor to be converted into kinetic energy. Finally, the kinetic energy is used to drive the vehicle by the shift gear. With this connection, the battery regulates between the amount of energy produced by the generator and the amount of energy required by the motor to keep the vehicle working properly. This kind of power system is used more in the urban buses and less in the sedans. The parallel hybrid system has two sets of drive system, the traditional internal combustion engine system and the motor drive system. The two systems can either work in tandem or drive the vehicle independently. The system can meet the requirements of complex road conditions, and the connection mode is simple in structure and low in cost. The parallel hybrid system is applied in Honda Accord and Civic. The combined hybrid system is characterized that the internal combustion engine system and the motor drive system each have a set of mechanical shift gear. The two sets of shift gears are combined through the gear train or the planetary gear structure, so as to comprehensively adjust the speed relationship between the internal combustion engine and the motor. Compared with the parallel hybrid system, the combined hybrid system can adjust the power output of the internal combustion engine and the operation of the motor more flexibly according to the working conditions. This connection mode has complex system and high cost. Toyota Prius uses a combined connection mode. By the proportion of the output power of the motor in the output power of the whole system, that is, the difference of the hybridization rate, the hybrid power system can also be classified into the following four categories. (1) Weak hybrid system. Representative models are PSA hybrid C3 and Toyota hybrid Vitz. This hybrid system is equipped with a belt-driven starting motor (commonly known as the belt-alternator starter generator, or BSG system) on the starting motor (usually 12 V) of the traditional internal combustion engine.

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3 New Energy Vehicle Powertrain Technology

The motor is a stop-start motor used to control the engine start and stop, thereby eliminating engine idling and reducing the fuel consumption and emission. In the strict sense, a vehicle with a weak hybrid system is not a true HEV because its motor does not provide continuous power for the vehicle driving. In a weak hybrid system, the motor is usually of either 12 or 48 V voltage, of which, 48 V is mainly used in the diesel hybrid system. (2) Mild hybrid system. Representative model is the GM hybrid pickup truck. The hybrid system uses an integrated starter generator (ISG system). Compared with the weak hybrid system, the mild hybrid system, in addition to controlling the engine start-stop, can realize the following: ➀ Under deceleration and braking conditions, part of the energy is absorbed; ➁ During driving, the engine runs at a constant speed, and the energy produced by the engine can be adjusted between the driving demand of the wheels and the charging demand of the generator. The mild hybrid system typically has a hybridization rate of less than 20%. (3) Moderate hybrid system. Representative models are Honda hybrid Insight, Accord and Civic. The hybrid system also uses the ISG system. Unlike the mild hybrid system, the moderate hybrid system uses the high-voltage motor and has an additional function that when the vehicle is in acceleration or heavy load conditions, the motor can assist in driving the wheels and make up for the deficiency of the engine power output, so as to better improve the performance of the vehicle. This system has a high hybridization rate up to about 30%. At present, the related technology has been mature and widely used. (4) Full hybrid system. Representative models are Toyota Prius and the new Estima. The system uses 272–650 V high-voltage starting motor with higher hybridization rate. Compared with the moderate hybrid system, the full hybrid system can achieve or even exceed 50% of the hybridization rate. The development of technology will make the full hybrid system become the main development direction of the hybrid power technology. The hybrid systems are used in AT, DCT, CVT, DHT, as well as BorgWarner P2 system. The system is used in AT, such as P2-8AT and 6AT from Shengrui, Toyota multi-speed hybrid transmission L310, and BMW Brilliance 530Le; used in DCT such as FEV 7DCT-350 P2 hybrid system, AVL 6-speed 48 V moderate hybrid system, MAGNA 7DCT-48 V hybrid system, Geely 7DCT390Hybrid system, Great Wall WEYP8 plug-in hybrid system and BYD Pro DM-I of BYD EHS hybrid system; used in CVT, Jatco CVT-based 48 V-P2 hybrid system, Wanliyang CVT and Punch VT5P0-CVT; used in DHT such as SAIC EDU, Honda i-MMD, GAC G-MC, Chevrolet Volt general Voletc system, GWM Lemon hybrid DHT 2-speed cylindrical gear 2DHT system and Geely planetary gear 3DHT system. The future development of DHT in the field of hybrid transmission technology must be a top priority. Figure 3.15 shows the projected market share of different types of hybrid transmission from 2017 to 2027. The plug-in hybrid system is a type of hybrid technology in which the vehicle battery is charged from an external power supply. In general, plug-in hybrid electric vehicles use more battery capacity than hybrid electric vehicles. This hybrid model

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107

Quantity/hundred million

17% compound annual growth rate

3.9 billion

1.81 billion Year

In the figure, BEV and Power Split are counted according to the number of vehicles, and others are counted according to the number of motors

Fig. 3.15 Proportion of hybrid transmission types. In the figure, BEV and power split are counted according to the number of vehicles, and others are counted according to the number of motors

is somewhere between a hybrid and a battery electric vehicle. In some cases, the hybrid vehicle is loaded with a battery and a charger to form a PHEV. Differences between the PHEV and the ordinary HEV: The ordinary HEV has a very small battery capacity, only supplies/recovers energy during start/stop and acceleration/deceleration and cannot be recharged externally or drive in the pure electric mode over long distances; the PHEV has a relatively large battery capacity and can be recharged externally and drive in the pure electric mode. After the battery is exhausted, the PHEV can drive in hybrid mode (mainly with internal combustion engine) and charge the battery at appropriate time. The plug-in hybrid drive mode is mainly driven by the motor, called hybrid electric mode, so the second drive mode (that is, range extender) has different choices. Current models and prototypes typically use the conventional engine as the second drive mode. The PHEV combines the advantages of the electric vehicle and diesel locomotive: In the short driving and urban traffic environment, the electric mode is used to achieve low noise and zero emission and save the battery power. When the battery is exhausted, the PHEV can still drive through the second driving mode (such as engine drive), with strong driving ability. The disadvantage is that it is expensive, more expensive than an independent HEV if it uses a high-capacity battery. In principle, the PHEV is a step closer to the electric vehicle era. In the future, the sales of the hybrid electric vehicles will increase gradually, and the market share of the PHEV will also increase gradually. At present, almost all vehicles adopt hybrid technology to varying degrees, and micro hybrid vehicles have become the focus of the industry due to their advantages of high cost performance. Today’s dominant full

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hybrid vehicles, most of which have power split designs, will be replaced by vehicles with powerful range extenders. The development of the PHEV with engines as range extenders is logical. In this way, the battery life doesn’t need to be too strong, costs can be controlled, and the engine can have different structures to achieve the required vehicle functions. So far, compared with conventional HEV, the PHEV has a high degree of electrification, large battery capacity and a large proportion of electric drive in the speed. Relatively speaking, the mechanical drive device proportion can be reduced. Another solution is to adopt the BEV configuration. Instead of using a mechanical drive, the recharging unit is powered independently by an integrated range extender. The advantage is that the device can be installed in a flexible position inside the vehicle, and the engine can be automatically set and optimized for a single point of operation. The following examples illustrate the application of hybrid systems. 1. Jatco CVT-48VP2 hybrid system In 2018, Jatco unveiled the conceptual model of the transmission used in the middlesized HEV. It is a Mild HYBRID combining the existing CVT and a 48 V motor. It is smaller and cheaper than the existing Strong HY-BRID, and can fully realize fuel saving. The conceptual model, which uses the same single-motor dual-clutch powertrain as Jatco CVT8HYBRID already on sale, is highly fuel-efficient because it can completely stop the engine and is driven only on electricity in the pure electric mode. In the fuel mode, 40% of its power is supplied by the electric power system, which is more than 15% less fuel than the original CVT. The low fuel consumption area in the high-speed area of CVT can be combined with the EV area of corresponding city streets. Because its length is exactly the same as the existing Jatco CVT8, it can be used without changing the design of the existing model. Figure 3.16 shows the hybrid system architecture. In Jatco 48 V hybrid system, a 15-KW motor is used instead of the hydraulic torque converter in traditional CVT. The motor is characterized by quick response and high torque. However, the CVT can withstand relatively little torque to avoid strip slippage. Therefore, the current CVT is only suitable for small motor hybrid systems, of which, 48 V hybrid system is very suitable. 2. BMW Brilliance 530Le In terms of power system, the vehicle will be equipped with a set of P2 plug-in hybrid system consisting of a 2.0 T turbocharged engine and a motor. As shown in Fig. 3.17, the motor has a power of 70 kW and a peak torque of 250 N·m; the power system has an integrated power of 185 kW, and an integrated output torque is 420 N·m. Connected to the engine is a hybrid transmission, which consists of a motor and an 8AT transmission. The 530Le can accelerate from rest to 100 km/h in 6.9 s. In terms of battery pack, the new BMW 530Le uses an ingenious dual-module concept, with a total battery capacity of 13 kW·h and a total weight of 117.2 kg, Compared with the high-voltage battery pack used in the previous generation of 5 series plug-in hybrid version, the weight has been reduced by 100 kg. The battery pack

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109

Fig. 3.16 Solution architecture of hybrid system

Hybrid transmission (electric motor included)

On-board charger

Fig. 3.17 BMW 530Le powertrain configuration

delivers instantaneous 93 kW and sustained 46 kW power output, and is designed with 15% battery redundancy to ensure eBoost capability at any battery level. Table 3.1 shows the battery pack information of the new BMW 530Le. BMW 530Le has a variety of driving modes and hybrid modes. It is equipped with a driving experience control system, which can provide four driving modes: Sport,

110 Table 3.1 Battery pack information of new BMW 530Le

3 New Energy Vehicle Powertrain Technology Parameter

Value

Battery capacity/(kW·h)

13

Weight/kg

117.2

Energy mass density/(W·h/kg)

111

Pure electric driving range/km

61

Pure electric maximum speed/(km/h)

140

Comfort, ECO PRO and ADAPTIVE. It is also equipped with the latest eDRIVE technology, i.e. AUTO eDRIVE, MAX eDRIVE and BATTERY CONTROL. In the urban road, if the AUTO eDRIVE mode is selected, the motor start will be selected in case of sufficient battery. As with most hybrid models, the motor start effectively makes up for the fuel consumption disadvantage of the gasoline engine at the low gear. Moreover, because of the excellent precision performance of the vehicle as a whole, it can avoid the impact of noise on occupant comfort in the stop-and-go congestion state. In the MAXeDRIVE mode, the vehicle runs on electricity as much as possible, and the engine automatically starts to recharge the battery in case of urgent acceleration or low battery. When the battery is low, choose BATTERY CONTROL mode, and the vehicle will be driven by the engine more and recharge the battery according to the set target value. 3. FEV 7DCT-350 P2 hybrid system Today’s traditional non-hybrid powertrain has the maximum powertrain length and transmission length. Therefore, the development of hybrid transmission without increasing the length of the powertrain has become an important development direction. Potential hybrid architectures include P2,Torque Split (P2.5) and P3 topology, of which, P2 is the most flexible and P3 is the least flexible in terms of hybrid functions. A common solution to hybrid traditional AMT is to replace the hydraulic torque converter with motor. The motor works with an applied cut-off clutch. This modification hardly affects the actual length of the P2 hybrid system and it is only required to make minor modifications to the basic transmission. The hybridization of the DCT is faced with a greater challenge than the hybridization of AT: For the P2 hybrid structure, the DCT still requires additional motor and cut-off clutch, which cannot be directly replaced like the hydraulic torque converter in an AMT. In order to limit the length increase of the DCT system after change, three clutches shall be highly integrated with the motor, which will lead to significant modifications to the basic transmission and sometimes even reduced gear to save length. Another concept for DCT hybridization is Torque Split or P2.5, where, the motor is placed parallel to the transmission and is connected to one of the input shafts. The main advantage of this structure is that only minor hardware modification is required on the basic transmission without increase in length. However, this is a challenge for

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111

the control logic of the transmission, because the gear preselection process will be closely related to the operation of the motor. In summary, DCT is the most flexible in terms of P2 hybrid structure, but challenging in terms of assembly and modularity. P2.5 is compact and modular, but challenging in terms of control strategies and hybrid functions. FEV will explain in detail the challenges faced by the current DCT hybrid structure and propose different solutions to these problems, so as to achieve the modularity and maneuverability of DCT. Figure 3.18 shows the CT350 P2 hybrid system. Table 3.2 describes the configuration parameters of the P2 hybrid system. 4. Toyota multi-speed hybrid transmission L310 The L310 transmission is composed of the input shaft, generator, drive motor, oil pump, power splitting mechanism, transmission shift, hydraulic control system and Fig. 3.18 CT350 P2 hybrid system

Table 3.2 7DCT350 P2 technical parameters

Parameter

Configuration/value

Gear number

7 + R(8 + R, FEV patent)

Torque capacity

350 N·m

Speed ratio range

6–8

Execution/cooling system

Full power on demand

Hybrid structure

P2 integrated motor and clutch

Motor power

100 kW(30 s)/50 kW

Motor torque

300 N·m

Weight (excluding oil)

< 105 kg

Installation dimensions

< 440 mm

Drive mode

FWD, AWD

112

3 New Energy Vehicle Powertrain Technology Power splitting mechanism

Fig. 3.19 Overall structure of L310 transmission

output shaft. Figure 3.19 shows the overall structure of the L310 transmission. The front end of the output shaft is connected with the V6 engine, and the rear end is connected with the power splitting mechanism. The generator is mainly used to generate electricity and the drive motor is used to drive the vehicle directly. With the power of 45 kW, the drive motor can drive the vehicle at low speed. The power splitting mechanism is used to adjust the power relationship among the engine, generator and drive motor. The transmission shift is the 4AT mentioned above, with the front end connected with the power splitting mechanism, and the rear end, as the output end, connected with the differential mechanism of the rear axle to drive the whole vehicle. The transmission archives shifting through a hydraulic control system located below the transmission. In addition, an oil pump is designed between the two motors for hydraulic drive, lubrication and cooling throughout the transmission. Figure 3.20 shows the power transmission route of the L310 transmission. The L310 transmission has three rows of planetary gear trains in its gear system. The front planetary gear train is the aforementioned power splitting mechanism, in which, the sun gear is connected to the generator, the planet carrier connected to the engine, and the gear ring connected to the drive motor and the rear 4AT. The middle planetary gear train and the rear planetary gear train are the main part of the 4AT and are combined with C1/C2 clutch, B1/B2 brake and F1 unidirectional clutch to comprise a transmission shift with 4 gears. The L310 transmission migrates the transmission shift to the output shaft, completely at the rear of the dynamically coupled system, and is designed as a 4-speed transmission shift. By combining the two parts, 10 different gears can be simulated. This will obviously increase the axial length of the transmission assembly, but this problem is relatively easy to overcome in a longitudinal vehicle. So, how about the fuel economy and power of the vehicle after the increase of gears? The main effect of adding a 4AT to the L310 is to extend the operating range of the engine, thus improving the vehicle performance at daily driving speed and reducing the engine speed at high cruising speed. At low speed, the engine torque

3.2 Hybrid AMT Technology

113 Transmission shift

Power splitting mechanism (front planetary gear train)

Drive motor Generator

Engine Output Middle planetary gear train Rear planetary gear train

Fig. 3.20 Power transmission route of L310 transmission

gradually increases with the speed and the motor is in the range of constant torque at low speed, so the low-speed gear with large drive ratio at low speed will effectively improve the output driving force of the powertrain. In contrast, the L310 can have the driving force increased by about 50% at low speed compared with the L110. This will allow the vehicle to have better acceleration performance and maximum gradeability. Increasing the L310 to 4 gears significantly increases the efficiency range of the powertrain, that is, the 4-gear transmission allows the engine and both motors to work in the high efficiency range. The increase in the powertrain efficiency interval can effectively improve the powertrain fuel economy. In a transmission with wet clutch, most of the mechanical loss comes from the drag loss. On the basis of ensuring the normal performance of the clutch, the clutch of the L310 transmission is improved to reduce the drag loss. The drag loss is mainly caused between the friction materials of the clutch and brake, so it is necessary to ensure adequate lubrication, optimize the segment shape, and reduce the drag loss caused by oil churning. Figure 3.21 shows the segment structure. Lubricating oil will accumulate between the brake and the case, and the lubricating oil churning by the friction plate will bring drag loss, so notches are designed at the spline teeth of the brake steel sheets to discharge oil. The lubricating oil will also

Fig. 3.21 Segment structure

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3 New Energy Vehicle Powertrain Technology

accumulate between the clutch hubs and the gaps between the friction plates are adjusted to improve the oil discharge performance. The shape of the friction plates shall be redesigned to improve the oil discharge performance to reduce drag loss. As can be seen from the previous mechanism introduction, the axial length of the L310 transmission is long, and the lubricating oil will accumulate at the front or rear end during acceleration and deceleration, while the hydraulic control system is located at the bottom of the transmission. In order to ensure the normal cooling and lubrication of the transmission and motor, it is necessary to fill a lot of lubricating oil to cover the whole bottom of the transmission, which is bound to increase the weight of the whole transmission, and increase the loss. Toyota uses a rotatable baffle at the lower end of the pump to split the bottom of the transmission into two storage spaces, saving 2L of lubricating oil. When the vehicle slows down, the bottom lubricating oil moves forward due to inertia, and the baffle seals the oil passage instantaneously to prevent the lubricating oil from accumulating at the bottom of the generator instantaneously. However, the baffle does not block off the oil passage, so as to that the lubricating oil for the generator can return to the bottom of the transmission. When the vehicle accelerates rapidly, the lubricating oil accumulates to the rear end of the transmission, and the inlet port is arranged in the rear position to prevent the inhalation of the air. 5. Shengrui P2-8AT, 6AT Shengrui 8AT, named SR-8AT, as shown in Fig. 3.22, with the maximum input speed of 6000 r/min, supports the front-engine front-wheel drive and front-engine fourwheel-drive models. In terms of size, weight and torque, Sungrui 8AT is available in a large torque version (maximum torque 380 N·m) in addition to the regular torque version. In terms of drive ratio, engineers have developed two versions of speed ratio after summarizing and optimizing the previous generation of products. The drive ratio of each gear of the small speed ratio version is not different from that of the first generation, with only slight adjustment, while the large speed ratio version is greatly changed. Two optimized transmissions have some progress in power, shift comfort and fuel consumption.

Fig. 3.22 Shengrui P2-8AT, 6AT

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115

6. Geely 7DCT390 Hybrid (P2.5 configuration) Geely 7DCT hybrid model integrates the motor on the input shaft, called P2.5 configuration. Geely 7DCT390 Hybrid is the first P2.5 configuration in China, which, on the basis of 7DCT330, integrates the motor on the 7DCT330 even input shaft. Similar to P3 configuration, compared with P2 configuration used by most manufacturers, this solution has the advantage of high flexibility of matching to the vehicle without increasing the axial size of the powertrain. In addition, with the P2.5 configuration, the front wet clutch module of the DCT can be shared and the high torque output can be achieved simultaneously. However, the general P2 configuration will be limited by the load torque of the wet clutch. With the existing wet clutch, it is unable to achieve the greater torque output, or a new wet clutch module needs to be developed to achieve greater torque output. According to Geely’s plan, the powertrain will cover Geely’s future A0-B sedans, SUV and MPV models, and is already applied in Lynk & Co 01, Geely GC9, Binyue, Binrui and other models. Geely 7DCT390Hybrid structure is shown in Fig. 3.23 and relevant parameters are shown in Table 3.3.

(a) 7DCT Hybrid

(b) 7DCT clutch structure (hydrostatic high pressure)

Fig. 3.23 Geely 7DCT390Hybrid structure

Table 3.3 Geely 7DCT390Hybrid parameters Parameter

Configuration/value

Length × width × height

395 mm × 586 mm × 538 mm

Gear number

7 forward gears,1 reverse gear,1 parking gear, 2/4/6/R gear feasible in pure electric mode

Maximum input torque

390 N·m

Weight

≤ 112 kg

Drive form

FWD

Life

≥ 350,000 km

Motor power torque

Peak 65 kW/160 N·m; rated 25 kW/60 N·m

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3 New Energy Vehicle Powertrain Technology

With this structure, 7DCT390 Hybrid can realize different functions such as pure electric drive, pure engine drive, hybrid drive, energy recovery, idle charging, driving charging and so on, as follows: (1) No power output: C1 and C2 are disengaged, and the odd shaft and even shaft are not put into gear; (2) Idle charging: Cl is disengaged, C2 engaged, the even shaft is not put into gear, the engine is working and driven to generate electricity; (3) Engine start: C1 is disengaged, C2 engaged, the even shaft is not put into gear and the motor drags the generator to start; (4) Pure electric drive: C1 and C2 are disengaged, the even shaft is put into gear and the motor provides power to drive the vehicle; (5) Energy recovery: C1 and C2 are disengaged, the even shaft is put into gear and the braking energy drives the engine to generate electricity; (6) Driving charging: C1 and C2 are engaged, the engine drives the vehicle through the odd shaft, and the motor drives the generator to generate electricity through the C2 clutch; (7) Hybrid drive: Cl is engaged, C2 disengaged, the odd shaft and even shaft are put into gear, the engine outputs power through the odd shaft and the motor outputs power through the even shaft to drive the vehicle. 7. Magna 7DCT-48 V hybrid system In order to establish a basic framework to meet different needs, Magna has introduced the 7DCT-48 V hybrid system based on the modular intelligent design concept, as shown in Fig. 3.24. The DCT features a torque distribution architecture, expandable power level from PHEV, a wide range of applications, and an integrated motor and inverter to reduce transmission space. The combination of a 48 V on-board voltage and a 25 kW motor allows for a variety of added values not limited to reduced emission through braking energy recovery. Depending on the specific structure, the 48 V system has other advantages such as: ➀ Better acceleration performance; ➁ Electric sliding and pure electric (engine off) cruise; ➂ Future all-wheel drive in the P4 configuration will be possible to varying degrees. The 7DCT300 Magna powertrain has successfully demonstrated that it is possible to reduce environmental impact while improving the overall ride comfort. The Magna

Clutch 2

Clutch 1

Fig. 3.24 Magna 7DCT-48 V hybrid system structure

Sub-transmission 2

Sub-transmission 1

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7-speed hybrid DCT is equipped with a 15 kW motor and an inverter. Under the WLTP cycle, the fuel consumption of a vehicle equipped with 7DCT300 can be reduced by 14–16%. This hybrid DCT combined with 48 V on-board voltage is a good mild hybrid solution. Meanwhile, 7DCT300 is also available in a 85 kW plug-in hybrid version with a motor that can run up to 400 V. With this combination, the vehicle can save the fuel by 19% up to 68% in WLTP conditions, and can even run on pure electricity on the highway. 8. Punch 48 V mild hybrid transmission The latest generation of Punch AT, with a 48 V motor, is electrically-compatible and will be used in weak hybrid models across PSA brands in the future. Punch Powertrain is an independent supplier of innovative and clean power systems with more than 45 years of experience in the production and development of continuously variable transmission (CVT). In recent years, Punch Powertrain is accelerating the development of its new products. In addition to the CVT transmission, Punch Powertrain is also developing and producing the dual clutch transmission (DCT), hybrid (48 V and plug-in hybrid) and electric transmissions. Figure 3.25 shows Punch 48 V mild hybrid transmission. The transmission is a 48 V mild hybrid system developed on 6L50 AMT. It can save 10.5% fuel under NEDC and 9.5% fuel under WLTP. The mild hybrid transmission has the main features of the BSG motor, including: ➀ Basic start-stop; ➁ Energy regeneration; ➂ Auxiliary engine torque increase ➃ Idle charging, electronic control assisted climbing and automatic cruise. The transmission is regular 6L and can support this function without changing the hardware. By developing special shift control logic, the high torque is more suitable in occasions where the vehicle needs more electric equipment. 9. DHT hybrid transmission The DHT is a hybrid drive system that essentially uses electric drive to achieve its functions, such as adjusting the revolutions and torques of the internal combustion engine during the operation of the vehicle. This means that the electric-driven auto parts receive the central task information in the DHT system, which is the central Fig. 3.25 Punch 48 V mild hybrid transmission

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component of the design and is the fundamental difference between the DHT drive and the traditional “additional drive solution”. The DHT system offers many advantages, three of which are particularly important. First, the DHT system structure is more compact and more efficient. While the number of actuators continues to be increased in the traditional AMT to prompt the drive development, the number of actuators is reduced in the DHT transmission. Second, the DHT system makes it possible to travel environmentally. With the support of electric drive, the internal combustion engine can operate more accurately in the power range to reduce the energy consumption. Finally, the electric drive can operate optimally with extra power to improve power and thus enhance the driving pleasure, which is an important advantage for the hybrid vehicles to win the market. 10. SAIC EDU system The main structure of the SAIC EDU system consists of two motors, namely, the ISG generator directly connected to the engine and the drive motor (TM motor) on the C2 clutch side. In the middle is the 2-speed AMT, where C1 is a normally disengaged clutch and C2 is a normally engaged clutch. Operating modes are pure electric, series and parallel. The power sources are the engine and battery. The power of the engine flows in two directions: first, the power is converted into electric energy by ISG generator; second, the power flows to the wheels through the clutch C2 and then through AMT. The SAIC EDU system architecture is shown in Fig. 3.26, and the specific parameter configuration is shown in Table 3.4.

Power battery EDU speed control system

Engine

Fig. 3.26 SAIC EDU system architecture

3.2 Hybrid AMT Technology Table 3.4 EDU system parameter configuration table

119 Parameter

Configuration/value

Maximum power/torque of main 50 kW/317 N·m drive TM motor Maximum power/torque of ISG generator

27 kW/147 N·m

Speed ratio

1st: 1.912; 2nd: 1.021; FD: 3.033

Maximum speed of input shaft

6800 r/min

Maximum torque of input shaft

587 N·m@1700 r/min

Clutch structure

Dry/normally open + normally closed clutch

Dimensions

390 mm × 641 mm × 442 mm

Weight with oil

≤ 115 kg

This innovative design of dual-motor and dual-clutch enables the EDU to have the following characteristics: (1) High efficiency and strong expansibility The power is all coupled through the dry clutch and there is no energy loss, so the transmission efficiency can be up to 95% from the mechanical point of view. Meanwhile, the free combination of the three power sources and the various hybrid modes formed by the variable speed can make each power source work at the most efficient operating point, which improves the overall efficiency of the system. After a high degree of integration, the entire EDU has an axial length of 390 mm, a radial length of 641 mm, and a height of 442 mm. The high degree of integration makes it possible to match multiple engines in the multi-vehicle platform. Four different engines of SAIC have been successfully matched and applied to the A, A+, B and SUV models. (2) Compact layout For the FF platform, SAIC has developed a built-in clutch. In the width of the motor, the dry clutch and its servo cylinder are placed in the motor cavity and the servo cylinder becomes a part of the motor, rather than in the traditional SPS configuration arrangement, so as to greatly save the axial space. (3) Full hybrid mode. With the engagement and disengagement of two clutches, and different working modes of different power sources, the EDU can realize all hybrid modes. Normally, the vehicle is driven by three driving modes: pure electric, series and parallel. At the high speed and high load, the vehicle is directly driven by the engine and dual motors, and the driving charging mode (combined hybrid) can also be realized. Each mode and each gear can be switched to the braking energy recovery according to the working conditions, and the power battery

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3 New Energy Vehicle Powertrain Technology

level is automatically controlled by the EDU hybrid control unit to ensure the most efficient energy output under various circumstances. (4) High fuel saving rate In addition to hardware, the software is also important to the transmission. The hardware is required to be of high integration and high reliability, while the software is required to be energy-saving, comfortable, intelligent and convenient. SAIC has innovated the wheel end torque demand analysis, directly converted the intention of the driver pedal into wheel end torque, and then distributed the torque command intelligently through the efficiency characteristics of the three power sources, improving the economical efficiency while ensuring driveability. 11. Honda i-MMD system The system consists of Atkinson cycle engine, clutch and dual motors in three-shaft layout. The engine is connected to the engine output shaft through the clutch and connected with the generator through the gears in front of the clutch; the motor is directly connected to the motor output shaft; between the engine output shaft and the motor output shaft is the third shaft, which transmits the power to the wheels. Honda i-MMD system architecture is shown in Fig. 3.27 and the specific parameters are shown in Table 3.5.

Battery

Motor Clutch Engine

Generator

Fig. 3.27 Honda i-MMD system architecture

3.2 Hybrid AMT Technology Table 3.5 Honda i-MMD system parameters

121 Engine

2.0 L Atkinson engine 105 kW(143PS)/6200 r/min 165 N·m/3500–6000 r/min

Drive motor

315 N·m

Battery

6.7 kWh, lithium ion battery

135 kW

The i-MMD system has three drive modes, as follows: (1) Pure electric mode, i.e. EV Drive. In this mode, the engine does not work, the clutch is disengaged, and the motor directly outputs the torque through the gear mechanism. (2) Series hybrid mode, i.e. Hybrid drive. In this mode, the engine generates electricity through the generator, the clutch is disengaged, and the motor outputs the torque through the gear mechanism. (3) Parallel hybrid mode, i.e. Engine drive. In this mode, the engine directly outputs torque, the clutch is engaged, and the motor outputs torque simultaneously. The realization of these three modes requires significant optimization and improvement of the system control strategy. (1) Improve fuel economy as much as possible in each mode. In Hybrid/Engine drive mode, on the basis of the original working conditions, the controller changes the engine/motor operating point to further improve the engine efficiency. In Hybrid drive mode, the engine and wheels are actually mechanically decoupled and, for the engine to operate at the optimal fuel economy position, the power required to drive the motor is compensated by the battery. In Engine drive mode, the Engine and the motor drive simultaneously. In this mode, the generator and the drive motor are involved in adjusting the operating point of the engine so that the engine operates at the optimal fuel economy position. (2) Switch modes to improve fuel economy. Switch between EV drive and Hybrid drive: Between EV and Hybrid modes, i-MMD adopts an intermittent hybrid mode, that is, the battery is involved in the power supply. In this mode, the fuel economy can be improved by up to 50% at low speed/low load, but is not improved significantly at high speed/high load and the energy efficiency in some operating conditions even decreases. Switch between Hybrid drive and Engine drive: In the Hybrid and Engine hybrid modes, the operating points of the engine and motor are not completely determined by the working conditions. In slow acceleration from cruise speed, Engine drive is more efficient, up to 12% more efficient than Hybrid drive; in intensive driving, the Hybrid drive is more efficient. 12. Other systems In the field of hybrid special transmission, BYD first completed the technical upgrade of T75 plug-in hybrid special transmission applied to Tang DM, and launched the EHS super hybrid system in the second half of 2020. EHS has been installed in

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3 New Energy Vehicle Powertrain Technology Double

Single gear reducer

Dual motor Direct drive clutch Motor oil cooling

Fig. 3.28 BYD plug-in hybrid system

BYD Qin plus, Song plus, Tang DMi and other models to achieve mass production. Meanwhile, BYD also carried out patent layout and project planning in distributed electric drive system, which further improved the platform expansion capability of BYD new energy powertrain. Figure 3.28 shows the BYD plug-in hybrid system. Great Wall Motor Honeycomb Drive developed a special 2-speed hybrid transmission, which was applied to Great Wall Lemon hybrid platform in 2021, as shown in Fig. 3.29. Honeycomb Drive 2-speed DHT features a highly integrated 7-in-1 design that supports vehicle HEV/PHEV architecture and provides 9 driving modes. Geely planetary gear 3DHT system is shown in Fig. 3.30. The extended range HEV is a series PHEV and a kind of electric passenger vehicle which is driven by pure electric energy and equipped with charging port and on-board power supply. Currently, this type of vehicle is equipped with an on-board battery and a small-displacement engine, but the engine does not output power. Such vehicle runs on electricity stored in the on-board battery. When the system determines that the power level is below a certain value, the engine will start to charge the on-board battery, thus increasing the driving range (range). The extended range electric vehicle

Fig. 3.29 Great wall motor plug-in hybrid system

3.2 Hybrid AMT Technology

123

Fig. 3.30 Geely planetary gear 3DHT system

(EREV) is developed on the basis of the battery electric vehicle. The reason why it is called extended range electric vehicle (EREV) is that the vehicle is added with a range extender to further improve the driving range of the BEV, so that it can avoid frequent stops to charge as much as possible. Working principle: When the battery is sufficient, the power battery drives the motor to provide the driving power of the whole vehicle. At this time, the engine is not working. When the battery power consumption reaches a certain level, the engine starts, provides energy for the battery and charges the power battery; when the battery is sufficient, the engine stops working, and the power battery drives the motor to provide the driving power of the whole vehicle. At present, the common extended range HEVs include Chevrolet Volt and BMW i3 extended-range version and so on. Unlike the common parallel hybrid vehicles, the extended range HEVs are driven only by motors instead of internal combustion engines. In an extended range HEV, the internal combustion engine is only used to drive the generator to generate electricity, charge the battery, drive the motor or provide energy for other electric equipment, such as air conditioning or 12 V power supply. Figure 3.31 shows the Volt hybrid system. Although the Ideal ONE has a 1.2 T gasoline engine, the gasoline engine is not involved in the power drive at all, and functions as a generator. Therefore, rather than having a 1.2 T engine, the Ideal ONE has a small-displacement generator. The Ideal ONE is a pure electric motor driven vehicle, which can be powered by a battery or a range extender. When the battery is dying, the range extender is involved and supplies power directly to the motor. The function of the range extender is to drive the motor rather than charge the battery, which greatly increases the driving mileage. Figure 3.32 shows the Ideal ONE model. The extended range HEV has the following advantages: (1) It can run in pure electric mode, requiring small battery capacity, low cost and no power shortage and roadside breakdown. (2) It can run in plug-in mode to further improve the fuel efficiency on the basis of hybrid power.

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3 New Energy Vehicle Powertrain Technology

Gasoline engine (for power generation only)

Electric control module

Lithium battery

Charging interface

Fig. 3.31 Chevrolet Volt hybrid system

Fig. 3.32 Ideal ONE model

(3) The battery charging power is small, so there is no need to build large charging facilities. (4) The battery can be charged and discharged not fully to ensure battery life. (5) With external charging mode, it can use the cheap off-peak electricity at night for charging. (6) Simple structure, direct drive motor, easy maintenance, easy and industrialization. (7) Energy saving: The engine is always in the best working condition, with high efficiency and low emission. (8) Emission reduction: The comprehensive fuel saving rate is high and the existing technology can save more than 50% of oil.

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3.2.3 Fuel Cell Powertrain Technology At present, many countries take the development of large fuel cells as a key research project, and the fuel cells will be widely used in power generation and automobile instead of the traditional generators and internal combustion engines. It is worth noting that this important new power generation method can greatly reduce the air pollution and solve the problem of power supply and grid peak load regulation. The complete 2, 4.5 and 11 MW fuel cell power generation equipments have entered into commercial production and all grades of fuel cell power plants have been built in some developed countries. Now, in North America, Japan and Europe, the fuel cell power generation technology is rapidly catching up and entering the stage of industrial scale application, which will become the fourth generation of power generation in the twenty-first century after thermal power, hydropower and nuclear power. The rapid development of the fuel cell technology in foreign countries must cause our enough attention and has been a subject that has to face in the energy and electric power industry. Technical routes of fuel cell vehicles: ➀ Fuel cell key material technology; ➁ Pile technology; ➂ System integration control technology;➃ Power system development technology; ➄ Design and integration of fuel cell vehicles; ➅ Increase power density ➆ Improve the durability ➇ Reduce the cost ➈ Improve the hydrogen loading safety. Its technical development focuses on:➀ New fuel cell core materials; ➁ Advanced fuel cell piles; ➂ Key auxiliary system component technology; ➃ High-performance fuel cell system; ➄ Decoupling fuel cell power system;➅ Hydrogen production, transportation, storage and hydrogenation infrastructure. According to the market demand and the degree of development of electric vehicles, the development scale of fuel cell vehicles is estimated as follows: in 2025, the number of fuel cell vehicles will reach 50,000, and in 2030, it will reach the level of one million; the specific power output (kW/kg) of the battery will increase from 2.0 in 2020 to 2.5 in 2030. The power system of the fuel cell vehicle is shown in Fig. 3.33. The fuel cell is a chemical cell that converts the energy released from the chemical reactions (not combustion) of substances into electricity. It needs to be continuously supplied with active substances—fuel and oxidant during working. The specific classification of fuel cells is shown in Table 3.6. The significant advantages of fuel cells are as follows: (1) Energy saving and high conversion efficiency. The operation efficiency of fuel cells is 50–70%, high at low power. The short-time overload capacity of fuel cells can reach 200% of the rated power, which is very consistent with the dynamic performance characteristics of vehicles when accelerating and climbing. (2) Basically zero pollution in emission. The reactants of the hydrogen–oxygen fuel cell include only clean water and hydrocarbons, and the products include water, carbon dioxide, carbon monoxide, etc., belonging to the “ultra-low pollution”.

126

3 New Energy Vehicle Powertrain Technology Air compressor

Fuel cell pack

Motor control system

Fuel cell humidifier

Output current Air

Water pump Adsorption alloy hydrogen

Heat exchanger

Drive motor Super-capacitor

Fig. 3.33 Power system of fuel cell vehicle

Table 3.6 Fuel cell classification Classification basis

Fuel cell type

Electrolyte

PEM fuel cell, alkaline fuel cell, phosphoric acid fuel cell, solid oxide fuel cell, direct methanol fuel cell, regenerative fuel cell and protonic ceramic fuel cell

Fuel type

Hydrogen fuel cell, direct methanol fuel cell and direct ethanol fuel cell

Type of fuel used

Direct fuel cell, indirect fuel cell and regenerative fuel cell

Fuel state

Fluid type fuel cell and gas type fuel cell

Reaction mechanism

Acidic fuel cell and alkaline fuel cell

Operating temperature

Low temperature (< 200 °C), medium temperature (200–750 °C), high temperature (750–1000 °C), ultra high temperature (> 1000 °C)

(3) Long service life without vibration and noise. Due to the electrochemical reaction, there is no noise or vibration in the whole process, which can reduce the wear of mechanical devices and prolong the life. (4) Simple structure and stable operation. The energy conversion is completed under static condition, the structure is relatively simple, and the machining accuracy of the components is low. Comparatively, their disadvantages are mainly as follows: (1) Single fuel type and high safety requirements. Fuel is mainly hydrogen. The safety requirements are high for hydrogen production, storage, custody, transportation and filling.

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127

(2) High sealing requirement. The electrode connections between battery cells of the fuel cell pack must be tightly sealed; otherwise, the hydrogen leakage will reduce the utilization rate of hydrogen and seriously affect the efficiency of fuel cell engines, and will cause hydrogen combustion accidents. (3) High price. High manufacturing cost and high price of battery pack. (4) An auxiliary battery system is required. Auxiliary batteries are required typically for fuel cell vehicles to store the abundant electric energy of the fuel cells and the braking energy that is regenerated during the vehicle deceleration. Figure 3.34 shows the working principle of a fuel cell: In the first step, the hydrogen is introduced through the anode collector plate (bipolar plate) to the cathode and anode catalyst layers via the anode gas diffusion layer. Under the action of the anode catalyst, the hydrogen molecules are decomposed into positively charged hydrogen ions and release negatively charged electrons to complete the anodic reaction; in the second step, hydrogen ions cross the membrane to reach the cathode, and the electrons form a current in the external circuit, which can output electric energy to the load through appropriate connections; in the third step, at the other end of the cell, the oxygen passes through the cathode collector plate to the catalyst layer via the cathode gas diffusion layer. Under the action of the cathode catalyst, the oxygen reacts with hydrogen ions passing through the membrane and electrons from the external circuit to form water, completing the cathodic reaction; in the fourth step, most of the water generated by the electrode reaction is discharged from the tail gas, and a small part diffuses through the membrane to the anode under the action of pressure difference.

3.2.4 PEM Fuel Cell The PEM fuel cell is composed of a proton exchange membrane, a catalyst layer, a diffusion layer and a collector plate. The proton exchange membrane is not only a diaphragm material that separates the fuel at the anode from the oxidant at the cathode, but also the substrate of the electrolyte and the electrode active substance (electrocatalyst). In addition, the cell contains an electrocatalyst and a bipolar plate. The function of the electrocatalyst is to speed up the electrochemical reaction, at present, platinum catalyst is mostly used, and the gas diffusion electrode contains a certain amount of catalyst. The function of the bipolar plate is to separate the reactant gas, collect the current, connect single cells in series and provide a channel for the reactant gas to enter the electrode and for the discharge of water through the flow field. Figure 3.35 shows the principle of the PEM fuel cell. As shown in Fig. 3.36, the fuel cell stack is composed of 370 micro fuel cells with a total output of 114 kW. After more than ten years of technical optimization, Toyota’s fuel cell stack has developed its own features, such as 3D three-dimensional micro-channel technology, which effectively improves power generation efficiency by better discharging the water as a by-product and allowing more air to flow in. As

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3 New Energy Vehicle Powertrain Technology Battery cell

Hydrogen (From the hydrogen cylinder)

Excess hydrogen recovery

Catalyst

Electrolyte

Catalyst

Oxygen (From the air)

Generate electricity to drive the wheels

Water

Fig. 3.34 Working principle of fuel cell

Cooling channel

Gas channel

Anode collector plate Anode diffusion layer Anode cSatalyst layer

PEM Cathode catalyst layer Cathode diffusion layer Gas channel Cathode collector plate Cooling channel Fig. 3.35 Principle of PEM fuel cell

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129

Fuel cell booster

Fuel cell stack Toyota's first mass-produced fuel cell, with emphasis on miniaturization and high volume energy density output: 3.1kW/L Output power 114kW (155 HP)

Compact and efficient large-capacity booster, capable of increasing voltage to 650V

Power battery Nickel-manganese battery is used to recover the braking energy to assist fuel cells during acceleration

PCU Control the charging and discharging strategies of power batteries under different driving conditions

Drive motor The motor is powered by a fuel cell and a battery pack Maximum power 113kW (154 HP)

High pressure hydrogen storage The tank holds hydrogen for fuel, about 700 barometric pressures

Fig. 3.36 Toyota Mirai hydrogen fuel cell vehicle

a result, the power generation efficiency of the entire stack has reached the world advanced level 3.1 kW/L, an increase of 2.2 times compared to 2008.

3.2.5 Audi A7-H-Tron Hydrogen Fuel Cell Vehicle In full fuel cell mode, it takes about 1 kg of hydrogen to drive 100 km, while the hydrogen storage tank can store 5 kg of hydrogen at 700 barometric pressures, so a driving range of 500 km is theoretically easy. As shown in Fig. 3.37, a fuel cell stack is arranged in the engine compartment, an 8.8 kW·h lithium battery pack is arranged under the trunk, and a motor is arranged in the front and rear axles, respectively. This combination provides a total of 170 kW of power output, pushing the performance index of the fuel cell vehicle to the level of an SPEC vehicle.

3.3 BEV AMT Technology 3.3.1 Development Trend of Electric Vehicle Transmissions At present, electric vehicles are generally equipped with a single gear reducer. With the continuous development of technical routes and in-depth study on product applications, the electric vehicle transmissions are mainly developing towards high speed, multi-speed and integration.

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3 New Energy Vehicle Powertrain Technology

Hydrogen filling port

Hydrogen storage tank

Three-phase DC converter Power distribution unit Power electric air compressor High-pressure hydrogen delivery line Fuel cell Air inlet

Medium-pressure hydrogen Hydrogen recirculating pump

Air compressor

Steam exhaust pipe

Fig. 3.37 Audi A7-h-tron hydrogen fuel cell vehicle

1. High-speed electric vehicle transmissions In the Energy-saving and New Energy Vehicle Technology Roadmap published by China Society of Automotive Engineers in 2016, the overall roadmap of automobile manufacturing technology clearly puts forward the requirements for the reducer and transmission manufacturing technology, and gradually achieves the high speed target of the reducer and transmission speed reaching 16,000 r/min by 2030. At present, the European AVL has published engineering prototypes and prototype vehicles with the maximum motor speed up to 30,000 r/min. The maximum speed of the drive motors in the vehicles massed produced by Tesla and BYD has reached 16,000 r/min. 2. Multi-speed electric vehicle transmissions At present, the vast majority of battery electric passenger vehicles on the market use the single gear reducer for power transmission, without speed ratio transformation. The single speed ratio of single gear reducer is difficult to meet the optimal performance requirements under various conditions such as high speed driving, low speed driving, accelerating overtaking, ramp driving, braking energy recovery and driving range. The 2-speed or 3-speed ATMs can be installed in electric vehicles to better play the motor characteristics, reduce the motor torque demand, reduce the motor volume and weight, reduce the overall cost of electric drive assembly and improve the driving range of electric vehicles. Although the electric vehicles have good starting acceleration performance, the response speed is very slow when the vehicles speed up in the medium–high speed section of about 100 km/h. The 2-speed or 3-speed transmissions can be used to greatly improve the acceleration performance of electric vehicles at the medium–high speed stage.

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3. Electric drive system integration With the continuous development of new energy vehicle technology, component integration is also the trend of electric drive system development in the future. The integrated design can simplify the assembly in the main engine plant, improve the product percent of pass and the efficiency of installation and maintenance on the one hand and reduce the connection of wiring harnesses and other parts on the other hand, so as to achieve the purpose of lightweight and cost reduction. The three-in-one solution of “Motor + reducer/transmission + motor control unit” has become the current mainstream solution for electric drive system research and development.

3.3.2 Development of Two-Speed Automated Manual Transmission for Electric Vehicles The two-speed automated manual transmission for battery electric vehicles (2ETS for short) adopts parallel shaft structure, covering gear drive system, differential system, electronic parking system, synchronizer shift system, dual-motor actuator system, TCU and software control system. 2ETS can take into account the needs of climbing and acceleration at low speed, and meet the vehicle requirements at high speed. The working area of the motor can be adjusted through the speed ratio to make the motor work in the high efficiency area most of the time, which improves the vehicle system efficiency and reduces the cost of the motor and the control unit. With the design maximum input torque of 280 N·m and the design speed ratio of 4–12, the 2ETS reaches the efficiency more than 96%, the driving range increased by more than 5%, the maximum motor speed reduced by about 15%, and the overall dynamic performance increased by more than 20%, which can effectively improve the BEV powertrain performance. Figure 3.38 shows the all-electric 2ETS AMT with parking system developed by Professor Chen Yong’s team at the New Energy Vehicle Research Center, Hebei University of Technology. The gearshift employs the ball screw and synchronizer system driven by the motor, and is successfully used in the engineering prototype vehicles of self-owned brand. Table 3.7 shows the technical parameters of 2ETS AMT.

3.3.2.1

Vehicle Parameters

The main vehicle parameters of the electric vehicle equipped with 2ETS are shown in Table 3.8 and the performance requirements are shown in Table 3.9.

3.3.2.2

Transmission Arrangement

The power transmission route of a traditional vehicle with AMT is as follows: power source—clutch—transmission—differential mechanism—output shaft. Due to the

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3 New Energy Vehicle Powertrain Technology

Fig. 3.38 2ETS Table 3.7 2ETS technical parameters

Table 3.8 Main vehicle parameters of electric vehicle

Technical indicator

Design parameters

Maximum input torque

250 N·m/280 N·m (enhanced)

Drive mode

Front drive

Gear number

2

Speed ratio

Gear 1: 11.71; gear 2: 4.66

Shifting speed

Upshift: 70 km/h; downshift: 45 km/h

Total weight

≤ 33 kg

External dimension

Meet the requirements of vehicle layout

Transmission efficiency

≥ 96%

Control system

All-electric

Main parameters

Value

Vehicle test mass m/kg

1758

A/m2

2.19

Coefficient of air resistance CD

0.302

Tyre rolling radius r/m

0.310

Rolling resistance coefficient f

0.015

Rated battery voltage/V

353

Rated battery capacity/(A·h)

117.6

Frontal area

3.3 BEV AMT Technology Table 3.9 Main performance requirements of electric vehicle

133 Main performance

Value

Maximum speed (instantaneous)/(km/h)

≥ 150

Maximum speed (continuous)/(km/h)

≥ 120

0–100 km/h acceleration time/s

≤ 10

Maximum climbing slope at a constant speed of ≥ 30% 15 km/h 100 km power consumption under NEDC condition/(kW·h)

≤ 18

clutch limit, the motor torque cannot be too large at the vehicle starting stage in order to avoid clutch slip from extending the engagement time. In addition, the traditional ATM is not internally integrated with a differential mechanism and has high requirements for layout space. Figure 3.39 shows the structural layout of the new two-speed AMT. The transmission has no clutch and the vehicle can still start fast and smoothly at the starting stage under the condition of the large motor output torque. Moreover, the transmission is internally integrated with a differential mechanism that can directly output power to the left and right axle shafts, with compact overall layout and saving the layout space. In addition, because the clutch is removed, the output shaft of the motor and the input shaft of the transmission are normally connected. In the process of shifting, the motor can actively control the speed to reduce the shifting impact and increase the shifting speed. Fig. 3.39 Schematic diagram of new two-speed AMT

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3.3.2.3

3 New Energy Vehicle Powertrain Technology

Drive Motor Power Calculation

1. Calculation of the rated power of drive motor Equation during vehicle driving: Ttq i g ηt CD A 2 du a = mg f cos α + u a + mg sin α + δm r 21.15 dt

(3.1)

where T tq is the motor torque (N·m); ηt is the powertrain efficiency; ig is the total drive ratio of current year; ua is the vehicle speed (km/h), g is the acceleration of gravity; α is the climbing angle (°); δ is the correction coefficient of rotating mass. The electric vehicle shall meet the mutual balance of the above forces, but also meet the balance of power when driving. The rated power of the drive motor should meet the maximum speed requirements of the battery electric vehicle. Considering that the drive motor has a certain overload capacity, 90% of the maximum speed can be substituted to calculate the rated power, that is, the rated power shall satisfy: Pe ≥

  C D A(0.9u max )2 0.9u max mg f + 3600ηt 21.15

(3.2)

where umax is the sustained maximum speed (km/h). It is calculated from Eq. (3.2) that when the sustained maximum speed is 120 km/h, the rated power of the drive motor shall be greater than 21 kW. 2. Calculation of peak power of drive motor The peak power of the drive motor shall simultaneously meet the requirements of the instantaneous maximum speed, maximum climbing slope and acceleration performance of the electric vehicle. According to Eq. (3.2), the peak power Pmax_v ≥ 35 kW that satisfies the instantaneous maximum vehicle speed of 150 km/h can be obtained. The power demand of a battery electric vehicle when it completes the maximum climbing at a certain speed is Pmax _i

  C D Au i2 ui mg f cos αmax + mg sin αmax + = 3600ηt 21.15

(3.3)

where Pmax_i is the peak power (kW) to meet the requirement of maximum climbing slope; amax is the maximum climbing angle (°); ui is the climbing speed (km/h). The data are substituted to obtain Pmax_i ≥ 46.42 kW. The power demand of a battery electric vehicle when accelerating is Pmax _a =

  C D Au a2 du a ui mg f + + δm 3600ηt 21.15 dt

(3.4)

where Pmax_a is the peak power (kW) to meet the requirement of shortest acceleration time.

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135

Both sides of Eq. (3.4) are processed and integrated against time to obtain t=

1 3.6



ut

0

δm  Ft − mg f +

C D Au a2 21.15

 du

(3.5)

where F t is the driving force (N); ut is the final speed (km/h) of the acceleration process, which shall be 100 km/t according to the dynamic performance requirements; t is 100 km acceleration time (s). What calls for special attention is that the driving force F t is determined as a piecewise function by the characteristic of constant torque before the drive motor reaches the rated speed and constant power after the drive motor reaches the rated speed. That is  Ft =

3600 Pmaxu e_a ηt , u ≤ u e 3600 Pmaxu_a ηt , u > u e

(3.6)

where ue is the speed (km/h) corresponding to the rated speed of the drive motor. When the characteristics of the drive motor and the drive ratio of Gear 1 are unknown, the ue is also unknown. The drive motor has the highest efficiency when working near the rated speed, so it can be considered that the speed corresponding to the rated speed is the economic speed under urban road conditions. Accordingly, the range of ue is roughly 50–80 km/h. According to Eqs. (3.5) and (3.6), the relationship between the 100 km acceleration time at different peak power and the speed of Gear 1 corresponding to the rated speed of the motor is obtained. The rated speed of the motor is preliminarily selected as 3000 r/min, 3500 r/min and 4000 r/min. If the 100 km acceleration time of the electric vehicle is required to be less than 10 s, then Pmax_a shall be greater than 98.5 kW, 101.2 kW and 104.3 kW respectively. In summary, the peak power of the drive motor is taken as 100 kW, and the maximum motor speed is selected as 7200r/min according to the motor characteristics.

3.3.2.4

Drive Motor Characteristic Curve Fitting

Since the rated speed of the motor has a great influence on the peak torque of the motor, the three parameters, i.e. peak speed of 7200r/min, rated power of 42 kW and peak power of 100 kW, shall be kept unchanged, the rated speed of the motor is set to 3000 r/min, 3500 r/min and 4000 r/min respectively, and three groups of external characteristic curves of the motor are fit. The ideal external characteristic curves of the motor obtained by fitting are shown in Figs. 3.40, 3.41 and 3.42, respectively. The maximum output power of the motor reaches the peak power of 100 kW near the rated speed.

3 New Energy Vehicle Powertrain Technology

Maximum motor power/kW

Maximum motor torque/(N·m)

136

Motor speed/(r/min)

Maximum motor power/kW

Maximum motor torque/(N·m)

Fig. 3.40 External characteristic curve at 3000 r/min

Motor speed/(r/min) Fig. 3.41 External characteristic curve at 3500 r/min

3.3.2.5

Determination of Parameters of Drive Motor

The data of the fitted external characteristic curves are written into the motor module in AVLCruise software for dynamic simulation verification. The simulation results are shown in Table 3.10. The acceleration time of the drive motors with rated speed of 3000 and 3500 r/min is less than 10 s at the speed of 0–100 km/h. In order to meet the requirements of the vehicle climbing slope and 0–100 km /h acceleration time, and reduce the peak torque of the motor as much as possible, the rated speed of the motor is set to 3500 r/min, and the peak torque is set to 275 N·m. According to the rated output power of the motor at rated speed, the rated torque of the motor is calculated as 114.6 N·m, and the rated torque is 115 N·m. Therefore, the

137

Maximum motor power/kW

Maximum motor torque/(N·m)

3.3 BEV AMT Technology

Motor speed/(r/min) Fig. 3.42 External characteristic curve at 4000 r/min

Table 3.10 Comparison of dynamic performance of electric vehicle at three rated speeds Rated speed/(r/min)

3000

3000

4000

Acceleration time/s

9.50

9.65

10.13

Gear 1

89.37%

69.69%

57.46%

Gear 2

26.82%

22.76%

19.67%

Maximum climbing slope

Table 3.11 Drive motor parameters Motor parameters

Parameter value

Rated power/kW

42

Peak power/kW

100

Rated torque/(N·m)

115

Peak torque/(N·m)

275

Rated speed/(r/min)

3500

Peak speed/(r/min)

7200

specific parameters of the electric vehicle drive motor are preliminarily determined as shown in Table 3.11.

3.3.2.6

Matching of Drive Ratio of Two-Speed Transmission

1. Minimum total drive ratio in Gear 1 The minimum total drive ratio in Gear 1 should guarantee the maximum climbing slope required by the vehicle. According to Eq. (3.1), the minimum total drive ratio in Gear 1 is calculated as 8.637.

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3 New Energy Vehicle Powertrain Technology

2. Maximum total drive ratio in Gear 2 The relationship between the speed and the drive motor speed is u a = 0.377

nr i g i0

(3.7)

where ua is the vehicle speed; n is the drive motor speed; ig is the gear drive ratio; i0 is the reducer drive ratio. The maximum total drive ratio in Gear 2 should ensure that the vehicle can achieve the required maximum speed when the drive motor is operating at the maximum speed. According to Eq. (3.7), the maximum total drive ratio in Gear 2 is calculated as 10.702. The upper and lower drive ratio limits calculated based on dynamic performance constraints provide a basis for the subsequent simulation calculation based on economic performance optimization. 3. Preliminary determination of total drive ratio The AMT drive ratio shall be determined with consideration to compliance with the dynamic requirements of the vehicle, the practical problems encountered in engineering manufacturing and assembly as well as the impact on other components of the powertrain. The author summarizes the following points for design reference only: (1) The drive ratio in Gear 1 should not be too large to avoid excessive lubrication requirements due to the main reducer under excessive load, and to avoid frequent slippage of the drive wheel. (2) The inter-gear ratio should not be too small, otherwise the two-speed transmission cannot effectively adjust the speed of the drive motor, so that the operating point of the drive motor falls more in the high efficiency area, causing unnecessary energy loss. (3) The matching of the drive ratio determines the gear size and the number of teeth, and then affects the size of the transmission and the main reducer. Therefore, factors such as ground clearance and center distance of the main reducer should be considered. (4) The drive ratio in Gear 1 determines the maximum torque that the drive wheel can output, so it is necessary to consider the clutch friction plate, the maximum torque that the brake friction plate can transmit, the relative linear speed of the clutch and other factors. (5) The mechanical strength of each component of the whole powertrain should be considered comprehensively. The matching of the drive ratio is a process that needs repeated verification. Considering the above constraints, the total drive ratio in Gear 1 is preliminarily determined in the range of 8.28–14.28, and the total drive ratio in Gear 2 in the range of 3.14–6.14. We will optimize the drive ratio value in this range subsequently.

3.3 BEV AMT Technology

3.3.2.7

139

Parking Mechanism Design

In the parking mechanism, the drive motor drives the actuator to complete the parking and disengagement. The mechanical actuator is mainly composed of the ratchet, pawl, sliding block, push rod, guide pin and pressing block. The motor fork drives the push rod forward and backward through the sliding block, and the push rod presses the pressing block between the pawl and the guide pin to complete the parking action. The whole mechanism relies on the push rod spring to realize the flexible locking of the pawl and the ratchet, and uses the torsion spring to realize the mutual disengagement of the pawl and ratchet. In order to meet the safety requirements of low speed safe parking, reliable self-locking and avoid abnormal parking, the electric parking mechanism has been studied, as shown in Fig. 3.43. The rigid-flexible coupling dynamic model of the parking mechanism is established and analyzed by using the multi-body dynamics software Adams. As a safety device, the parking mechanism needs to meet the following performance requirements: vehicle rolling distance not exceeding 80 mm during ramp parking; reasonable safe parking speed; it can lock the vehicle on the slope of 30%, and can disengage from P gear smoothly; abnormal parking is not allowed. The dynamic simulation analysis model established by Adams is shown in Fig. 3.44. 1. Simulation of critical parking speed The dynamic simulation environment provided by Adams is used to set the initial state and the action to be executed for the simulation model. The STEP function is used to give the ratchet an angular acceleration, and set a sensor. When the ratchet

Motor

Pawl

Ratchet Sliding block

Push rod

Guide pin

Briquetting

Fig. 3.43 Schematic diagram of parking mechanism

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3 New Energy Vehicle Powertrain Technology

Fig. 3.44 Dynamic simulation analysis model

speed is equivalent to the speed of the vehicle running at 6 km/h, stop acceleration, and apply the drive at the fork and simulate the parking action. When the pawl and the ratchet are locked and the ratchet stops rotating, the simulation ends. The critical parking speed is at the step of the pawl speed curve. As shown in Fig. 3.45, the ratchet does no longer accelerate when it reaches the required speed, and the speed remains stable when the locking clearance is eliminated. After the ratchet starts to contact the pawl, the ratchet speed decays unevenly due to the different energy loss in each collision. At 0.48 s, the ratchet speed drops sharply, and then fluctuates to a certain extent, indicating that the parking has been completed. The angular speed of ratchet at 0.48 s is 659.8 (°)/s, and the critical parking speed is calculated as 3.4 km/h, meeting the design requirements.

Angular speed/( (°)/s)

2. Simulation of self-locking performance

Time/s Fig. 3.45 Ratchet angular speed

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141

When the ratchet engages with the pawl and the parking mechanism is kept in the parking state, a torque is applied on the ratchet, which is equivalent to the torque generated at the shaft of the ratchet when the vehicle is parked on a slope of 30% with gross vehicle mass (GVM). As shown in Figs. 3.46 and 3.47, the torque curve remains stable after reaching the desired value, and the pawl angle can be neglected. It can be seen that the actuator bears the torque and is not disengaged, meeting the self-locking performance requirements. In the subsequent simulation, the torque value is increased, and the safety factor of ramp parking is determined to be 2.8. 3. Simulation of disengagement performance

Angle/(°)

Torque/(N•mm)

When the vehicle is parked on the ramp and put into P gear, it will move a short distance to eliminate the clearance between the pawl and the ratchet. The vehicle stops moving when the ratchet contacts the pawl and a torque that stops the vehicle from moving is generated. In some cases, it is the contact force between the ratchet and the pawl that prevents the parking mechanism from be disengaged smoothly. The simulation of disengagement performance is to verify whether P gear can be disengaged smoothly when needed.

Time/s

Angle/(°)

Torque/(N•mm)

Fig. 3.46 Simulation of self-locking performance under uphill conditions

Time/s Fig. 3.47 Simulation of self-locking performance under downhill conditions

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3 New Energy Vehicle Powertrain Technology

When the simulation vehicle is parked on a ramp of 30% slope with GVM, the pressing block and push rod are withdrawn to observe whether the pawl can be disengaged from the ratchet smoothly under the action of the torsion spring. As shown in Fig. 3.48, at 0.2 s in the uphill condition, the contact force rapidly drops to 0 after a small fluctuation, and the pawl pops out quickly; similarly, at 0.21 s in the downhill condition, the pawl is disengaged from the ratchet, as shown in Fig. 3.49. Simulation results show that the disengagement performance meets the requirements. 4. Simulation of parking impact force under motion state

Angle/(°)

Force/N

The main purpose of simulation analysis of the parking impact load at different vehicle speeds is to understand whether the parking mechanism will be damaged at high speed parking, so as to provide reference for design and test. As shown in Fig. 3.50, from the simulation, the larger impact load appears in at the low speed below 10 km/h and high speed above 60 km/h. At low speed, due to low ratchet speed, the overlapping area covered by the respective movement trajectories of the pawl and the ratchet will be relatively large, that is, more parts of the pawl go

Time/s

Angle/(°)

Force/N

Fig. 3.48 Simulation of disengagement performance under uphill conditions

Time/s Fig. 3.49 Simulation of disengagement performance under downhill conditions

3.3 BEV AMT Technology Ratchet and pawl

Peak impact load F/N

Fig. 3.50 Relationship between impact load and vehicle speed

143

Pawl and sliding block Sliding block and pin

Vehicle speed v/(km/h)

deep into the ratchet, and the part in contact with the ratchet changes from the fillet of the pawl to the plane above the rounded corner, and the impact arm becomes shorter, so the impact force is larger; at the medium–low speed, with the increasing ratchet speed, the overlapping area covered by the two trajectories decreases rapidly, the area of the pawl going deep into the ratchet decreases greatly, and the corresponding impact force decreases; at the high speed, the increase of speed will lead to the increase of impact force, which is more obvious after 30 km/h. The above peak impact loads are all within the design safety range with a safety factor of 2.

3.3.2.8

Synchronous Shift Performance

Based on the two-speed fully electronic AMT for battery electric vehicles, a theoretical analysis model of synchronizer system dynamics is established, and the influence of different speed differences before and after speed control on the synchronization time of upshift and downshift compared, so as to provide theoretical basis for the shifting strategy of battery electric vehicles. Compared with internal combustion engine, the motor has the characteristics of high speed, low speed and constant torsion. The speed ratio range of the matched two-speed fully electronic transmission is wider than that of the AMT, causing that the speed difference between the active end and the passive end of the synchronizer at the time of upshift and downshift is several times than larger that of the transmission for ICEV. Taking the upshift when the vehicle speed increases to 70 km/h, and downshift when the speed decreases to 45 km/h for example, the speed difference of the synchronizer is as high as 3500 r/min in upshift, and 897 r/min in downshift. This is determined by the transmission structure and gear ratio parameters. The equivalent moment of inertia at the active end of the synchronizer is 0.0617 kg·m2 in upshift, and 0.5707 kg·m2 in downshift, which is 9.24 times of the moment of inertia in upshift. When the motor is not involved in speed control during the shift process, take the shift force of 500 and 1000 N for example to calculate the upshift and downshift synchronization time. The results are shown in Fig. 3.51.

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Upshift

Downs

Fig. 3.51 Synchronization time for different shift forces

When the shift force is 500 N, the upshift synchronization time is 0.86 s, and the downshift synchronization time is as high as 3.38 s, both exceeding the maximum recommended synchronization time of 0.25 s. Even when the shift force is increased to 1000 N, the synchronization time cannot fall to an acceptable range. It can be seen that when the motor is not involved in the speed control, the upshift and downshift synchronization time is too long, especially in the case of downshift, which will cause excessive sliding work and shift impact, shorten the life of the synchronizer, seriously affect the quality and comfort of shift. Therefore, during the shift, the motor needs to be actively involved in regulating the speed of the active end of the synchronizer. Figure 3.52 shows the synchronization time under different gear shift forces with different speed differences during upshift and downshift. In the case of upshift, the gear ring speed of the synchronizer is greater than the gear hub speed, the friction moment and the trailing moment are in the same direction, the equivalent moment of inertia is small, and the requirement for the speed difference is relaxed. In the case of downshift, the gear ring speed of the synchronizer is less

Fig. 3.52 Relationship between the shift synchronization time and speed difference, shift force

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than the gear hub speed, the friction moment and the trailing moment are in different positions, the equivalent moment of inertia is large, and the requirement for the speed difference is strict. The sliding friction work W is the work done by the friction moment of the synchronizer, which is an indicator of the synchronizer life.  W =

t

TR ||ω1 − ω2 ||dt

(3.8)

0

where T R is friction moment; ω1 -ω2 is speed difference. The sliding friction work can be effectively reduced by adjusting the speed difference. Impact degree J is an important index to evaluate the shift quality, and its magnitude is expressed by the change rate of vehicle longitudinal acceleration. J=

dF j d(Ft − Fw − F f ) da = = dt δm · dt δm · dt

(3.9)

where F j is acceleration resistance; F t is driving force; F w is air resistance; F t is rolling resistance; δ is correction coefficient of rotating mass. The impact degree depends on the rate of change of the driving force, that is, the rate of change of the motor torque. By controlling the recovery of the motor torque, the impact degree can be changed to improve the shift comfort. Figure 3.53 shows the shift logic. From the above analysis, it can be seen that the motor direct drive two-speed transmission system needs to reduce the speed difference to compensate for the increase in the moment of inertia. The shift force and speed difference can be coordinated to shorten the synchronization time, effectively improve the shift performance, and prolong the synchronizer life. The torque control can reduce the shift impact and improve the shift comfort.

3.3.3 Two-Speed AMT Control Technology 3.3.3.1

Electric Control System Architecture

The topology of the control system of the two-speed transmission is shown in Fig. 3.54. The Vehicle Control Unit (VCU) is responsible for receiving/sending signals of the vehicle electric control system through the controller area network (CAN), such as receiving the accelerator pedal position signal, brake pedal position signal, ABS_ESC (ECP) signal, etc. The shift knob button signal is collected by EGSM controller and sent to VCU through CAN. The shift control strategy is also typically built into the VCU; TCU (transmission control unit) is responsible for responding to the torque and speed request of the drive motor and controlling the

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Speed mode

Shift command No

Is the target speed reached?

TCU requests motor control

Yes Sliding friction synchronization

No TCU takes control of the motor

No Is it synchronized?

Yes Torque mode

Yes Engage the gear

Adjust the motor torque according to the set torque curve No

No Is the gear engaged?

Is the target torque reached? Yes Yes Control the motor in Disengage the gear

torque mode No

No Disengage successfully

Is the torque recovered?

Yes

Shift end

Fig. 3.53 Shift logic

shift actuator; MCU (drive motor control unit) is mainly used to drive the motor. BMS is the battery management system. ABS and BMS are located in the VCAN (vehicle CAN); MCU (IPU/PEU) and TCU (PCU) are located in EVCAN (power CAN); VCU has two channels of CAN, one in VCAN and one in EVCAN.

3.3 BEV AMT Technology

Transmission control unit

Vehicle control unit

147

Motor control unit

Battery management system

Anti-lock braking system

Fig. 3.54 Control system topology

3.3.3.2

TCU Hardware

TCU is the core component of the AMT control system. Its control quality directly determines the dynamic performance, economy and smoothness of the vehicle, and also has a great impact on the vehicle safety. Therefore, it is the core technology in the field of powertrain control, and the emergence of new energy vehicles has injected new vitality into its development. At present, the TCU functions are realized through the universal Rapid Control Prototype (RCP), and the parameters are shown in Table 3.12. The RCP simulation is at the second stage of the control system development, long before product development, so that the new control ideas of designers can be easily and quickly tested on real-time hardware. With real-time testing, designers can find the problems early in the design process to modify the prototype or parameters before real-time testing. This is repeated, and eventually a reasonable and feasible control prototype is produced that is fully oriented to the user requirements. The RapidECU can replace the real controller hardware in the development process of the electric control system. Through the automatic code generation technology, the control algorithm model formed at the MATLAB/Simulink modeling and simulation stage is downloaded into the RCP hardware, and connected to the actual controlled object to perform the HIL simulation verification of the control algorithm and to achieve the calibration early in the development stage. RapidECU hardware core adopts Freescale MPC55xx, MPC56xx, S12x/S12 and other series of microprocessors, and the hardware design meets the automobile grade standard. The RCP can be developed and verified for control algorithm in advance without controller hardware, which is especially suitable for the development and research of new products and models. The RCP test results can also provide reference for hardware design. Therefore, the RCP also reduces the hardware rework probability in the rapid software verification, which can greatly shorten the development cycle, reduce/eliminate the possible errors and defects in the early development to save the cost and reduce material consumption and improve the control unit design quality.

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Table 3.12 RCP parameters Basic parameters Host processor

MPC5554, 32-bit, basic frequency 80 MHz, hardware floating point unit

Storage space

Flash 2 MB, SRAM 64 KB

Supply voltage

9–32 V, peak voltage 40 V

Circuit protection

All the input and output interfaces are provided with relative short-circuit protection and the short-circuit protection for the battery positive terminal, and the power interface is protected by the main relay

Program flash

CAN bus-based Bootloader online flash

Standardization

ASAP2 standard CCP protocol

Power supply and communication Sensor power supply

2-channel 5 V, 50 mA and 100 mA 1 channel programmable, 0–5 V, 300 mA 1 channel programmable, 0–10 V, 300 mA

Communications

3-channel CAN, CAN2.0B, ISO11898

Input Voltage input

15 channels, 8 channels 0–5 V, 7 channels configurable

Resistance input

6-channel NTC/PTC

Circuit protection

20 channels, of which, 10 channels configured as active high, 2 channels configured as active low and 8 channels configured as active high or active low

Frequency input

16 channels, of which, 8 channels with magnetoelectric sensor signal (sine wave signal) and 8 channels with Hall sensor signal (square signal)

Output PWM power drive

4-channel rated 2.9 A, peak 8 A, compatible with the switch working mode and PWM working mode (1) 8-channel rated 1.8 A, peak 3 A, compatible with the switch working mode and PWM working mode (1)

Relay drive

Up to 17 relay drives, switch operating mode

DC motor drive

3 channels, rated current 15 A, maximum operating current rating 25 A (2)

Constant current drive

4 channels, rated current 3 A, current feedback (3)

Analog output

2-channel analog output, 0–10 V (4)

Physical properties Enclosure

Material aluminum, external dimensions 200 mm × 180 mm × 30 mm

Connector

121-pin AMP connector

Weight

500 g

Operating temperature

− 40 °C to + 85 °C

Protection level

Dustproof and waterproof level IP65, climatic environment protection conforming to ISO16750-4, chemical environment protection conforming to ISO16750-5 (continued)

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149

Table 3.12 (continued) Basic parameters Mechanical strength

3.3.3.3

Vibration, impact and drop tests conforming to ISO16750-3

TCU Control Model

The vehicle control strategy is a kind of software control logic determined by many factors, such as system function requirements, user driving and using habit and design experience. With the model-based development mode and on the platform of MATLAB/Simulink/StateFlow software, the TCU control system is subject to the functional verification, RCP design and other basic work in the early development. The AMT electric control system development technology needs to achieve the functions such as best gear selection, shift process automatic control, driver misoperation avoidance and warning, starting self-learning control, fault mode limping, retarder automatic control and safety protection. In addition to meeting the above functional requirements, TCU for new energy vehicles also needs to be equipped with functions such as integrated control of powertrain, clutchless shift control, coordinated mode switching control and calculation of optimal gear for hybrid system.

3.3.3.4

Calibration Software

MeCa and CANape are used as calibration software. MeCa, as a universal ECU measurement and calibration tool, can collect and display the internal data of the ECU in real time, and adjust the internal parameters of the ECU online. In addition, it also provides automatic measurement and calibration functions, ECU program flash and upgrading functions. MeCa realizes the communication between the upper and lower computers through the standard protocol, supports the calibration protocol CCP based on CAN, and provides a full graphical user interface and a variety of graphical controls, which can display various types of measurement data and adjust the calibration parameters. CANape is a comprehensive tool for ECU development, calibration, diagnosis and measurement data acquisition, mainly for electric control unit parameter optimization (calibration). It calibrates parameter values and collects measurement signals simultaneously during system operation. The physical interface between CANape and ECU can be CAN bus using CCP (CAN calibration protocol) or FlexRay using XCP protocol. In addition, CANape provides symbolic access to diagnostic data and diagnostic services through an integrated diagnostic feature set. In this way, it can achieve the full diagnostic tester functions.

150

3.3.3.5

3 New Energy Vehicle Powertrain Technology

Control Strategies to Improve Shift Time and Impact

In order to improve the shift time and impact, the control strategy with the service time shall be used during gear disengagement, and there is a coupling relation between the shift time and impact during shift engagement, so the integrated control strategy shall be considered. 1. Disengagement control strategy The control object of the shift process is motor controlled shift actuator, which is composed of the DC motor, ball screw, shift rocker arm and angular position sensor. The input quantity is the driving voltage, and the output quantity is the angular displacement of the shift rocker arm, namely the signal value of the angular position sensor. The corresponding relationship between the input and output quantities is as follows:    2  d α dα + K (3.10) F U = (K 1 + K 2 cos2 α) + K3 4 z dt dt 2 where K 1 , K 2 , K 3 and K 4 are constants related to the mechanical structure of the motor and actuator; a is the angular displacement of the shift rocker arm; F z is the shift resistance. According to Eq. (3.10), it can be seen that the change law of the synchronizer clutch position is related to the terminal voltage and shift resistance of the actuator. The duty cycle signal size can be changed by PWM to realize the control of the actuator. The gear disengagement process shall be controlled within the shortest time, so 100% duty cycle shall be applied to the shift motor and the drive torque of the drive motor shall be reduced to 0 to minimize the gear disengagement resistance. 2. Speed control and gear engagement control strategy The mark of gear disengagement completion and speed control is generally that the synchronizer clutch is located in the “absolute” neutral position, i.e., the midpoint position of the line of the shift axis stroke. The neutral range is from the position where the synchronizer clutch is separated from the soldered tooth ring of the current gear to the position where it is about to engage with the soldered tooth ring of the target gear. In terms of the drive motor, the synchronizer clutch shall enter the speed control mode immediately after it enters the neutral range, so that the speed difference between the synchronizer clutch and the soldered tooth ring can be controlled in a reasonable range. In terms of the synchronizer clutch, because there is no synchronizer structure, the synchronizer clutch shall enter the pre-engagement state after being disengaged from the soldered tooth ring of the current gear, that is, run to the position about to contact with the soldered tooth ring, and wait for the drive motor to complete speed control. There are two reasons to enter the pre-engagement state: one is to reduce the total gear stroke after speed control and shorten the engagement time; the other is

3.3 BEV AMT Technology

151

Drive motor speed control range

Braking and waiting speed control range

In the gear

In the gear (a) General neutral range Tooth surface separation interval

Drive motor speed control range

Braking and waiting engagement interval

In the gear

Tooth surface contact interval

In the gear (b) Redefined neutral range

Fig. 3.55 Comparison of neutral ranges in different strategies

to shorten the acceleration distance of the synchronizer clutch driven by the shift force, reduce the axial speed of the synchronizer clutch at the instant of contact with the soldered tooth ring and reduce the engagement impact force. Compared with the general strategy of gear disengagement—neutral gear and speed control—speed control completion—gear engagement from neutral gear, the redefined strategy of speed control in neutral range improves the coincidence degree of the running time of the synchronizer clutch and the active speed control time of the drive motor. Figure 3.55 shows the comparison of the neutral ranges of the two speed control strategies. Since there are four working conditions in the fillet surface contact, the drive motor shall be made to operate in free mode to reduce the engagement resistance in order to shorten the engagement time. The impact force during engagement is related to the axial relative speed and circumferential relative speed of the synchronizer clutch and the soldered tooth ring. By redefining the neutral range, the running speed of the synchronizer clutch can be improved, therefore, in order to shorten the engagement time, similar to the case of gear disengagement, the gear shift process also needs full duty cycle drive to achieve the purpose of optimal shift time. To sum up, the entire shift control strategy is shown in Fig. 3.56. 3. Control method based on position identification and correction The key point of control is to make the actuator drive the synchronizer clutch to quickly and accurately stop in the engagement waiting interval. Usually, the calibration curve is used to control the actuator. The corresponding curve of the voltage U and position signal x of the shift motor is established and shall be corrected and calibrated through several tests. Therefore, we have designed an actuator control

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3 New Energy Vehicle Powertrain Technology

Shift end

Shift start

Yes The drive torque is 0 Engaged in target

No Disengage the gear Engagement with full duty cycle

No Separation of synchronizer clutch and the soldered tooth ring?

Free mode of drive motor

Yes Speed control mode of drive motor

The target speed difference has been reached Pre-engagement, synchronizer clutch runs to the engagement waiting interval

The actuator is decelerated by electric braking

Yes

No

Has the actuator stopped?

Fig. 3.56 Shift control strategy process

method based on position identification and correction, and the control logic is shown in Fig. 3.57. The internal parameters of the position identification module include the drive position interval, the braking position interval and the allowable position accuracy

Voltage drive Target position

Position

Electric braking

Actual position Actuator

identification Precision correction

Fig. 3.57 Control logic based on position identification and correction

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153

interval. In this control method, the position identification module receives the target position signal and the signal difference between the target position and the actual position, and sends a drive request to the voltage drive module; when the actuator reaches the braking interval, it sends a short and plug braking request to the brake module; after the braking is completed, if the signal difference between the actual position of the actuator and the target position is not within the allowable accuracy range, the actuator will send a correction request to the accuracy correction module. The internal parameter of the voltage drive module is the duty cycle curve; the internal parameters of the braking module are short braking and plug braking curves; the PI controller is inside the accuracy correction module to correct the position deviation. After the correction, the accuracy correction module sends the parameters to the position identification module and corrects the drive position interval and braking position interval parameters.

3.3.3.6

Analysis of Simulation and Test Results

In order to verify the effect of reducing the axial velocity of the synchronizer clutch at the gear engagement stage on the axial impact force during the fillet surface collision, as shown in Fig. 3.58, a synchronizer-free gear shift model is established in the AMESim simulation platform, and the relevant parameters are shown in Table 3.13. In order to verify that the shift control strategy can quickly complete the shift process in a short time and to verify the effectiveness of the actuator control method, a shift test is carried out on the test bench. The principle of the shift test bench is shown in Fig. 3.59. The test bench consists of the HVDC source, real vehicle powertrain, flywheel set of equivalent moment of inertia, dynamometer and corresponding control units, and upper computer. The control program is written using MATLAB/Simulink, and flashed with the RCP to realize the TCU function. The

Fig. 3.58 AMESim synchronizer-free gear shift model

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3 New Energy Vehicle Powertrain Technology

Table 3.13 Simulation parameters

Parameter

Value

Type of shift motor

12 V DC brush

Screw diameter, lead/mm

16.00/2.00

Total mass of fork—synchronizer clutch/kg

0.22

Equivalent moment of inertia at synchronizer clutch end/(kg·m2 )

11.80

Equivalent moment of inertia at soldered tooth end/(kg·m2 )

0.27

Initial speed difference/(r/min)

10.00

Width of soldered tooth/mm

2.6

Included angle of soldered tooth/(°)

43

Contact stiffness of soldered tooth/(N/m)

1 × 106

MeCa is used as the parameter calibration system for the upper computer and dSPACE is used as the signal acquisition system. The actual bench is shown in Fig. 3.60. 1. Analysis of simulation results Figure 3.61 shows the changing curve of the synchronizer clutch displacement, synchronizer clutch speed, soldered tooth speed, axial impact force and shift motor current in the gear engagement process when the speed difference is controlled at 10 r/min and the duty cycle is 100%. The original curve is the run curve of the synchronizer clutch driving the engagement with full duty cycle starting from the Mechanical and electrical connections Signal communication

HVDC source Shift actuator

Motor control unit

Drive motor

Transmission

Dynam ometer Freewheel set

Fig. 3.59 Principle of shift test bench

Wheel

3.3 BEV AMT Technology

155

Fig. 3.60 Physical shift test bench

neutral position; the optimized curve is the run curve that the synchronizer clutch stays in the waiting interval after electric braking according to the contract strategy before engagement. Among them: the original shift time is 69 ms and the optimized shift time is 71 ms, extended by 2.90%; the original instantaneous speed at the shift engagement is 219.46 mm/s, and the optimized speed is 146.87 mm/s, reduced by 33.08%; the maximum impact force of the original gear engagement is 6019.99 N, and the optimized impact force is 4796.34N, reduced by 20.33%. In conclusion, on the premise of that the engagement time is hardly affected, this control strategy effectively reduces the running speed of the synchronizer clutch in the gear engagement process and effectively reduces the maximum axial impact force. 2. Test results and analysis Figure 3.62 shows the initial shift curve a of the synchronizer clutch position in the shift process and the shift curve b after self-correction using the control method. It can be seen from curve a that the synchronizer clutch starts to run under the full duty cycle drive of the actuator after gear shift. Due to the inaccurate setting of the drive interval and braking interval, the electric braking process is completed at 0.624 s; as the accuracy requirements are not met, the accuracy correction module works to make the synchronizer clutch continue to run to the engagement waiting interval, wait for the completion of the drive motor speed control, which takes 275 ms; it takes 140 ms to engage the gear after reaching the target speed range, and 471 ms to shift the gear. After many shift corrections, the shift curve is shown in curve b, and the accuracy correction module is no longer involved in the gear disengagement and pre-engagement process. The full duty cycle drive and electric braking can quickly and accurately complete the shift process. It takes 128 ms for gear disengagement and pre-engagement and 151 ms for gear engagement. The total time is 463 ms. After many shift corrections by the accuracy correction module, the time of gear disengagement is reduced by 53%.

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3 New Energy Vehicle Powertrain Technology

Fig. 3.61 Improvement of shift process by control strategy

Displacement/mm

Original curve

Current/A

Impact force/N

Rotational speed

Speed/(m·s-1 )

After optimization

Time/s

Although curve a shows that too much time is consumed in the gear disengagement stage, and the speed control time is approximately equal to curve b, the redefined neutral speed control interval strategy of the drive motor greatly improves the coincidence degree of the running of the actuator and the speed control time of the drive motor, ensuring that the difference between the total shift time and curve b is less than 2%. The reason for the difference between curve a and curve b in the gear engagement stage is the randomness of the contact between the synchronizer clutch and the fillet surface of the soldered tooth ring. When the shift motor is driven by the full duty cycle, the time difference in the gear engagement process is only 7%, and the influence is not significant. In conclusion, the shift strategy can effectively reduce the shift time and realize the fast shift process of AMT without synchronizer.

Fig. 3.62 Shift test results

Position sensor signal/mV

3.4 High-Strength Component Technology of Vehicle Powertrain

Speed control range

157

Target position Actual position

Time/s Position sensor signal/mV

(a) Initial shift curve

Speed control range

Target position Actual position

Time/s (b) Shift curve after completion

3.4 High-Strength Component Technology of Vehicle Powertrain 3.4.1 Vehicle High-Strength Gear Technology Gear is an important core component in the vehicle powertrain and other mechanical devices. In recent years, with the development of modern vehicles and new energy vehicles, military vehicles, ships, aerospace vehicles, high-speed railway facilities and other technologies, the powertrain further requires gears with high strength, high speed, high efficiency, long life, lightweight, miniaturization and other characteristics. This not only raises a new topic for gear design, but also brings new research and development tasks for the development of new material and innovative material processing technologies, among which, the surface strengthening technology is the key to ensure high performance of gear. At present, China is lagging far

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behind Europe, America, Japan and other countries in high-intensity gear design and manufacturing technology, especially in the strength and service life of the parts of high-grade auto and machinery products, which has restricted the development of the AMT and other high-end electromechanical equipment in China. Therefore, it is imperative to improve the strength of high-end gears comprehensively. The research practice shows that, to improve the fatigue strength life limit of gears, it is necessary to improve the alloy composition of materials, improve the carburizing and carbonitriding heat treatment techniques and combine with the R&D of the surface strengthening treatment of gears, that is, to achieve comprehensive gear surface integrity and get better gear fatigue resistance, so as to achieve high performance requirements for the high-strength gear contact fatigue limit, bending fatigue limit, fatigue endurance life and best friction coefficient. In recent years, in order to develop new markets, the automobile companies are constantly improving the guaranteed mileage. Many of the world’s most famous automobile companies have increased the guaranteed mileage of passenger vehicles to more than 340,000 km, and of commercial vehicles to more than 1 million kilometers. To achieve this performance index, the automobile companies in the United States, Japan, Europe and other countries have put forward more stringent market requirements, intensified the research on improving the gear fatigue strength life, carried out in-depth research and development from the perspective of multi-factor comprehensive indexes, mainly including the analysis and optimization of gear alloy materials, optimal heat treatment technique of gear and gear surface strengthening technology such as manganese phosphate conversion coating, compound tooth surface shot peening, tooth surface shot peening with molybdenum disulfide and particles, and has achieved good practical effect in the application of automatic and manual transmissions.

3.4.1.1

Automobile Gear Material Technology and Research Status

1. Automobile gear materials at home and abroad and gear process parameters The modulus is an important parameter of gear. The strength, noise, light weight and processing technology should be considered to select the automobile gear modulus. Table 3.14 shows the commonly used moduli and diameters of gears for passenger vehicles and commercial vehicles. In the process of torque transmission and speed change, automobile gears are usually in the working environment of high speed, high load and alternating impact load. Table 3.14 Range of moduli and diameters of gears for vehicles Gear type

Passenger vehicle

Commercial vehicle

Shaft gear

Disk gear

Shaft gear

Disk gear

Modulus/mm

1.25–5

1.25–4

3–5

2.5

Diameter/mm

30–120

50–200

60–150

80–250

3.4 High-Strength Component Technology of Vehicle Powertrain

159

The automobile gear materials not only need to have good machining properties and heat treatment carburizing and quenching properties, but also need to meet the reasonable cost requirements. In order to ensure the stability of tooth surface and tooth crest quenching depth, the low carbon alloy steel with a carbon mass fraction of about 2% and added with Ni, Cr, Mn, Mo and other alloying elements alone or in combination is usually selected. Japan and Germany have made long-term research and development in the field of low carbon alloy steel materials of high strength gears for vehicles. Table 3.15 shows the ingredients of alloy steel gear materials commonly used in automobiles. At present, the main types of steel used for automobile gears at home and abroad are 20CrMnTi (domestic), 20MnCrS (German) and 20CrMoH (Japanese). Steel types A, B and C in the table are high fatigue steels. 2. Gear failure mode and damage mechanism Understanding the gear failure form and damage mechanism can provide more explicit guidance for the gear surface strengthening. The automobile gears are in the state of continuous load work, there are both rolling and sliding between the gear meshing surfaces, and the tooth root is also affected by pulse and alternating bending stress. There are typically four different gear failure modes: ➀ Tooth breakage; ➁ Macro-pitting/micro-pitting; ➂ Wear; ➃ Tooth surface gluing. Figure 3.63 shows the gear damage failure position model. Most of the gear failure modes above originate from the surface of the tooth surface or root. It can be seen that the gear surface is very important. Gear surface integrity refers to the condition of an undamaged or hardened surface and its determined properties, including surface residual stress, microhardness, surface roughness, microstructure, etc., as well as thickness and bonding strength for the gear surface coating modification. Both surface chemical heat treatment and shot peening deformation strengthening will affect the gear surface integrity such as surface roughness, morphological characteristics, texture, hardness and residual stress. The gear surface integrity is closely related to bending fatigue resistance and contact fatigue resistance. 3. Study on bending fatigue damage mechanism and materials Gear strength mainly refers to the bending fatigue strength of gear and the contact fatigue strength of tooth surface. As shown in Fig. 3.64, the main cause of gear bending and fracture is that the gear root is subject to repeated concentrated stress and has cracks generated and gradually expanded to failure. The bending fatigue crack originates from the grain boundary oxide layer on the surface of the gear and extends along the austenite grain boundary below the surface to the depth of the hardened layer, thus causing the failure of the grain boundary. The grain boundary oxide layer on the surface of the material is mainly composed of Si, Mn, Cr and other alloying elements that can improve the quenching performance. The grain boundary edge is prone to local incomplete quenching areas, forming an incomplete carburizing abnormal layer composed of troostite and bainite. Figure 3.65 shows the grain boundary oxide layer texture after carburizing and quenching of the 20CrMoH sample. The black whisker components extending from the surface to the interior are

0.17–0.22

0.20

0.17

0.19

0.18

20MnCrS (Germany)

Steel A

Steel B

Steel C

20MnCrS (domestic imitation)

20CrMoH (Japan)

0.17–0.23

0.17–0.22

20CrMnTi (China)

C

Sample type

1.1–1.4

0.72

0.50

0.07 0.30

0.31

0.87

0.73

≤ 0.4 0.25

0.80–1.10 1.10–1.50

0.17–0.37

Mn

≤ 0.25

Si ≤ 0.035

0.006

0.006

0.060

0.030

≤ 0.025

0.018

0.018

0.012

0.030

0.02–0.04

0.02–0.04

≤ 0.035 ≤ 0.025

S

P

–

–

0.01

–

–

–

≤ 0.030

Cu

–

–

0.03

–

–

–

≤ 0.030

Ni

1.43

2.11

0.95

1.05

1–1.3

1.00–1.30

1.00–1.30

Cr

Table 3.15 Mass fraction of each component of alloy steel gear materials commonly used in automobiles at home and abroad (%)

0.44

0.41

0.39

0.20

–

–

–

Mo

–

–

–

–

–

–

0.04–0.10

Ti

160 3 New Energy Vehicle Powertrain Technology

3.4 High-Strength Component Technology of Vehicle Powertrain

161

Meshing direction Pitting Tooth crest Wear scratch

Gear trajectory Tooth root Pitting

Wear scratch

Fig. 3.63 Gear damage failure position model

the oxides of Si, Mn and Cr. To improve the gear bending fatigue strength, it is usually necessary to increase the R angle of the tooth root, high pressure angle and adopt the carburizing and quenching or carbonitriding heat treatment, shot peening and other surface treatment techniques. For example, the quenching speed can be generally used to improve incomplete carburizing anomaly. However, attention should be paid to avoid large tooth surface deformation, or increase Ni, Mo and other alloying elements that are beneficial to improving the quenching performance while reducing the content of the elements such as Si, Mn and Cr. 4. Study on contact fatigue mechanism and materials of tooth surface The tooth surface fatigue failure is caused by the repeated action of tensile stress caused by different tooth surface contact stress and relative sliding speed of tooth

(a) Input shaft gear damage

Fig. 3.64 Examples of gear bending fracture failure

(b) Main drive gear breakage

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(a) Section

(b) Oblique section

Fig. 3.65 Grain boundary oxide layer of gear surface

surface meshing in the gear pair. The main forms of failure are surface failure pitting and peeling. An example of tooth surface fatigue pitting is shown in Fig. 3.66. The tooth surface fatigue life is proportional to the surface temperature at the time of gear engagement, tooth surface roughness and friction coefficient, and inversely proportional to the viscosity of lubricating oil. Generally, the gear tooth surface fatigue life can be effectively increased by improving the hardness and tempering resistance of materials at high temperature. The results show that increasing the carbon mass fraction of tooth surface from 0.8–1.0% to 2.0–3.0% can inhibit the surface softening at high temperature, but the carburizing time and diffusion time need to be strictly controlled due to the large amount of tiny carbides precipitated during over carburizing. Figure 3.67 shows the relationship between tooth surface hardness and surface temperature of over carburizing and ordinary carburizing. In addition, the contact fatigue life of tooth surface can be greatly improved by appropriately increasing the content of Si and Cr alloying elements in the material and implementing carbonitriding heat treatment. Figure 3.68 shows the comparison of pitting fatigue test results of gear steels with the same alloy composition on the dynamic cycle test bench (where, CQT represents carburizing and CNQT represents carbonitriding).

(a) Gluing

Fig. 3.66 Examples of tooth surface fatigue pitting

(b) Fatigue pitting

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Hardness/HV

Over carburizing Ordinary carburizing

Heating temperature/

Fig. 3.67 Comparison of influence of over carburizing and ordinary carburizing on tooth surface hardness

Steel A+CNQT

Steel B+CNQT

Steel C+CNQT

20MnGrMo+CNQ

20MnGrMo+CQT

Number of cycles of pitting fatigue life (×104) Fig. 3.68 Gear pitting fatigue test results

3.4.1.2

Numerical Simulation Technique for Heat Treatment

It is crucial for numerical simulation and prediction of heat treatment deformation and strength to master basic parameters and strength characteristics of gear materials through gene analysis and basic performance test. Since the diffusion process of carburizing and nitriding in heat treatment involves temperature change, phase transformation and stress–strain and is a dynamic process of multi-field coupling

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behavior, mastering the dynamic process of multi-field coupling is the key to obtain the optimal heat treatment process of gears. For example, the gear steel will produce phase transformation plasticity during heat treatment, and its behavior will directly affect the shape and residual stress of the gear after heat treatment. Therefore, it is often difficult to predict and control the heat treatment deformation of gear and unable to determine the machining allowance before heat treatment if the phase transformation plasticity is not considered during heat treatment simulation. The gear heat treatment strengthening technology should focus on the control of surface integrity, that is, the control of the surface hardened layer texture, hardening depth, core hardness, residual stress, etc. Improper control of gear heat treatment will easily lead to defects such as transitional grain boundary oxide layer texture, decarbonization and microscopic cracks on the surface layer.

3.4.1.3

Tufftriding Heat Treatment

The tufftriding process is the tufftriding and ionitriding process developed on the basis of the nitriding, which is not limited by the steel type. In essence, tufftriding is low-temperature carbonitriding dominated by nitriding. At the same time as the nitrogen atoms infiltrate, a small amount of carbon atoms also infiltrate. Compared with carburizing, tufftriding has low treatment temperature, generally 460–600 °C, only a few microns to dozens of microns of surface hardened layer, low diffusion layer hardness, low brittleness and small gear deformation. Nitriding can improve the gear surface hardness, wear resistance, fatigue strength and corrosion resistance. Japanese automobile companies do not have high requirements for the fatigue life limit. The automobile gears and rotating members not subject to the tooth surface finishing after heat treatment are subject to the tufftriding during heat treatment, mainly aimed at improving wear resistance of gear surface and fatigue strength of medium carbon steel gears. Tufftriding has a wide application prospect in the AMT gear process.

3.4.1.4

Surface Quenching

Surface quenching mainly includes induction quenching and laser quenching. Compared with carburizing and quenching, the surface quenching leads to small deformation. The induction quenching is mainly used for automobile gear surface quenching. Depending on the gear modulus, different ways of induction quenching are adopted: high-frequency induction quenching when the gear modulus is 3–5 mm; medium-frequency induction quenching when the modulus increases to 5–8 mm. The high-frequency induction quenching can get a hardening layer evenly distributed along the gear profile and can be used to strengthen the vehicle steering pinion gears to greatly improve the fatigue strength of the test piece. The high-frequency induction quenching has the outstanding advantages of little CO2 emission, high gear fatigue strength and wear resistance and small distortion. The laser quenching

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has the advantages of fine and uniform grains in the quenching zone and small gear deformation, providing an effective way of tooth surface strengthening for gears with large modulus and high precision, but its cost is high.

3.4.1.5

Carburizing

Carburizing is one of the widely used chemical heat treatment methods in the surface treatment of automobile gears. The carburizing treatment can achieve good comprehensive mechanical properties of gears and effectively prevent the tooth breakage. At present, carburizing methods include gas carburizing, vacuum carburizing and plasma carburizing. Gas carburizing is a widely used surface strengthening process for low carbon alloy steel gears, which can achieve high gear surface hardness and improve its wear resistance, while the core is still the original lath-shaped martensite structure to maintain good toughness. The high temperature carburizing increases the gear carburizing temperature from 900 to 1050 °C, which can significantly shorten the carburizing time by more than 50%, so as to effectively improve the production efficiency. However, high temperature carburizing can easily lead to the coarsening of austenite grains, reduce the gear fatigue property and increase deformation. In order to overcome the problem of grain growth during high temperature carburizing, it has been found by domestic and foreign scholars after study that microalloying is an effective means to restrain the austenite grain growth of gear steel. The research in Japan shows that the optimal depth of carburized layer and the minimum deformation can be obtained by actively controlling the depth of carburizing and surface hardness during heat treatment. The adjustment of the additive amount of alloying elements such as Nb, Ti and B effectively controls the austenite grain coarsening produced by high temperature carburizing and well solves above problems. Vacuum carburizing and plasma carburizing have the advantages of no grain boundary oxide layer, high surface mechanical properties, few CO2 emissions, short heat treatment process time and energy saving, but the cost is high.

3.4.1.6

Carbonitriding

In carbonitriding heat treatment, the gear strength and wear resistance can be better improved by effective control of the nitrogen concentration and the time node of nitrogen addition. The carbonitriding heat treatment is beneficial to adjust the residual austenite content and restrain the initial fatigue crack from developing deep. The thickness of the carburized abnormal layer of the steel (20CrMoH) by traditional carburizing and quenching is 15–20 μm, and the thickness of the carburized abnormal layer by carbonitriding is only 1/2 of that by traditional carburizing and quenching. Carbonitriding can effectively increase the carburized layer depth, refine the austenite grains, reduce the gear deformation, and improve the gear strength and wear resistance. The actual instantaneous working temperature of the engaged tooth

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surface of carburized gear for transmission reaches 250–270 °C, higher than the commonly used tempering temperature range of 150–200 °C. Higher engagement temperature will lead to the decrease of tooth surface hardness and easy to produce fatigue pitting. The carbonitriding process is used to improve the tempering resistance by adjusting the nitriding capacity, and the tempering resistance temperature reaches about 300 °C.

3.4.1.7

High Strength Optimization Design of Automobile Gears

From the perspective of micro finishing of automobile gears, the optimization of high strength gear is mainly realized from three aspects: axial modification, profile modification and tooth edge modification. 1. Analysis of axial and profile modification design in optimization design In gear design, the influence of load is very large. The load is not distributed evenly on the gear, so it is necessary to make the corresponding design for the evenness of load distribution, so as to realize the purpose of gear optimization. There are mainly two influencing factors that cause uneven load: First, the error caused by the assembly factor makes the original gear engagement centerline not translate according to the trajectory, resulting in the meshing gear offset; second, gear deformation. The unevenness of the load generated by the powertrain during transmission leads to the gear deformation. In particular, when designing an AMT, it is necessary to consider the clutch, brake, motor pump, hydraulic valve body, arrangement of various sensors, elastic deformation of the long shaft after load, as well as the reduction of gear support stiffness caused by the overall lightweight of the transmission. In order to keep the gear involute engaged correctly, it is necessary to make the design based on axial modification, so as to improve the bearing capacity of the bearing and effectively strengthen the reliability of the powertrain operation. In addition, the axial modification also plays a positive role in other aspects, such as the evenness of gear load force, the reduction of engagement error rate and the reduction of planetary transmission vibration. The amount of axial modification caused by insufficient rigid support of general transmission should be controlled within 20 μm. Meanwhile, considering the different load, different speed and reverse engagement during the gear operation, it is also necessary to make corresponding adjustment according to the actual situation of gear operation through the profile modification design and properly remove the interference caused by the meshing gear, so as to effectively improve the stability of the powertrain during operation, then effectively alleviate the noise generated by the gear, and maintain good characteristics at the gear pair engagement. 2. Analysis of tooth modification design in optimization design Tooth modification design is often not carried out for a single gear, but for gear pairs under normal circumstances. There are many standards for tooth modification, and the standards set by various manufacturers, units and even countries are not the

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same. Therefore, before tooth modification, the corresponding standards need to be unified. In the design of tooth modification, there are many links that need to be paid attention to, especially the control of top chamfer. The top chamfer will affect the tip diameter, which will affect the effect of modification. If the top chamfer is not controlled in place, the actual engagement of the gear will be affected, and will gradually decrease. This will eventually cause interference to the operation of the whole powertrain, thus affecting the stability of the system operation.

3.4.2 Automobile High-Strength Bearing Technology Bearing, as an important key component in automobile industry, is widely used in the car seat, steering system, transmission, transfer case and braking system and plays special roles in bearing load, reducing friction and guiding the moving parts. With the development of economy and continuous progress of industrial technology, China has become a big producer of bearings including automobile bearing steel. However, there is still a certain gap between China and German Schaeffler, Swedish SKF, American TIMKEN, Japanese KOYO and other first-class manufacturers. The bearing material is an upstream industry. The future direction of efforts is still strict control of metallurgical quality, the level of non-metallic inclusions, the size and distribution of carbides, and improvement of the level of heat treatment technology. Heat treatment is a critical process in the manufacturing process of automobile bearings. The machining quality and raw materials are two important factors affecting the bearing life. Heat treatment has an important effect on the microstructure, mechanical properties, surface quality, size and shape accuracy and stability of bearings and other parts under service conditions, Therefore, it is an important research topic of heat treatment technology to optimize the heat treatment process, select the appropriate heat treatment parameters, and obtain the best overall performance suitable for the service conditions and failure mode of the workpiece. The bearing is composed of an outer ring, an inner ring, a rolling body (ball, cylinder, cone or needle roller, etc.) and a retainer. Some bearings are also equipped with seal rings. In addition to the seal ring and part of the retainer, the rest of the manufacturing material is mainly bearing steel. The type and model of automobile bearings is mainly selected on the basis of the nature, direction and size of load, the work environment of actual part, as well as the requirements for the bearing stiffness, limit speed, life and accuracy. Bearings are widely used in the whole vehicle, and change with the vehicle type, installation site and manufacturer. The following is a brief introduction of the powertrain bearings (alternator bearings in engine, electromagnetic clutch bearings in air conditioning, tensioning wheel and idler wheel bearings, etc.), drive system bearings (shaft gears in transmission, differential and clutch bearings, etc.) and other related products.

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Powertrain Bearings

The engine, as the heart of the vehicle, constantly powers the other parts. Its internal bearings were previously dominated by sliding bearings, and now most of them are sealed ball bearings on the premise of improving bearing performance. The alternator bearings are single-row sealed ball bearings, which are mainly subject to centripetal force and are required to operate reliably at speed over 2000 r/min and temperature above 180 °C. The bearing ring and rolling body are made of high purity GCrl5, and the hardness after heat treatment is required to reach 58–64 HRC; the retainer is generally made of nylon (PA46), and the seal ring is generally made of acrylic rubber (ACM) according to the standard JB/T 8167-2017. The electromagnetic clutch bearings in air conditioning are double row angular contact ball bearings with the outer ring rotation. The speed of the air conditioning pulley can reach 7000–13,000 r/min, and the maximum temperature is up to 160 °C. The tensioning wheel and idler wheel bearings are high-performance sealed ball bearings, with the former acting on the loose side of the synchronous drive belt and the latter acting on the tight side. The retainer can be made of engineering plastics, or 08 steel or 10 steel, and the seal ring is made of ACM or FPM (fluororubber) according to the standard JB/T10859-2008. The water pump bearing is generally the double row ball bearing, with the radial dimension smaller than that of the general bearings. It is essentially a simplified double support bearing without inner ring. The raceway of the rolling body is directly processed on the shaft, and the two supporting bearing outer rings are processed into a whole. The two sides of the ring are sealed with seals. The roller is usually made of high chromium bearing steel, and the shaft and outer ring are made of carburizing steel or high-carbon chromium bearing steel according to the standard JB/T8563-2010.

3.4.2.2

Drive System Bearings

The representative part of the drive system is transmission, which is classified into manual transmission (AMT), automatic transmission (AT), continuously variable transmission (CVT) and dual clutch transmission (DCT), and is also the part mostly applied in the bearing. There are often multiple bearings in the transmission for different gears, mainly including ball bearing, cylindrical roller bearing, tapered roller bearing and needle roller bearing. The bearings have high working speed and the oil cleanliness has a great impact on the bearing service life.

3.4.2.3

Automobile Bearing Materials and Performance Requirements

At present, the vehicles are developing towards electrification, intelligence, lightweight, performance and high reliability. Due to the progress of electronic

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control technology, the vehicles are also developing towards low energy consumption and high efficiency. As an important part of automobile powertrain, the rolling bearing and high efficiency conical bearing must adapt to this trend. In the service process of automobile bearings, the rolling body and the ring surface should bear a large pressure per unit area, which can be up to 5000 MPa by calculation. Bearings operate by means of rolling and sliding. In addition to high-frequency and alternating contact stress, the bearings are also subject to the action of centrifugal force. The main failure modes of automobile bearings are peeling, pitting, adhesion, strain, fracture, loss of precision, and excess vibration and noise. Therefore, there are the following requirements for the bearing steel performance: ➀ High purity; ➁ Low oxygen content; ➂ High hardness and wear resistance; ➃ Good dimensional stability; ➄ Sufficient compressive strength and deformation resistance; ➅ Good process performance. The bearing steel is one of the important special steel varieties and its quality and performance largely reflect the metallurgical level of a country. The life and reliability of automobile bearings are related to design, processing and manufacturing, lubrication, installation and maintenance, but raw materials are the key basis. Of the bearing components, except the retainer made of the nylon material (such as injection molded PA66 + 30%GF) from the original stamping steel, and the seals made of rubber (such as ACM + SPCC, NBR + SUS430), the rolling body and inner and outer rings of Chinese automobile bearings are largely made of high-carbon chromium bearing steel (the mass fraction of C is 0.95–1.05%, and of Cr is 1.40–1.65%). In order to improve the hardenability to adapt to the wall thickness variation of parts, a series of high-hardenability high-carbon chromium bearing steels can be developed by increasing the content of Mo: such as 100Cr6 and 100CrMo in Germany, SKF2 and SKF3 in Sweden, 52,100.3 and 52,100.4 in the US, SUJ2, SUJ3, SUJ4 and SUJ5 in Japan. They are suitable for martensitic quenching, and also for bainite quenching of ultra-thick wall bearing parts. There are slight differences in chemical composition, but they can be regarded as variants of Gcr15. Although these varieties are relatively simple, they are also the most demanding varieties of constructional steels (gear steel, bearing steel, spring steel, non-tempered steel and cold heading steel). It is required to improve the steel purity, strictly reduce the content of elements such as O, S, Ca, N and Ti and control the possible defects in the metallurgical forming process including smelting, casting, rolling and forging. The smelting processes commonly used are vacuum degassing, electroslag remelting and external refining. Reducing the oxygen content can significantly prolong the fatigue life of bearings. Figure 3.69 shows the relation curve between the oxygen content and the bearing comparative life (L18 in the figure represents the basic rating life and refers to the rated life related to 90% reliability). In GB/T18254-2016, the oxygen content of high-carbon chromium bearing steel is clearly stipulated: not exceed 15 × 10–6 in the moulded steel and not exceed 12 × 10–6 in the continuously cast steel, and as low as 5 × 10–6 with the development and control of metallurgical equipment and process in actual production. In addition, in the standards or technical agreements, there are relevant limits on the smelting methods, non-metallic

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Fig. 3.69 Relationship between oxygen content and bearing comparative life

Comparative lifetime (L10×106)

170

Oxygen content (×10-6)

inclusions, segregation, carbon layers, macrostructure, microstructure, carbide inhomogeneity, surface quality, and measurement allowance. The bearing manufacturers must strictly test and manage steel products when they leave and enter the factory. It should be added that, except the vast majority of automobile bearings that are rolling bearings, the crankshaft bearing, connecting rod bearing, piston bush, guide holder for shock absorber and transmission reverse gear bushing are sliding bearings, which are not involved in the heat treatment and are formed mainly relying on powder metallurgy sintering and rolling, with the back generally made of the steel (such as 08Al) with the carbon mass fraction less than 0.15% and the spindle made of alloy layer (such as Al–Sn20Cu or common tin base, lead base, copper base or aluminum base bearing alloy). The heat treatment discussed in the following article is mainly aimed at automobile rolling bearings.

3.4.2.4

Heat Treatment Technology of Automobile Bearings

The main effect of adding alloying element chromium in the steel for automobile bearings is to improve the hardenability of steel, so that the parts texture is relatively uniform on the section after quenching and tempering. Chromium can form alloyed cementite, refine the austenite grain, reduce the superheated susceptivity of steel, improve the wear resistance, obtain the fine or cryptocrystalline martensite when quenching, and increase the toughness of steel. Cryogenic treatment is generally not required for automobile bearings, unless there are special requirements for the stability of parts size and the content of residual austenite. 1. Production process route of automobile bearing parts General production route of steel ball rolling body: bar → ball formed by hot heading of ball-billet (filing) → soft grinding → heat treatment → hard grinding → fine lapping → fine grinding (polishing). General production route of inner and outer rings: tubing (cold rolling) → annealing → turning → soft grinding → heat treatment → grinding finishing.

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General production route of solid retainer (nylon): blank → turning → pulling and drilling window → surface treatment. General production route of pressed retainer (metal): strip or sheet → forming → bossing → frame trimming → pressing slope → expansion → surface treatment. The rolling body, outer and inner rings of the automobile bearings as well as the flanges of the hub bearings should be subject to appropriate heat treatment, in order to give full play to the potential of the materials, obtain the expected performance of the parts and improve the service life of the assembly. Heat treatment mainly includes spheroidizing annealing, integral quenching + low temperature tempering, chemical heat treatment and inductive heat treatment. 2. Overview of heat treatment of key bearing parts for automobile

Temperature/

The following is a brief introduction of the heat treatment equipment, process cases, technical requirements and development prediction. The special atmosphere furnace is usually used for the spheroiding annealing equipment, so that the surface of annealed parts is not oxidized, and can improve the material utilization of bearing parts. The heating temperature of bearing materials ranges from 835 to 850 °C, and the spheroidization temperature ranges from 750 to 760 °C, as shown in Fig. 3.70. After the rolling ball is forged, it is annealed by Aichelin continuous nitrogen base special atmosphere furnace, with the spheroidizing annealing temperature of 760 °C, the dew point lower than 20°C, the propane flow rate of (0.18 ± 0.02)m3 /h, the furnace pressure of 50–300 MPa, the test hardness not more than 210 HB and the decarbonization layer not thick than 0.25 mm. The hardness of the steel ball after overall quenching and tempering should reach more than 60 HRC. The quenching and tempering equipment usually uses protective atmosphere type cast chain furnace,

Furnace cooling Into the heating

Heating

Air cooling

Time/h

Fig. 3.70 Spheroidizing annealing process curve of bearing parts

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mesh belt furnace or push rod furnace, with high production efficiency and low energy consumption. Common domestic manufacturers are Jiangsu Fengdong, NORINCO and Hangzhou Jinzhou. The inner and outer rings are quenched in a continuous furnace with protective atmosphere, using the special KR468G bearing quenching oil and the adjusted heating temperature, time, conveyor belt running speed and other parameters, or subject to martensite step quenching in salt bath. The process curve is shown in Fig. 3.71. The hardness is 63–64.5 HRC after quenching and 61– 63HRC after tempering at (180 ± 10) °C. The taper of the ring is about 0.05 mm and the roundness is not more than 0.15 mm. The automobile hub bearings with flange plate are made of S55C and shall have the surface hardness more than 60HRC in the quenching area. It is advisable to use automatic induction quenching production line. The water quenching medium with adjustable concentration is selected, with the pressure of 0.2–0.6 MPa, the hardness of 62–65 HRC after quenching, the hardened layer depth of 2.2–3.4 mm, the roundness not more than 0.1 mm, and the hardness up to 60–63HRC after integral tempering at (160 ± 10) °C × (120 ± 5)min. With the continuous improvement of domestic heat treatment equipment and production technology, the production and processing technology of automobile bearing parts has been basically mature. The original box furnace, pit furnace, salt bath furnace, drum furnace, ordinary air heating furnace and other equipment are basically eliminated. The popular solution is the protective atmosphere equipment supplemented with pressure swing adsorption, membrane nitrogen making and other technologies. The integral quenching and tempering line and automatic induction quenching and tempering line dominated by the roller mesh belt furnace have become the mainstream. In addition, the transition from protective atmosphere to controllable atmosphere, and transition of the furnace control system from single line computer control to cluster computer control change have also gradually developed into two major trends.

Fig. 3.71 Integral quenching and tempering process curve of bearing parts. Note In the figure, Accm is the final temperature at which the secondary cementite is completely dissolved into austenite; Ac1 is the temperature when the pearlite starts transformation to austenite; Ms is the temperature when the austenite starts transformation martensite

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3.4.3 New Surface Treatment Technology for Powertrain Parts 3.4.3.1

Current Status of Surface Strengthening Technology for Transmission Pair

The tooth surface fatigue damage will be caused by the repeated action of the high contact stress and the tensile stress in the rapid relative sliding of tooth surface meshing. In order to prevent this kind of damage, the modified coating technology of tooth surface can be used to effectively improve the surface integrity of gear pair and the fatigue resistance of tooth surface. In recent years, with the constant improvement of process, the surface coating technology has gradually presented its unique distinction in the improvement of friction and wear of friction pair and the surface state, created considerable economic benefits, developed into an important technology in the field of surface engineering and provided an important means to improve the tribological properties of the transmission pair and reduce the material wear. Many foreign research institutions and scholars have made in-depth research on the surface coating strengthening technology of the transmission pairs. The FZG gear test bench was used for the gluing test of PVD-coated gears at the Gear Research Centre, Technical University of Munich, Germany. The results showed that, compared with the uncoated gear, the coated gear showed better gluing resistance, and the PVD coating could significantly reduce the body temperature of the gear; the Centre also evaluated the bearing capacity of gear with two indexes: the degree of micro-pitting damage and the average tooth profile deviation. The results showed that the degree of micro-pitting damage of gear was greatly reduced after coating treatment. W. Habchi studied the influence of thermal and mechanical properties of coatings on friction in elastohydrodynamic lubrication contact. The results showed that the friction coefficient increased with the thermal inertia and hardness of the coating at a large sliding speed, and the soft coating with low thermal inertia could minimize friction. More and more domestic research institutions and scholars also begin to apply the coating technology to the gear and other transmission pairs to improve the transmission performance between transmission pairs. As one of the most widely used protective measures in chemical conversion coating, manganese phosphate conversion coating, with the advantages of low preparation cost, high processing efficiency and low pollution, is widely used in the automobile, machinery, shipbuilding and other fields. Shi Wankai et al. from Chongqing University studied the tribological properties of the manganese phosphate conversion coating. The results show that the coating can significantly reduce friction and wear when the load is large, and the pores formed on the coating surface are the main reason for improving the friction and wear properties. The scholar also established a contact mechanical analysis model of coated gear with the finite element theory, and discussed the change law of stress distribution with the coating type, thickness, load value and other parameters, which provided guidance for the application of physical vapor deposition coating

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to high-speed and heavy-load gear assembly. Chen Yong et al. studied the influence law of the manganese phosphate conversion coating on the fatigue pitting strength of gears with different machining methods using the contract test and demonstrated that the gears with manganese phosphate conversion coating could withstand the initial impact and improve the pitting durability of gears. In recent years, the research and development results of shot peening treatment technology on the gear surface have greatly improved the gear bending fatigue strength life limit, which exceeds the contact pitting fatigue strength limit of the tooth surface. How to further improve the contact fatigue strength limit of tooth surface has become the most important research topic of high strength gear technology.

3.4.3.2

Manganese Phosphate Conversion Coating

The application of the manganese phosphate conversion coating technology in improving the surface strength of transmission parts first appeared in the aspect of improving the fatigue life of bearing rollers. The manganese phosphate conversion coating obtained after the gear surface phosphating can effectively reduce the friction coefficient of the friction pair surface and has good resistance to gluing or abrasion. In Japan, the author first applied the manganese phosphate conversion coating technology to the automatic transmission gear in the research practice of high strength gear. Shi Wankai from Chongqing University and the author prepared the superfine manganese phosphate conversion coating on the surface of 20Cr gear, and studied the relationship between the size of phosphide grain and the oil storage characteristics of the surface pores of the coating. The results showed that the superfine manganese phosphate conversion coating on the steel surface had obvious antifriction and wear resistance effect under the condition of surface oil immersion and lubrication. The manufacturing processes of the manganese phosphate conversion coating mainly include pretreatment of the gear surface with degreasing agent in a 70–95 °C degreasing bath, washing with water and then surface conditioning at the treatment temperature 40–80 °C, with the phosphating temperature range of 80–100 °C, acid ratio of 5.6–6.2 and treatment time of 10–15 min. After the preparation of the manganese phosphate conversion coating, a soft layer of several microns thick is formed on the gear surface, which flattens out most of the concave and convex cutting ripples on the gear surface, reduces the local maximum meshing contact stress and metal surface friction factor, and improves the oil film and lubrication condition in gear engagement. A superfine manganese phosphate conversion coating can be obtained by controlling the process parameters of the manganese phosphate conversion coating to affect the coating density and grain size. After treatment, a soft layer of 3–5 μm thick is formed on the tooth surface and the density of the formed coating surface is about 2.2 g/m2 . After treatment, the surface morphology is observed by scanning electron microscopy (SEM), as shown in Fig. 3.72. The ordinary manganese phosphate conversion coating treatment and superfine manganese phosphate conversion coating treatment shall be selected combined with the gear

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(a) Ordinary

175

(b) Superfine

Fig. 3.72 Surface topography of ordinary and superfine manganese phosphate coating

Separation voltage/V

Untreated

Treated with manganese phosphate coating

Run time/h

Fig. 3.73 Formation of oil film on cylindrical roller

processing technology and actual working conditions. Figure 3.73 shows the formation of oil film by cylindrical roller. The formation of the oil film by cylindrical roller is observed and tested with the separation voltage resistance measurement method, with complete contact at 0 V and complete separation at 0.1 V. The separation voltage of the cylindrical roller after the manganese phosphate conversion coating treatment begins to rise after 30 min, and its oil film formation ability is significantly better than that of the untreated cylindrical roller pair.

3.4.3.3

Molybdenum Disulfide Coating Technology

Molybdenum disulfide (MoS2 ), as a high-quality solid lubrication material, has good antifriction, wear resistance and bearing capacity. The MoS2 film is of layered structure, and the particles that compose the deposited film layer have low hardness and high stability.

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Pitting area rate/(%)

Fig. 3.74 Comparison of fatigue life and pitting area ratio of gears with different materials

Steel A Steel C Grinding + shot peening Steel B+ carbonitriding Molybdenum disulfide coating

Run/(×106r)

It has become a research hotspot to improve the bearing capacity of gear surface by using MoS2 , and scholars at home and abroad have done a lot of research. Amaro et al. obtain MoS2 lubricating film on the spline gear using the magnetron sputtering, which effectively reduced friction at high speed and increased the fatigue life limit. Holmberg et al. used MoS2 /Ti composite coating technology to further reduce the friction coefficient, which could be as low as 0.07 at room temperature to effectively reduce the friction and wear of the friction pair in operation. Martins et al. conducted FZG bench test on MoS2 composite coated gear. The gear coated with MoS2 was operated at a 5-stage load and 3000 r/min, and the temperature and friction coefficient of the gearbox decreased significantly. The molybdenum disulfide coating technology has been applied in the development and research of transmission gears in Nissan and Mazda. The main principle is that the 2–3 μm soft coating on the tooth surface after MoS2 film plating can reduce the local maximum meshing contact stress and surface friction coefficient of the tooth surface, and improve the lubrication condition in gear engagement. Figure 3.74 shows the comparison of fatigue life and pitting area rate of gears with different materials and gears with different tooth surface treatments. In the figure, steel A (1Cr–0.4Mo) is the commonly used gear steel, steel B is the vanadium added gear steel, and steel C is the Mn/Mo incremental gear steel. The test results show that, after the surface coating with of molybdenum disulfide, the smoothness of tooth surface after initial gear engagement and operation is obviously improved, and the fatigue life is increased by more than 3 times.

3.4.3.4

Superfine Composite Material Coating Technology

In recent years, companies in Japan and Taiwan have studied and applied the spraying technology of composites containing MoS2 and superfine metal particles, which, as a new method in the field of pressure spraying, has achieved a good practical effect in the field of high strength gear surface strengthening. In this technology,

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(b) Treated

Fig. 3.75 Comparison of surface morphology before and after spraying with composite

the spherical ground ball and solid lubricant (MoS2 ) composite material are pushed by the high-pressure inert gas to strike the gear surface at high temperature and high pressure and penetrate into the tooth surface by 3–4 μm depth, so that the microstructure of the metal surface is changed several microns deep; due to the impact of spherical particles, a number of tiny holes are formed on the tooth surface, so that the surface structure is slightly compressed, resulting in the reduction of the external stress and the significant increase in the surface hardness. Moreover, the solid lubricant is attached to the surface, improving the self-lubrication of the tooth surface, reducing the roughness of the tooth surface, improving the gear engagement quality and reducing the engagement noise. As shown in Fig. 3.75, the inner edge of the needle bearing of a transmission gear has been sprayed with composite material to improve the smoothness of the surface indentation, and numerous fine pits have been formed on the surface, which is conducive to the formation of the oil film, thus improving the oil film adhesion on the friction surface and improving the fatigue strength.

3.4.3.5

Compound Strengthening Technology of Gear Surface

With the continuous improvement of gear requirements and the continuous development of gear surface processing technology, the use of two or more surface strengthening technologies for gear compound treatment to improve the integrity of the gear surface to meet the more demanding requirements for gears has become an important means in the field of gear nowadays, such as QPQ (quench polish quench), composite coating technology combining thermal spraying and shot peening, coating and shot peening composite technology, etc. The QPQ is a metal surface modification technology with high corrosion resistance and wear resistance, which is composed of low temperature salt-bath nitrocarburizing and salt bath oxidation. The technology has been used by GM to improve the wear resistance of the internal combustion engine cylinder liners. It is also applied in the camshaft of Volkswagen and the internal

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3 New Energy Vehicle Powertrain Technology

gears of the heavy duty vehicle reducers of Sinotruk. The compound strengthening technology of thermal spraying and shot peening makes the gears have both high resistance to bending fatigue and good resistance to contact fatigue, and enhances the antifriction and lubrication properties of the gears.

3.4.3.6

Barrelling and Abrasive Flow Machining

Under certain conditions, barrelling can improve the roughness of tooth surface and fatigue life of gear with low cost. The barrelling process is that the mixture of grinding stone and grinding powder with different kinds of materials and diameters of several millimeters rotates in the same direction (100 m/min) with the grinding treatment tank, and the rotation direction of the processed gear is opposite and the gear moves up and down for 15 ~ 30 min of treatment. Professor Hoyashita from Saga University, Japan, together with the author and Sumitomo Heavy Industries, studied the barrelling method after the gear shot peening, and obtained good test results, which attracted the attention of the relevant experts in the United States and Japan. Abrasive flow machining (AFM) is a new process technology for surface polishing and deburring of workpiece by elastic material consisting of flexible polymer carrier and abrasive. Xu et al. treated helical gears with AFM and demonstrated through the simulation and experimental study that AFM could effectively improve the surface roughness quality of helical gears. The selection and matching of abrasive media in the barrelling and AFM technology are very important to the effect of machining. It is very important to continue the simulation and experimental study of the abrasive material against the tooth surface roughness and fatigue strength, as well as to study the optimal selection and matching of various abrasive media.

3.4.4 Influence of Oil on Fatigue Strength Life and Wear of Gear In addition to meeting the lubrication requirements of gears and bearings, the automatic transmission fluid (ATF) is also used as a hydraulic control oil to lubricate and cool the clutch and other components and control the action stability. Therefore, the dynamic friction coefficient, static friction coefficient and oxidation durability of oil products are very demanding. In recent years, due to the increase of requirements for the control system accuracy and sliding performance by the automatic transmission, the oil lubrication of gear system is faced with great challenges. Table 3.16 shows the representative characteristics of two different oils of the automatic transmission. The helical gear pairs used for the test are treated with compound shot peening and manganese phosphate chemical treatment respectively. Figure 3.76 shows the fatigue test bench of the power circulating gear. The working temperature of ATF in transmission is usually 80–110°C. The fatigue pitting area ratio of gear is measured

3.4 High-Strength Component Technology of Vehicle Powertrain

179

Table 3.16 Representative traits of ATF Parameter Density/((g)cm−3 ) (15 °C) Dynamic viscosity/cSt (40 °C)

ATF-A

ATF-B

0.867

0.857

34.1

33.9

Dynamic viscosity/cSt (100 °C)

7.55

7.34

Mean dynamic friction coefficient

0.128

0.137

Feedback controller Bus feedback

380V alternating current

Test bench test system

Control unit

Drive variable frequency motor

Tacho-torq uemeter

Torque-spe ed sensor

Vibration detection

Tooth Oil temperatu surface Tacho-torquemete re temperat r detection ure

Reduction box under test

Torque-spe ed sensor

Control unit

Oil temperature control system

Load variable frequency motor

Fig. 3.76 Fatigue test bench of the power circulating gear

when the contact stress of gear is 1730 MPa under the working oil temperature of 80 °C. The results are shown in Fig. 3.77. The fatigue pitting area ratio of gear in lubricating oil ATF-A is smaller than that in lubricating oil ATF-B. Figure 3.78 shows the wear amount at the bottom of the gear. The wear amount of the driving pinion in the lubricating oil ATF-A is much greater than that in the lubricating oil ATF-B. The test results show that gear wear is inversely proportional to the pitting area ratio.

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3 New Energy Vehicle Powertrain Technology

Pitting area rate/(%)

ATF-A manganese phosphate conversion coating ATF-B manganese phosphate conversion coating

Number of cycles (×106)

Wear depth/um

Fig. 3.77 Influence of different transmission fluids on gear pitting

ATF-A manganese phosphate conversion coating ATF-B manganese phosphate conversion coating

Number of cycles (×106)

Fig. 3.78 Influence of different transmission fluids on wear depth

Bibliography Amaro RI, Martins RC, Seabra JO et al (2005) Molybdenum disulphide/titanium low friction coating for gears application. Tribol Int 38:423–434 Ay N, Celik ON, Goncu Y (2013) Wear characteristics of traditional manganese phosphate and composite hBN coating. Tribol Trans 56(6):1109–1118 Chen Y (2003) The influence of ATF on the pitting fatigue strength of carburized gears. JATCO Tech Rev 4:84–91 Chen Y (2003) 浸炭菌車刀上》 千>分强度仁及(寸渭滑油刀影簪. Jatco Tech Rev 4:83–91 Chen Y, Yamamoto A, Omori K (2007) Improvement of contact fatigue strength of gears by tooth surface modification processing. In: 12th IFToMM World Congress, Besancon, France Chen Z, Liu X, Liu Y et al (2014) Ultrathin MoS, nanosheets with superior extreme pressure property as boundary lubricants. Scien Rep 5

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Chen Y, Zang L, Ju D et al (2017) Research status and development trend on strengthening technology of high strength automobile gear surface. China Surf Eng 30(1):1–15 Fargas G, Roa JJ, Mateo A (2015) Effect of shot peening on metastable austenitic stainless steels. Mater Sci Eng A, 641:290–296 Feng X, Zhou J, Mei Y et al (2015) Improving tribological performance of gray cast iron by laser peening in dynamic strain aging temperature regime. Chinese J Mech Eng 28(5):904–910 Fernandes CM, Marques PM, Martins RC et al (2015) Gearbox power loss. Part II: friction losses in gears. Tribol Int 88:309–316 Fujii M, Mizuno Y, Yosida A (2007) 106 influence of artificial defect on rolling contact fatigue strength of steel roller/MPT. In: Fukuoka: the JSME international conference on motion and power transmissions. The Japan Society of Mechanical Engineers, pp 43–46 Han B, Ju DY (2009) A Method for Improving compressive residual stress of small holes surface by water-jet cavitation peening. Mater Sci Forum:137–142 Hivart P, Hauw B, Crampon J et al (1998) Annealing improvement of tribological properties of manganese phosphate coatings. Wear 219(2):195–204 Holmberg K, Mathews A, Ronkainem H (1998) Coatings tribology-contact mechanisms and surface design. Tribol Int 1–3:107–120 Hoyashita S, Hashimoto M (1998) Surface improvement and durability of case-carburized gear tooth (2nd report): effects of shot peening and barrelling processes. Int J Jpn Soc Precis Eng 32(2):104–109 Ju D (2012) Future development roadmap of metal heat treatment in Japan. Heat Treat Metals 37(1):14–20 Lig J, Peng Q, Li C et al (2008) Microstructure analysis of 304L austenitic stainless steel by QPQ complex salt bath treatment. Mater Characterization 59(9):1359–1363 Lince JR, Loewenthal SH, Clark CS (2019) Tribological and chemical effects of long term humid air exposure on sputter-deposited nanocomposite MoSz coatings. Wear 432–433:202935 Liu XH (2007) Study on process for decreasing heat treatment distortion of GCr15 bear ring. Metal Hotworking Technol 10 Liu W, Xia Y, Fu X (2005) Lubricating materials for gear transmission. Chemical Industry Press, Beijing Lu S, Zhou L, Li J (2009) Preparation technology of molybdenum disulfide coating for rotating seal ring. Lubri Eng 34(09):72–75 Luo Y, Xie M (2013) Application of QPQ in auto parts. Modern Comp 7:58–60 Lv Y, Lei L, Sun L (2015) Effect of shot peening on the fatigue resistance of laser surface melted 20CrMnTi steel gear. Mater Sci Eng A, 629:8–15 Martins RC, Paulo SM, Seabra JO (2006) MoS-/Ti low-friction coating for gears. Tribol Int 39:1686– 1697 Morais R, Reguly A, Almeida L (2006) Transmission electron microscopy characterization of a Nb microalloyed steel for carburizing at high temperatures. J Mater Eng Perform 15(4):494–498 Niemann G, Rettig H, Lechner G (1961) Scuffing tests on gear oils in the FZG apparatus. Tribol Trans 4(1):71–86 Palaniradja K, Alagumurthi N, Soundararajan V (2004) Evaluation of process capability in gas carburizing process to achieve quality through limit design concept. Trans Mater Heat Treat 25(5):395–397 Rakita M, Wang M, Han Q et al (2013) Ultrasonic shot peening. Int J Comput Mater Sci Surf Eng 5(3):189–209 Shen Y (2013) Metal surface self-lubrication treatment method: China, 201310441042.4. 2013-1225 Sherafatnia K, Farrahig H, Mahmoudi AH et al (2016) Experimental measurement and analytical determination of shot peening residual stresses considering friction and real unloading behavior. Mater Sci Eng, A 657:309–321 Shi W, Jiang H, Qin D et al (2009) Friction and wear performance of superfine manganese phosphate conversion coating. Tribology 29(3):267–271

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Totik Y (2006) The corrosion behaviour of manganese phosphate coatings applied to AISI 4140 steel subjected to different heat treatments. Surf Coat Technol 200(8):2711–2717 Wang CM, Liau HC, Tsai WT (2007) Effects of temperature and applied potential on the microstructure and electrochemical behavior of manganese phosphate coating. Surf Coat Technol 102(2–3):207–213 Wang G, Jiao M, Li H et al (2014) Application and research of new thermal spraying technology in engine friction-reduction performance. Surf Technol 43(1):103–108 Xu YC, Zhang KH, Lu S et al (2013) Experimental investigations into abrasive flow machining of helical gear. Key Eng Mater 546:65–69 Yao L, Deng Y (2012) Composite aitrided QPQ treatment new technology development and application. Internal Combus Engine Parts 5:36–40, 43 Yilmaz M, Kratzer D, Lohner T et al (2018) A study on highly-loaded contacts under dry lubrication for gear applications. Tribol Int 128:410–420 Yong C (2001) P-SC300 report on research results of japan high precision and high efficiency gear performance research branch. Jpn Soc Mech Eng 1:141–145 Yoshita M, Ikeda A, Kuroda S (2004) Improvement of CVT pulley wear resistance by micro-shot peening. JATCO Tech Rev 5:51–59 Zang L, Chen Y, Ran L et al (2017) Experimental study on the fatigue characteristics of automatic transmission hears with manganese phosphate conversion coating. Autom Eng 39(10):1203– 1210 Zang L, Chen Y, Chen H et al (2018) Simulation and experimental study on temperature field characteristics of coated gears in automatic transmission. Autom Eng 40(9):1054–1061 Zang LB, Chen Y, Ranl X et al (2019) Comparative study on the friction property of bearing steel modified by graphite/MoS composite coating and manganese phosphate coating. Mater Sci 25(4):383–393 Zang LB, Chen Y, Wu YM et al (2020) Tribological behavior of AlSI52100 Steel after PC/MoS lubricant surface modification. Strength of Mater:1–12 Zhangj JW, Lu LT, Shiozawa K et al (2011) Analysis on fatigue property of microshot peened railway axle steel. Mater Sci Eng, A 528(3):1615–1622 Zhao H, Wu Q, Huang K et al (2013) Status and problem research on gear study. J Mech Eng 49(19):11–20

Chapter 4

Energy Management Strategy Techniques for New Energy Vehicles

4.1 Introduction 4.1.1 Energy Management Strategies for Battery Electric Vehicles With the continuous development of power batteries, their specific energy density, cost and life have been greatly improved, which promotes the promotion and application of electric vehicles and makes them become one of the typical products of future transportation. A fully functional energy management system can give full play to the performance of the battery module, reduce the battery module fault, prolong the service life of the battery module, and increase the use safety of the electric vehicles. Therefore, the research of the electric vehicle energy management system has attracted more and more attention from scholars and experts. In general, the energy management system of an electric vehicle needs to achieve the following functions: (1) (2) (3) (4) (5)

Energy detection and distribution; Battery status prediction and control; Charge interaction and balancing; Monitoring and recording; Power regulation of vehicle accessories.

Among them, the design of the energy management strategy, the prediction of the battery state of charge (SOC) and the regenerative braking energy recovery are the hot spots and key technologies in the current energy management research of battery electric vehicles. A battery electric vehicle is equipped with P, R, N and D gears, and the driver can change gears according to different situations. When the vehicle is trouble-free

© Huazhong University of Science and Technology Press and Springer Nature Singapore Pte Ltd. 2023 Y. Chen, New Energy Vehicle Powertrain Technologies and Applications, Key Technologies on New Energy Vehicles, https://doi.org/10.1007/978-981-19-9566-8_4

183

184

4 Energy Management Strategy Techniques for New Energy Vehicles Self-test

Yes

Shift position? No

Passive stop state

Parking state

Backup state

Driving state

Fig. 4.1 Driving mode of battery electric vehicle

and the drive system is in normal drive mode, the driving mode of the vehicle can be divided into passive stop state, driving state, backup state and parking state, as shown in Fig. 4.1. (1) Passive stop state: This state is mainly controlled for low battery. At this point, if the driver starts the vehicle, the energy control system will prohibit the high voltage, and indicate the low battery and the mileage that can travel on the instrument to warn the driver to charge in time. (2) Parking state: In this state, the battery power is sufficient. If the driver needs to park temporarily or for a long time according to the situation, he/she shall push the gearshift into N/P gear, and the motor will stop working in this state. (3) Backup state: When the battery is sufficient, the driver engages R gear. In this state, the motor runs in reverse, and the speed is limited by limiting the output power of the motor. At this time, the motor torque is determined by the accelerator pedal, brake pedal and battery status. (4) Driving state: When the battery is sufficient, the driver engages D gear. In this state, the energy management system is the highest priority for the operation of the driver, and it also determines whether the vehicle needs to enter the braking energy recovery mode combined with the vehicle speed, remaining battery capacity and rotational speed information. The brake device for the battery electric vehicle, with the same function as that of the traditional internal combustion engine vehicles, is to slow down or stop the vehicle. It is mainly composed of a brake and its control device. Unlike traditional vehicles, the battery electric vehicle has a braking energy recovery device. In the process of vehicle braking, it is ideal to maximize the recovery of braking energy, but in fact, not all braking energy can be recovered. In order to improve the energy feedback rate of battery electric vehicles, the proportion of regenerative braking and mechanical braking must be well distributed under the condition of ensuring the stability and smoothness of braking. In the process of formulating the control strategy, some factors affecting the vehicle, such as battery SOC, must be taken into account. In the case of insufficient battery SOC, battery charging should be considered first. If

4.1 Introduction

Drive shaft

Kinetic energy

185

Transmission

Mechanical energy

Energy conversion device

Hydraulic energy,

Energy storage electric devices energy, etc.

Fig. 4.2 Principle of braking energy recovery

the SOC is still at a very high level, the regenerative braking must be reduced or even stopped in order to prevent overcharging. The principle of braking energy recovery is shown in Fig. 4.2. Battery SOC is the ratio of the battery remaining capacity to the battery capacity. Accurate SOC estimation can prolong battery life, improve battery safety, and prevent battery damage caused by overcharge or overdischarge. Battery SOC estimation for electric vehicles can predict the driving range, allowing the driver to plan its driving and avoid dead battery during the journey; can help the driver to distribute the energy reasonably, make more effective use of the limited energy, and avoid the battery damage caused by overcharge or overdischarge. Therefore, battery SOC estimation is very important for the EV battery management system. It is affected by many factors, including temperature, charge–discharge rate, battery aging, battery self-discharge and number of charge–discharge. (1) Temperature Battery temperature is closely related to SOC estimation accuracy. Long-term operation of the battery at too high or too low temperature will accelerate battery aging and change the chemical properties, which will change many parameters of the battery, such as cycle life and available capacity. (2) Charge–discharge rate Stable discharge current can guarantee the available capacity of the battery, while unstable discharge current will reduce the available capacity of the battery. (3) Battery aging Battery aging refers to the denaturation of some substances, electrolyte concentration change, ion migration speed change and current decrease caused by the physical and chemical changes of chemical substances in a battery, thereby resulting in increase in the battery internal resistance and capacity decrease. (4) Battery self-discharge Battery self-discharge refers to the voltage drop of the battery during standing. It is divided into reversible and irreversible cases. Irreversible self-discharge will reduce the battery capacity, resulting in shorter battery life. (5) Number of charge–discharge Battery charge–discharge is a process that must be experienced in the driving process of electric vehicles. The increase in the number of charge–discharge will inevitably

186

4 Energy Management Strategy Techniques for New Energy Vehicles

bring about the problem of battery aging. Large number of charge–discharge will accelerate the battery aging, reduce the battery capacity, and reduce the accuracy of battery SOC estimation.

4.1.2 Energy Management Strategies for Hybrid Electric Vehicles As the only energy source, the battery of a battery electric vehicle bears the total power load of the vehicle. This structure determines that only a simple energy management strategy can be designed to achieve energy distribution. The existing energy management strategies are mainly aimed at hybrid electric vehicles with internal combustion engine and electric motor. Such hybrid electric vehicles are intermediate products in the transition from traditional internal combustion engine vehicles to battery electric vehicles and fuel cell vehicles. It is the medium- and long-term goal of developing electric vehicles around the world to produce zero-emission electric vehicles using chemical or fuel cells. Hybrid electric vehicles will have the additional freedom to optimize the operating point of each power source for different objectives. As shown in Fig. 4.3, the hybrid electric vehicle can have greater adjustability by adjusting the engine operating point with the auxiliary motor, so that the engine is always in the high efficiency area. This way of improving the vehicle performance by adjusting the energy flow of different power sources is called energy management strategy (EMS). The energy management strategies of hybrid electric vehicles can be classified depending on the controlled object, control objective and considerations. It can be classified into SHEV energy management strategy, PHEV energy management strategy and SPHEV energy management strategy by the configuration of hybrid system and classified into the rule-based, optimization-based and intelligent control-based energy management strategies by the control mode. From most relevant 100 articles with keyword EMS and HEV from 2015 to 2020 searched from Google Scholar, the EMS types, vehicle configuration and model results are shown in Fig. 4.4. EMS can be divided into three categories: rule-based, optimization-based and intelligent control-based. The rule-based type can be classified into deterministic rule-based and fuzzy rule-based, and optimization-based can be classified into instantaneous optimization and global optimization. From the statistical results, it can be seen that the research hotspots are concentrated on instantaneous optimization EMS, global optimization EMS and intelligent control EMS; the construction hotspot is parallel and series; the models are dominated by passenger vehicles.

4.1 Introduction

187 Universal cha racteristics

Maximum torque

Maximum torque

Torque

Torque

Universal cha racteristics

Speed/(rad/s)

Speed/(rad/s)

Fig. 4.3 Schematic diagram of energy management strategy

Overview Deterministic rule-based Fuzzy rule-based Instantaneous optimization Global optimization Intelligent control

Series Parallel Series-parallel Power split

Passenger vehicle Commercial vehicle

Fig. 4.4 EMS type, vehicle configuration and model results

4.1.2.1

Energy Management Strategy Based on Deterministic Rules

The energy management strategy based on deterministic rules is the earliest control method applied to hybrid electric vehicles. The decision-making idea is to divide different modes according to the deterministic values of different input signals and then obtain the size of control variables for mode switching and power/torque distribution. Figure 4.5 shows the typical mode switching strategy and EV, CD and CS strategies. The general rule-based strategy is obtained by combining these four basic strategies. After settings of the corresponding rules, the optimization algorithm is used to select the parameters to achieve the best effect in the rules. From these strategies, it can be seen that the rule-based EMS is mainly formulated according to the following four points:

188

4 Energy Management Strategy Techniques for New Energy Vehicles Deterministic rule-based

Road load

Accelerator/brake pedal signal

SOC value

Divide the engine working interval

Speed-based

Torque-based

Baseline energy management

Threshol

Yes

No

No Yes

Engine

Pure

Loaded

Use engine MAP

Threshol

End

No Combined drive

Maintain

(a) Mode switching strategy

(b) EV strategy

No Yes

No Yes

No No No

Yes Yes Yes

Yes No

Yes

No

End

(c) CS strategy

Yes

End

(d) CD strategy

Fig. 4.5 Energy management strategy based on deterministic rules

(1) Electric braking is used instead of some traditional mechanical braking to realize braking energy recovery. (2) The motor drives the engine to start to avoid the low efficiency area when the engine self-starts. (3) Engine idle stop to reduce the engine idle fuel consumption. (4) Active charging and torque/power distribution are used to correct the operating point of the engine to avoid the engine working in the low efficiency area and improve the engine load rate. The operating modes of hybrid electric vehicles are usually classified into pure electric mode, engine mode, hybrid mode, regenerative braking mode and charging mode. Pure electric mode: When a hybrid electric vehicle starts at a high SOC or runs

4.1 Introduction

189

at a low speed, the engine is turned off and the vehicle is driven by the motor alone. Engine mode: When the vehicle is in medium load conditions, such as medium and high speed, and the engine is in the high efficiency area, the motor is turned off and the vehicle driven by the engine alone. Hybrid mode: When the vehicle is accelerating, climbing or in other high load conditions, in order to ensure efficient operation of the engine, the motor assists the engine to drive the vehicle. Regenerative braking mode: When the vehicle is in retarding braking, the driver steps down the brake pedal, which generates negative power demand, and absorbs braking energy as much as possible without affecting the braking safety of the vehicle. Charging mode: When the SOC of the battery is lower than a certain set value (set as 42%), the vehicle enters the charging mode, and the engine charges the battery through the generator to ensure that the battery power is maintained in the normal range, so as to prevent excessive consumption of the battery from damaging the battery life. Above is to divide the engine working area into high load, medium load and medium–low load areas, calculate the current required power and determine the corresponding working mode combined with the driver’s accelerator pedal opening and opening change rate. The specific rules are as follows: when the required power is in the high-load area, the hybrid mode is used to control the engine in the high-efficiency working area, and the insufficient power is supplied by the motor; if the required power is in the medium-load area, the engine mode is used, and the required power is supplied by the engine alone; if the required power is in the medium–low load area, the vehicle will enter the pure electric mode or the driving charging mode. Compared with traditional internal combustion engine vehicles, the hybrid electric vehicles with different structures have the fuel economy and emission performance greatly improved. According to different working conditions, the logic threshold method is applied to control the parallel hybrid power. The threshold is set to limit the engine and battery operating interval, control the engine operating in the high efficiency area and provide the required torque, and the motor acts as a load regulator. When the vehicle needs a large torque output, the motor is involved in driving; when a small torque output is needed, the vehicle is driven by the motor alone or the motor works as a generator to absorb the remaining torque of the engine and charge the battery, so that the battery SOC is maintained within a reasonable range. According to the speed and SOC, the operating conditions are divided, including starting or braking, low speed driving, normal driving, full load driving and deceleration coasting. According to the speed and SOC threshold control under different working conditions, the 100 km fuel consumption under certain working conditions is reduced by 37% compared with that of traditional vehicles while ensuring the dynamic performance. This paper studies the energy management strategies of SPHEV under different operating conditions. Based on the analysis of the working principle of the SPHEV, the operating conditions of the vehicles are classified into charging condition, discharging condition and braking condition, taking the maximization of the overall system efficiency as the main control objective. For charging and discharging conditions, an energy management system model is established with the maximization of the overall system efficiency as the main control objective; for

190

4 Energy Management Strategy Techniques for New Energy Vehicles

the braking condition, the energy management strategy is adopted with the maximization of regenerative braking energy recovery as the control objective, which reduces the fuel consumption by 36.95% compared with the traditional basic models. The energy management strategy based on deterministic rules is often formulated on the basis of the experience of engineers, the division of working modes and the static energy efficiency MAP, with simple and understandable idea, simple calculation and easy-to-implement method; however, it cannot adapt to the requirements of different operating condition changes and actual dynamic changes, and cannot realize optimal control. In order to find the optimization of performance and the real-time adaptability of working conditions, fuzzy control is integrated into rule control on this basis.

4.1.2.2

Energy Management Strategy Based on Fuzzy Logic Rules

The energy management system of a hybrid electric vehicle contains several subsystems and has the nonlinear time-varying characteristics, which can be managed and controlled by fuzzy logic rules. The energy management strategy based on fuzzy logic rules is to deal with nonlinear and uncertain problems by taking the advantages of strong robustness and real-time of the fuzzy control method. Based on the fuzzy logic rules, the working mode and power of hybrid electric vehicle are divided. The speed, SOC, torque and power are fuzzied to realize the rational control of the HEV energy management system and improve the overall performance of the vehicle. The energy management strategy based on fuzzy logic rules, instead of dependent on the accuracy of the system model, is of strong robustness and inference and more suitable for the control of complex hybrid nonlinear systems. However, it still needs to rely on empirical rules to achieve accurate control effect, and cannot guarantee the optimal control, so it is necessary to combine other intelligent control algorithms to improve the control performance. In order to achieve the global optimal control effect, more researchers have begun to pay attention to and explore the optimization-based energy management strategy.

4.1.2.3

Global Optimization-Based Energy Management Strategy

The optimization-based energy management strategy optimizes the control objective minimization by defining the energy cost function and combining the constraints. Usually, the fuel consumption of hybrid electric vehicles is taken as the control objective to form a single objective control under constraints, and also the emission, change in battery power and driving performance are taken as the control objectives simultaneously for multi-objective optimization control. At present, the optimization-based energy management strategy can be divided into two categories: one is the global optimization-based energy management strategy for energy optimization control under specific working conditions on the basis of static data table or historical data; the other is the energy management strategy that can generally

4.1 Introduction

191

guarantee local or instantaneous optimization on the basis of real-time status of the vehicle or the online control of current parameters. As shown in Fig. 4.6, the optimization-based EMS can be classified into global optimization EMS and instantaneous optimization EMS. The optimization based on the vehicle working condition is the global optimization EMS, and the optimization based on the real-time state of the vehicle is the instantaneous optimization EMS. The earliest global optimization is dynamic programming, which transforms a complex optimization problem into multi-level and single-step optimization selection problems. Subsequently, Pontryagin’s minimum principle for stochastic dynamic programming was developed. The instantaneous optimization methods include Equivalent Consumption Minimization Strategy (ECMS) and model predictive control (MPC). The most representative energy management strategies based on global optimization include dynamic programming (DP) control method, Pontryagin’s minimum principle (PMP) control method, genetic algorithm (GA) and energy management methods combined with other intelligent control methods. The energy management strategies based on global optimization usually control the energy distribution for a specific operating mode cycle, while the fuel economy of vehicles is often very dependent on the operating mode cycle, so such strategies has certain limitations, and are not ideal when applied in the practical control. Optimization-based (determine optimization objectives and constraints)

Global optimization (the whole cycle condition is known)

Dynamic programming

Constrained by engine fuel ti

Suitabl e for vehicle s with fixed routes

Instantaneous optimization (based on real-time vehicle status)

Pontryagin's Minimum Principle

Stochastic dynamic programming

Constrained by emissions

It can be used as the basis of fuzzy logic design

Real-time monitoring combined with the condition recognition technology

Principle of minimum equivalent fuel

Model prediction

Equivalent fuel consumption converted to engine fuel consumption

Maintai n the SOC value as the basis

Control strategy objectives (minimum fuel consumpti on, etc.)

Total fuel consumption model

SOC variation-based model

Average engine working efficiency

Average motor working efficienc y

Average battery working efficienc y

Motor equivalent fuel consumption model for battery charging and discharging

ECMS objective

Model predicti

Dynamic program ming

Work efficiency-based model

Engine fuel consum ption

Motor torque

SOC variati on

SOC variation-based equivalent fuel consumption model

Fig. 4.6 Classification of optimization-based energy management strategies

Accel erator pedal positi on

Deman ded torque predict ion

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4 Energy Management Strategy Techniques for New Energy Vehicles

1. DP energy management method At present, the energy management in the steady state process of hybrid electric vehicles has been more mature, especially the energy management algorithms under specific working conditions. The most representative energy management method is based on dynamic programming. The dynamic programming method, as a mathematical method to solve the optimization problem in the decision-making process, was proposed by American mathematician Bellman in the early 1950s when he studied the optimization problem in the multi-stage decision-making process. It is an optimization method that transforms a multi-stage process into a series of single-stage problems and solves them one by one by means the relationship between the stages. The DP algorithm has been used for energy management of hybrid electric vehicles since 2000, and is recognized as an ideal hybrid energy management method that can achieve global optimization and better improve fuel economy. The application of DP algorithm is usually aimed at the known specific cycle conditions, and it is necessary to master the future cycle condition information in advance. Moreover, with a “curse of dimensionality” with large computation amount and long time consumption, the DP algorithm cannot realize real-time control, so its practical application is limited. However, the DP algorithm has an undeniable control effect, It is often used to optimize the management of common or fixed driving routes, such as hybrid buses and hybrid commuter vehicles, and is also used as a standard to evaluate the advantages and disadvantages of other control algorithms. Although the practical application of the DP algorithm is limited and affected, there are still a lot of researches devoted to the improvement and exploration of DP algorithm, mainly reflected in the following three aspects: ➀ Reduction of computing time and memory requirements; ➁ Identification and prediction of future operating condition information; ➂ Improvement of DP algorithm or combination with other technologies. 2. Energy management method based on Pontryagin’s Minimum Principle Pontryagin’s minimum principle, also known as the maximum principle, was put forward by Pontryagin, a Soviet scholar in the mid-1950s. It is a method used to solve the optimal control problem with control and state constraints. This method overcomes the defect that the variational method cannot find the extremum of the functional of the constrained control variables and objective functions, and is the extension and generalization of the variational method. The energy optimization problem of hybrid electric vehicles can come down to an optimal control problem of time-varying nonlinear system with constraints. The Hamil-tonian equation obtained from the mathematical model of the hybrid electric vehicles, based on certain assumptions, can obtain the globally optimal solution by using Pontriagin’s minimum principle, which, compared with DP algorithm, greatly reduces the amount of calculation and is more suitable for real-time control. Therefore, after DP algorithm, a lot of researches and explorations have been carried out on the application of Pontriagin’s minimum principle in the energy management system of hybrid electric vehicles.

4.1 Introduction

193

3. Energy management method based on genetic algorithm Genetic algorithm is an adaptive probabilistic iterative search algorithm developed on the basis of the mechanism of natural selection and natural genetics. It can quickly achieve global convergence, find the optimal value, and is suitable for hybrid electric vehicle energy management optimization. It is easy to form multi-objective optimization problems and improve the comprehensive performance. However, the algorithm often needs prediction of the driving cycle conditions in advance, and the calculation amount is not significantly reduced, so there are still some limitations in its practical application.

4.1.2.4

Energy Management Strategy Based on Instantaneous Optimization

The idea of instantaneous optimization was born with the research of real-time energy management control methods. The main starting point is to guarantee minimum energy consumption or minimum power loss in the current time energy management process, obtain the instantaneous optimal operating point based on the optimum curve for operation of engine (fuel consumption, power, efficiency MAP) and control each hybrid state variable for dynamic energy distribution, the engine, so that the engine and motor work at the instantaneous optimal state point. The energy management method based on instantaneous optimization optimizes and controls the energy flow of the vehicle in the instantaneous working condition without the need for knowing the future driving information of the vehicle in advance, and is not restricted by the specific working condition cycle. It has relatively small calculation amount and is easily applied. However, the instantaneous optimization is not equal to the overall optimization, so the global optimization cannot be guaranteed. The commonly used optimization methods include energy management method based on ECMS, energy management method based on model predictive control and energy management method based on other intelligent control. 1. Energy management method based on equivalent consumption minimum strategy (ECMS) The equivalent consumption minimum strategy (ECMS) is to convert the energy consumption of the motor into the fuel consumption, i.e. equivalent fuel consumption, in a certain instantaneous working condition, introduce the equivalence factor to establish the total fuel consumption cost function of each instant, or optimize the emission through the weighting factor and make a multiple objective function before optimization solution. Therefore, it is also called cost-based energy management strategy. The energy management method based on ECMS can not only realize realtime control, but also compromise the dynamic performance, fuel economy and emission performance of the vehicle. However, this method generally does not take into account the dynamic change of battery SOC, but is based on the assumption that the engine compensates the battery power under the same conditions. It cannot guarantee the global optimization.

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2. Energy management method based on model predictive control Energy management method based on model predictive control (MPC) is to convert the global optimization control of the fuel economy in the whole driving cycle to the local optimization control in the prediction area through online identification and optimization of vehicle dynamic parameters, and update the prediction of the running state or control parameters of the vehicle in the next time domain by constantly rolling optimization, so as to obtain the optimization results. The MPC method is of strong robustness and suitable for the control of uncertain and nonlinear dynamic systems, so it can be used for energy management of hybrid electric vehicles. In addition, the MPC can also be combined with other intelligent algorithms, such as the introduction of neural network, artificial intelligence, fuzzy control and other theories, to obtain more excellent control performance. 3. Energy management method based on other intelligent control The control methods used for energy management also include neural network and game theory. Energy Management based on neural network: with strong information processing capability and function approximation capability, the neutral network is used for modeling, control, reasoning and optimal computation of complex nonlinear objects which are difficult to describe accurately. Moreover, with the function of self-organization and self-learning, it is often combined with other control methods for the optimization of controller parameters. Energy management based on game theory: Game theory (GT) is used for energy management of hybrid electric vehicles. Usually, the energy distribution between the engine and the motor is regarded as a competitive or adversarial game behavior to be controlled based on the feedback of Stackelberg equilibrium principle.

4.2 Powertrain Modeling 4.2.1 Energy Conversion System Model The internal combustion engine is the most common power plant used in automobiles. It will remain the main vehicle power plant for the foreseeable future. In hybrid electric vehicles, the internal combustion engine will also be the preferred primary power source. However, unlike in the traditional vehicles, the engine in the hybrid electric vehicles car runs at high power for a long period of time without having to change its power output frequently. To date, engines with specific designs and controls for hybrid electric vehicles have not been fully developed. Here we will review the commonly used four-stroke internal combustion engine and other forms of engines that can be reasonably applied to hybrid electric vehicles, such as two-stroke engine, rotor engine, Stirling engine and gas turbine. The four-stroke spark-ignition internal combustion engine is composed of two major mechanisms and five major systems, namely, crankshaft and connecting rod

4.2 Powertrain Modeling

195

mechanism, valve mechanism, cooling system, lubrication system, ignition system, fuel supply system and starting system. The crankshaft and connecting rod mechanism converts the gas pressure generated by fuel combustion into the torque of crankshaft rotation through the piston and connecting rod, and uses the inertia of the flywheel to complete the four auxiliary strokes of air intake, compression, work and exhaust. The valve mechanism timely opens and closes the inlet and exhaust valves according to the engine work sequence and the requirements for working cycle of each cylinder, so that the combustible mixture or fresh air enters the cylinder, and discharges the exhaust gas. Fuel supply system: The function of the gasoline engine fuel supply system is to prepare a certain amount and concentration of gas mixture according to the requirements of the engine, supply it into the cylinder, and discharge the exhaust gas from the cylinder after combustion; the function of the diesel engine fuel supply system is to supply the diesel and air into the cylinder respectively, form a gas mixture and burn it in the combustion chamber, and finally discharge the exhaust gas after combustion. The function of the lubrication system is to deliver a fixed amount of clean lubricating oil to the surface of the parts in relative motion, so as to achieve liquid friction, reduce friction resistance, reduce wear of the parts, and clean and cool the surface of the parts. The lubrication system is usually composed of the lubricating oil channel, oil pump, oil filter and some valves. The function of the cooling system is to dissipate the heat absorbed by the heated parts in time to ensure that the engine works at the most appropriate temperature. The cooling system of the water-cooled engine is usually composed of the cooling water jacket, pump, fan, water tank and thermostat. In a gasoline engine, the combustible gas mixture in the cylinder is ignited by the electric spark. For this purpose, a spark plug is installed on the cylinder head of the gasoline engine, with the head extending into the combustion chamber. All the equipment that can produce spark between the spark plug electrodes on time is called ignition system. The ignition system usually consists of the battery, generator, distributor, ignition coil and spark plug. Starting system: To make the engine transition from the static state to the working state, the engine crankshaft must be rotated first with external force, so that the piston makes reciprocating motion. The combustible gas mixture in the cylinder shall burn and expand to do work, pushing the piston down to rotate the crankshaft, so that the engine can run by itself and the working cycle can be carried out automatically. The air/fuel mixture formed in the intake manifold enters the cylinder and burns to generate heat, which rapidly increases the temperature and pressure in the cylinder. The piston is squeezed to move downward, and the connecting rod converts the linear motion of the piston into the rotational motion of the crankshaft. As shown in Fig. 4.7, the four-stroke spark-ignition internal combustion engine has four distinct processes corresponding to the four strokes of the piston: The intake valve opens, the exhaust valve closes, the piston moves down the cylinder, and the air/fuel mixture that forms the intake stroke (cylinder filling process) in the intake manifold is sucked. The quasi-static model of engine is established by integrating the theories of dynamics, thermodynamics and fluid mechanics. Fuel consumption is the integral of fuel consumption rate against time, i.e.

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Fig. 4.7 Working process of four-stroke spark-ignition internal combustion engine

 Fuel =

tf

m f (ωe , Te )dt

(4.1)

t0

where ωe and T e are the engine speed (rad/s) and torque (N·m), respectively; mf is the engine fuel consumption rate.

4.2.2 Energy Storage System Model 4.2.2.1

Fuel Cell

The fuel cell is an electrochemical device that directly converts the energy generated by chemical reaction between the hydrogen and oxygen into electricity. There are many types of fuel cells available, and the PEM fuel cell is considered the most promising option for automobile applications due to its high power density, low operating temperature (around 80 °C), and high overall efficiency. The fuel cell modeling can be based on the lookup table index to the polarization curve to characterize the performance of the fuel cell stack. No matter how complex the system, the model provides a specific net power for a set amount of fuel consumed. Figure 4.8 shows the net power and efficiency data for a PEM fuel cell stack built in ADVISOR. The performance of auxiliary systems, such as the characteristics of the air compressor and fuel pump, can also be represented by the polarization curve derived from ADVISOR experimental data. The power delivered by a fuel cell system is the difference between the power generated by the fuel cell stack and the power consumed by the auxiliary system. The fuel cell stack model can also be built in a more complete way through the co-simulation link between ADVISOR and Gctool.

197

Efficiency/(%)

4.2 Powertrain Modeling

Power/kW

Fig. 4.8 Net power and efficiency of 50 kW fuel cell system model

In this case, the electrochemical, thermal and mass transfer properties can be incorporated. It should be pointed out that such a detailed model is not necessary for the analysis of the overall vehicle system-level performance.

4.2.2.2

Storage Battery

One of the biggest challenges in power transmission is to enable the amount of stored electricity to be used in the required amount at the required time. The battery has a high energy density compared to its alternatives and can be recharged to provide regenerative braking capability. The electrochemical properties of the battery are highly nonlinear and dependent on many factors, such as SOC, SOH, running time, temperature, aging, load curve and charging algorithm. To make the supplied energy suitable for all-electric range (AER), tens to hundreds of batteries shall be connected in series or parallel to achieve the desired voltage and current ratings of the battery pack. This will lead to more prominent nonlinear characteristics of the battery. In addition, there are some phenomena that can only be observed in the battery pack, but not in individual batteries, such as heat imbalance in the battery pack. Three basic battery models: ideal model, linear model and Thevenin model, as shown in Fig. 4.9. The ideal model basically ignores the internal parameters of the battery, so it is very simple. Figure 4.9a shows an ideal battery model, which basically consists of voltage source only. The linear model is by far the most widely used battery model. As shown in Fig. 4.9b, the model consists of an ideal battery with open-circuit voltage and equivalent series resistance (ESR). The voltage rating can be obtained by conducting an open circuit test or load test on a fully charged battery. Although this model is widely used, it still does not take into account the influence of the SOC and the electrolyte concentration change on the internal impedance of the battery.

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(a) Ideal model

(b) Linear model

(c) Thevenin model

Fig. 4.9 Battery model

The Thevenin model consists of open-circuit voltage, internal resistance, capacitance and overvoltage resistance. As can be seen from Fig. 4.9c, the capacitance depicts the capacitance of the parallel plate, while the resistance depicts the nonlinear resistance provided by the parallel plate to the electrolyte. In this model, all elements are assumed to be constant, so this model is the least accurate. However, a new method for evaluating batteries can be introduced from this perspective. The improved model is based on the combined load operation within a certain range, and the main circuit is composed of five sub-circuits: ➀ DC voltage source, indicating the voltage in the cell; ➁ Cell polarization, ensuring the availability of active materials in the battery; ➂ Influence of temperature on battery terminal voltage; ➃ Internal resistance of battery, mainly depending on the voltage and SOC of the battery cell; ➄ Voltage source with the voltage value of 0 V, used to record the current value of the battery. This simulation model can be well adapted to different charge and discharge modes. It is quite accurate, and can be further used as a model for nickel–cadmium and lithium-ion batteries applied in hybrid electric vehicles and other traction equipment. It is only required to be modified in a small part to change the parameters such as load status, current density and temperature.

4.2.2.3

Supercapacitor

The supercapacitor, also known as double-layer capacitor, can produce very high capacitance per unit area of the contact surface between its electrode and the electrolyte. Such capacitor typically has a capacitance value of 400–800 F and a very low resistivity (about 10−3 Ω·cm). The supercapacitor works at high energy density and is commonly used in space communication, digital mobile phones, electric and hybrid electric vehicles. In some cases, a hybrid system with a battery next to a supercapacitor can prepare an energy storage system that has a number of advantages.

4.2.2.4

Super High Speed Flywheel

Flywheel is the most common energy storage device in different power system configurations. With the continuous improvement of the digital signal processing (DSP)

4.2 Powertrain Modeling

199

Rectifier/inverter

DC-DC converter

Motor/generator Flywheel

Rectifier/inverter

AC power supply

Fig. 4.10 Typical FESS as voltage regulator and UPS

and microprocessor technology, together with the development of magnetic materials technology, the performance of the flywheel energy storage system (FESS) is more outstanding. Embedding an FESS in a system has many advantages over other auxiliary storage devices, such as battery. Due to its specific battery characteristics, the FESS can produce the best charge and discharge state. This fact promotes the search for battery management optimization. A rotating flywheel can use its inertia to convert mechanical energy into kinetic energy for storage. The FESS consists of the rotor, motor/generator system and matching accessories. Figure 4.10 shows an FESS used as a voltage regulator and an uninterruptible power supply (UPS). The system shown in Fig. 4.10 has three main operating modes: charging mode, voltage regulation mode, and UPS mode. The motor/generator (M/G) device stores energy in the form of rotor moment of inertia, and, at some appropriate points in the system operation, retrieves this stored energy according to the demands of the load. Therefore, the M/G device is a high-speed device, which basically operates in the running state of the motor when the flywheel is charged and in the generator mode when the flywheel is discharged. The motor used for the M/G device is brushless direct current (BLDC) motor with appropriate ratings. The following formula can simulate an FESS: Vx = Ri x + (L − M)

di x + Ex dt

(4.2)

where V, i and E are the voltage, stator current and counter electromotive force of the brushless DC three-phase motor respectively; R, L and M are the resistance, the self-inductance coefficient and mutual inductance coefficient of stator winding respectively. The counter electromotive force is proportional to the mechanical speed ω and angle. In order to electrically simulate the FESS that works together with the power electronic intensive system, it is very important to obtain the equivalent

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Fig. 4.11 Equivalent circuit of FESS

electrical model. Therefore, a very important mathematical formula is given here to describe the above system, as follows: ⎧ di ⎨ V = Ri + L dt + aω + bω + TL T = ai = Jr di dt ⎩ em TL = J dω dt

(4.3)

where V is the voltage at both ends of the motor wiring terminal; i is the current flowing through the motor; ω is rotor speed; T em is the electromagnetic torque applied to the rotor; T L is the mechanical torque applied to the rotor by the flywheel; J r is the equivalent moment of inertia of the rotor; J is the moment of inertia of the flywheel; R and L are armature resistance and self-inductance coefficient, respectively; a is the ratio of rated voltage to rated speed of the motor; b is the mechanical resistance coefficient. The above three formulas together constitute the equivalent circuit described in Fig. 4.11. It should be noted that the circuit parameters used are basically those that define the FESS. Therefore, on the whole, Fig. 4.11 is the FESS described by the electrical equivalent. This greatly simplifies the simulation of the FESS with an electrical system, as such an electrical model can be installed and analyzed on any commonly used electrical CAD simulation software.

4.2.3 Vehicle Dynamic Model 4.2.3.1

General Description of Vehicle Motion

The motion characteristics of a vehicle in its direction of travel depend entirely on the total acting force in that direction. Figure 4.12 shows the forces acting on a vehicle moving uphill. The traction force F on the contact surface between the drive wheel’s tyre and the road surface pushes the vehicle forward. This acting force is generated by the torque of the power plant and transmitted through the transmission device to drive the drive wheel eventually. When the vehicle moves, it will be subject to resistance that will hinder its movement. This resistance usually includes tyre rolling

4.2 Powertrain Modeling

201

Fig. 4.12 Force acting on a vehicle moving uphill

resistance, air resistance and climbing resistance. According to Newton’s second law, the vehicle acceleration can be described as ∑ ∑ F− Fi dv = (4.4) dt δM where v is the vehicle speed; ∑F is the total traction force of the vehicle; ∑F 1 is the total resistance; M is the total mass of the vehicle; δ is the rotational inertia coefficient that equivalently converts the moment of inertia of the rotating component into the translational mass.

4.2.3.2

Vehicle Driving Resistance

On hard ground, the tyre rolling resistance is basically caused by the hysteresis of the tyre material. Figure 4.13 shows that the force P acting on a stationary tyre passes through its center. In this way, the pressure on the contact surface between the tyre and the ground is symmetrically distributed along the center line, and the resulting reaction force Pz is collinear with P. During loading and unloading, the load P as a function of the tyre deformation z is shown in Fig. 4.14. Due to the hysteresis of rubber material under deformation, for the same deformation Z, the load under loading is greater than that under unloading (see Fig. 4.14). When the tyre rolls, as shown in Fig. 4.15a, the front part of the contact surface is loaded, while the rear part is unloaded. Hysteresis causes the asymmetric distribution of the ground reaction force, so that the pressure on the front part of the contact surface is greater than that on the back part. The result of this phenomenon is that the ground reaction force is shifted forward. The forward offset ground reaction force and the vertical load applied to the wheel center produce a torque that resists the wheel roll. On soft ground, the rolling resistance is basically caused by the deformation of the ground,

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Fig. 4.13 Pressure distribution on the contact surface

Fig. 4.14 Force acting on the tyre as a function of tyre deformation under loading and unloading

Force P Load

Unload

Deformation z

as shown in Fig. 4.15b. At this point, the ground reaction force is almost completely shifted to the front half of the contact surface. The torque generated by the forward offset of the resultant ground reaction force is called the rolling resistance moment and can be expressed as Tt = Pa

(4.5)

To keep the wheel rolling, the force F acting on the center of the wheel shall be balanced with the rolling resistance moment, that is, the force shall be F=

Tt Pa = = Pf rd rd

(4.6)

where r d is the effective radius of the tyre; f = a/r d is called the rolling resistance coefficient. In this way, the rolling resistance moment can be replaced by a horizontal force acting on the center of the wheel in the direction opposite to the direction of wheel motion.

4.2 Powertrain Modeling

203

Direction of motion

Direction of motion

(b) Soft ground

(a) Hard ground Fig. 4.15 Tyre deflection surface and its rolling resistance

The rolling resistance coefficient f depends on the tyre material, tyre structure, tyre temperature, tyre inflation pressure, the inclination angle a of the ground, the geometry of the outer tread, surface roughness, pavement material and the presence or lack of liquid on the road surface and other factors. The air resistance is expressed as FW =

1 ρ AC D v 2 2

(4.7)

where C D is the coefficient of air resistance representing the shape features of the vehicle body; v is the wind velocity component in the direction of vehicle motion, which is positive when its direction is the same as the direction of vehicle speed, and negative when it is opposite. For several typical vehicle forms, the coefficient of air resistance is shown in Table 4.1.

4.2.3.3

Vehicle Dynamic Equation

Longitudinally, as shown in Fig. 4.12, the main external forces acting on the twoaxle vehicle include the rolling resistance F and F n of the front and rear tyres, which are characterized by the rolling resistance moment T and T n , respectively; the air resistance is F w ; the climbing resistance is F g (i.e. Mgsina) and the traction force of the front and rear wheels is F and F r . For a RWD vehicle, F is zero; for an FWD vehicle, Fr is zero. Thus, the vehicle dynamic equation is: M

dv = (F + Fr ) − FW − Fg (F + Fn ) dt

(4.8)

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4 Energy Management Strategy Techniques for New Energy Vehicles

Table 4.1 Coefficient of air resistance for different vehicle forms Coefficient of air resistance

Vehicle form Open-type

0.5–0.7

Covered truck

0.5–0.7

Floating car body

0.4–0.55

The wedge-shaped body, headlights 0.3–0.4 and bumper are integrated inside the body, and the body understructure is covered to optimize the cooling airflow The headlights and all wheels are inside the body, and the body understructure is covered

0.2–0.25

Type K (small blocking surface)

0.23

Optimized streamlined design

0.15–0.20

Truck and large goods vehicle

0.8–1.5

Bus

0.6–0.7

Streamlined bus

0.3–0.4

Motorcycle

0.6–0.7

4.3 Feature Analysis of Typical Working Conditions of Key Components …

205

4.3 Feature Analysis of Typical Working Conditions of Key Components Under Different Energy Management Strategies 4.3.1 Feature Analysis of Two Cycle Conditions of the Sample Vehicle

Acceleration/(m/s2)

Vehicle speed/(km/h)

In order to explore the difference of the fuel consumption and emission of heavy-duty PHEV under China Heavy-duty Commercial Vehicle Test Cycle (CHTC) and China World Transient Vehicle Cycle (C-WTVC) conditions, the statistical characteristics of the two conditions are firstly analyzed. Figure 4.16 shows the comparison of speed and acceleration in two conditions. Figure 4.17 shows the speed distribution statistics of the two conditions. The speed is lower and the acceleration is higher in urban areas in CHTC, indicating that urban conditions are more congested. They have the same characteristics in the suburbs and on the highway. Relatively speaking, the deceleration in the urban area and suburb is greater in CHTC than in C-WTVC. This fully shows that vehicles have great potential in energy recovery in CHTC. The heavy-duty vehicles mainly run in the medium–low speed zones under CHTC compared with C-WTVC, in which 0–10 km/h accounts for 26.61%. According to the speed and acceleration, the two conditions are divided into three sub-conditions: idle, drive and braking. The statistics of sub-conditions of the two conditions are shown in Table 4.2. CHTC represents more congested traffic. Braking and idle speed subconditions accounted for 49.22% and 48.83% respectively under the two conditions, indicating that these two conditions have great energy saving potential.

Time/s (a) Comparison of speed under two conditions

Fig. 4.16 Comparison of two conditions

Time/s (b) Comparison of acceleration under two conditions

4 Energy Management Strategy Techniques for New Energy Vehicles

Proportion

206

Speed section/(km/h)

Fig. 4.17 Speed distribution under two conditions

Table 4.2 Sub-condition statistics of two conditions Sub-condition

Idle

Drive

Braking

Total

C-WTVC (%)

10.33

51.17

38.50

100.00

CHTC (%)

14.28

50.78

34.94

100.00

4.3.2 Feature Analysis of Typical Working Conditions of Key Components Under Different Strategies When the structural parameters of the hybrid system are determined, the distribution of energy source power/torque depends on the energy management strategy when the road conditions request the vehicle’s speed and acceleration during vehicle driving. In order to exclude the influence of each control parameter in various strategies on the working condition distribution of key components, the energy management strategy selected here adopts the control parameters when the energy consumption is optimal. Here, only a 6t 1.5 T extended-range cargo van is analyzed, so the condition of the key components is the power distribution between the engine and battery.

4.3.2.1

Power-Following Energy Management Strategy

First, a power-following energy management strategy is formulated, as shown in Fig. 4.18. Its working mode is as follows:

4.3 Feature Analysis of Typical Working Conditions of Key Components …

207

Fig. 4.18 Schematic diagram of power-following energy management strategy

Required power/kW

If the battery SOC is at the set upper limit and the required power is lower than the minimum engine power (area A), the battery alone provides power to the motor and the engine shuts down. If the battery SOC is between the set upper and lower limits, and the required power of the motor is small (area B), the vehicle state is maintained at this time. If the battery SOC is lower than the set lower limit (area D), all the power required by the vehicle is supplied by the engine, and the balanced power is used to charge the battery pack. If the battery SOC is greater than the set lower limit and the required power of the motor is greater than the minimum output power of the engine (area C), then the battery and APU (auxiliary power system) work simultaneously to provide electric energy for the motor. Figure 4.19 shows the power distribution between the battery and the engine, and Fig. 4.20 shows the power distribution between the engine and the power battery. It can be seen that the engine power is mainly concentrated in the intervals [0,10) and [30,40), of which the interval [0,10) is mainly because of many engine outages, and the interval [30,40) is close to the efficient working interval of the engine. The strategy is more distributed here, which indicates that it is reasonable.

Power/kW

Fig. 4.19 Power distribution between battery and engine (1)

Engine power Battery power Required power

Time/s

4 Energy Management Strategy Techniques for New Energy Vehicles

Distribution ratio/(%)

Distribution ratio/(%)

208

Power interval/kW (a) Engine power distribution

Power interval/kW (b) Power battery power distribution

Fig. 4.20 Power distribution between engine and power battery (1)

4.3.2.2

Fuzzy Rule-Based Energy Management Strategy

Fuzzy Logic Control (Fuzzy Control) is a kind of computer digital control technology based on fuzzy set theory, fuzzy language variables and fuzzy logic reasoning. In 1965, L.A. Zadeh from the US founded the fuzzy set theory; in 1973, he gave the definition of fuzzy logic control and related theorems. Compared with traditional control methods, the fuzzy control has the following outstanding characteristics: (1) Fuzzy control is a rule-based control, which uses the language control rule directly based on the control experience of the field operator or the knowledge of relevant experts. An accurate mathematical model of the controlled object is not required in the design, thus making the control mechanism and strategy easy to accept and understand, easy to design and apply. (2) Based on the qualitative understanding of industrial process, it is easy to establish the language control rules, so fuzzy control is very suitable for those objects whose mathematical models are difficult to obtain, whose dynamic characteristics are difficult to master or whose changes are very significant. (3) Because of the different starting points and performance indexes, the modelbased control algorithm and system design method are easy to differ greatly, but a system language control rule is relatively independent. The fuzzy connection between these control rules can be used to find a compromise choice, so that the control effect is better than that of the common controller. (4) Fuzzy control is designed based on enlightening knowledge and language decision rules, which is helpful to simulate the process and method of artificial control, enhance the adaptive ability of the control system and make it have a certain level of intelligence. (5) The fuzzy control system is highly robust and the influence of disturbance and parameter variation on the control effect is greatly weakened, especially suitable for nonlinear, time-varying and pure lag system control.

4.3 Feature Analysis of Typical Working Conditions of Key Components …

209

Combined with the energy management strategy of hybrid electric vehicles, the energy management strategy based on fuzzy control does not need a specific mathematical expression of engine and battery and how to allocate the required power, but can realize the reasonable allocation of variables, so that the engine has higher working efficiency and longer battery life. The EREV has complex structure and many variables, which means that the strategy is required to have high stability and strong anti-interference ability, and the fuzzy control has good robustness, which can meet the EREV requirements for strategy. The required power of the vehicle and the battery SOC are taken as the input variables of the fuzzy control strategy, and the engine power is obtained by inference of the fuzzy inference system, so that the purpose of power allocation can be achieved. Here, the required power and the battery SOC are taken as the inputs of the fuzzy controller, and the domain of discourse of the required power Preq is divided into 7 subsets, i.e. {NB, NM, NS, ZO, PS, PM, PB}. For the input variable SOC, its domain of discourse is set as [0, 1] according to the actual range, and it is divided into five subsets, i.e. {BL, SL, M, SH, BH}. The output variable of the fuzzy controller the engine power Pe , whose domain of discourse is determined according to the lowest fuel curve of the MAP and whose range is [0, 40]. The domain of discourse is divided into five fuzzy subsets, i.e. {NS, ZO, PS, PM, PB}. According to the above design, the membership function graph of the fuzzy strategy as shown in Fig. 4.21 can be obtained. A triangle membership function is adopted here because of its simple structure, obvious effect and fast operation, and its function expression is as follows: ⎧ ⎪ 0 x ≤a ⎪ ⎪ ⎨ x−a a ≤ x ≤ b b−a f (x, a, b, c, d) = c−x ⎪ c−b b ≤ x ≤ c ⎪ ⎪ ⎩0 x ≥ c

(4.9)

where a and c represent the left and right end points of the bottom edge of the triangle, and b represents the vertex of the triangle. The centroid method is selected as the defuzzification method, in which, the center of gravity of the area enclosed by the membership function curve and the abscissa is taken as the final output value of fuzzy reasoning. The function expression is as follows:  vμv (v)dv (4.10) v0 =  μv (v)dv The membership control rules of the fuzzy strategy are shown in Table 4.3, and their reasoning form is of the “if and then” structure.

4 Energy Management Strategy Techniques for New Energy Vehicles

Membership degree

Membership degree

210

Membership degree

Engine power

Required power

Fig. 4.21 Graph of membership function of fuzzy strategy

Table 4.3 Control rule table SOC

P NB

NM

NS

ZO

PS

PM

PB

BL

PB

PB

PB

PB

PB

PB

PB

SL

PM

PM

PM

PS

PB

PB

PB

M

NS

ZO

PS

PM

PM

PB

PB

SH

NS

ZO

ZO

PS

PS

PS

PB

BH

NS

NS

NS

ZO

PS

PM

PM

Figure 4.22 shows the power distribution between the battery and the engine, and Fig. 4.23 shows the power distribution between the engine and the power battery. It can be seen that the engine power is mainly concentrated in the intervals [10, 30), and the interval [10, 30) is the power fluctuation range of the engine at the high efficiency operating point. The strategy is more distributed here, which indicates that it is reasonable.

4.3 Feature Analysis of Typical Working Conditions of Key Components …

211

Power/kW

Engine Battery Required power

Time/s

Distribution ratio/(%)

Distribution ratio/(%)

Fig. 4.22 Power distribution between battery and engine (2)

Power interval/kW

(a) Engine power distribution

Power interval/kW

(b) Power battery power distribution

Fig. 4.23 Power distribution between engine and power battery (2)

4.3.2.3

Equivalent Consumption Minimum Strategy (ECMS)

The minimum fuel consumption that can be obtained by a hybrid system under certain driving conditions according to the optimal control theory can be obtained by Eq. (4.11). Jmin = min

N −1 ∑

(m f c (T f c (t), ω f c (t)) · Δt + m mc_eq (Tmc (t), ω(t)))

(4.11)

j=1

where mfc represents the fuel consumption rate of the engine at the speed and torque at a certain moment; mfc_eq represents the equivalent fuel consumption of the motor at the speed and torque at a certain moment. The solution to this equation can be used

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4 Energy Management Strategy Techniques for New Energy Vehicles

as a control command for the hybrid electric vehicle to obtain the global minimum fuel consumption under the target driving condition, provided that the target driving condition is known in advance. Therefore, the ECMS is proposed: Jmin =

N −1 ∑

min(m f c (T f c (t), ω f c (t)) · Δt + m mc_eq (Tmc (t), ω(t)))

(4.12)

j=1

There are two key points to the ECMS: ➀ Equivalent fuel consumption—For a non-plug-in hybrid electric vehicle, the electric energy cannot be obtained from the outside, and the battery SOC shall be maintained within a stable range, The electric energy consumed by the battery (not including the energy recovered by regenerative braking) during the vehicle driving will be compensated at some point in the future by the extra fuel consumed by the engine to drive the electric motor to charge the battery. Therefore, it is necessary to establish an equivalent relationship between the current power consumption and the additional fuel consumption to compensate for this part of power consumption in the future, so as to transform them; ➁ Instantaneous optimization—Under the premise of satisfying the vehicle dynamic performance, the power is distributed between the motor and engine in real time according to the state of the hybrid vehicle and the required torque, so as to achieve the optimal fuel economy of the vehicle, and meet the following conditions: Jmin =

N −1 ∑

min(m fc (Tfc (t), ωfc (t)) · Δt + m mc_eq (Tmc (t), ω(t)))

j=1

Figure 4.24 shows the power distribution between the battery and the engine. Figure 4.25 shows the power distribution between the engine and the power battery. The engine power changes greatly under this strategy. However, it can be seen from Fig. 4.25 that the power is mainly distributed within the interval [40, 50) except for idle speed and stop area, indicating that the strategy controls the engine power near, but not at, the optimal operating point, which indicates that the strategy takes into account the battery charging efficiency. To sum up, we have used three strategies of optimal parameters to analyze the working conditions of key components, counted their characteristics respectively, and compared the typical working conditions of key components of the power-following strategy, fuzzy rule and ECMS under CHTC.

4.4 Optimal Energy Management Strategies for Hybrid Electric Vehicles

213

Power/kW

Engine Battery Required power

Time/s

Distribution ratio/(%)

Distribution ratio/(%)

Fig. 4.24 Power distribution between battery and engine (3)

Power interval/kW

(a) Engine power distribution

Power interval/kW

(b) Power battery power distribution

Fig. 4.25 Power distribution between engine and power battery (3)

4.4 Optimal Energy Management Strategies for Hybrid Electric Vehicles 4.4.1 Energy Management Strategy Based on Dynamic Programming Algorithm Optimization 4.4.1.1

Analysis of Dynamic Programming Problems of Energy Management Strategy

The goal of energy management strategy optimization is to achieve the optimal vehicle fuel economy or emission performance within a driving range (the fuel

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4 Energy Management Strategy Techniques for New Energy Vehicles

Motor

Driving cycle

hybrid Vehicle

Vehicle

Electric

State change

Required power

Acceleration

Engine

Fuel consumption

Time

Fig. 4.26 Schematic diagram of energy flow in hybrid electric vehicle

economy is taken as the optimization objective in this section), provided that the future road condition information of the driving cycle or driving trajectory is available. Figure 4.26 is the schematic diagram of the energy flow in a hybrid electric vehicle. If a certain driving cycle is known, the acceleration and speed trajectory of the driving cycle can be obtained. For a specific vehicle, the required power (traction power or torque) along the driving cycle time can be obtained. The task of energy management is to rationally allocate energy according to the characteristics of the power system according to the required power at each moment, so as to achieve the goal of minimizing the cumulative fuel consumption in the whole driving cycle, while satisfying a variety of system constraints. It is clear that this is a global optimization problem for strongly nonlinear systems under multiple constraints. However, the theory of dynamic programming proposed by American mathematician R. Bellman et al., is a global optimization method that transforms a complex decision-making problem into a series of sub-stage decisionmaking problems. Using the numerical iterative solution method, it is suitable for analytical or numerical system models, and has been widely used to solve global optimization problems of dynamic systems under complex constraints. Since the dynamic system with the dynamic programming solved using the numerical method presents a good optimal control trajectory with the driving condition change, the system equation needs to be discretized with the driving condition change: x(k + 1) = f (x(k), u(k))

(4.13)

where x is the state variable of the system; u is the control variable. For the hybrid electric vehicle studied in this section, it can be written as: S OC(k + 1) = f (S OC(k), TE M (k), TI C E (k), G(k))

(4.14)

where SOC represents the state of charge of battery; T EM and T ICE represent the torque of motor and engine respectively; G represents the transmission gear. Optimization objective: J = min

N ∑ k=1

[L(x(k), u(k))]

(4.15)

4.4 Optimal Energy Management Strategies for Hybrid Electric Vehicles

215

where L is the optimized cost function. Our optimization objective is to minimize the cumulative fuel consumption during the driving cycle, so it can be written as: J = min

N ∑

[ f uel(S OC(k), TE M (k), TI C E (k), G(k))]

(4.16)

k=1

In this section, a hybrid electric city bus is taken as the prototype to establish a longitudinal vehicle dynamic model, so as to accurately predict energy consumption and provide a simulation environment for the optimization of energy management strategies. According to whether the driver model is included, the longitudinal vehicle dynamic model can be roughly divided into forward model (dynamic model) and backward model (quasi-static model). The forward model is a model in which the driver model issues a control command to the power system by judging the difference between the current vehicle state (such as speed, acceleration, etc.) and the target state/expected state, and the power output from the power system is transmitted by the powertrain to drive the vehicle to approach or reach the expected state. The advantage of the model is that it can capture the dynamic characteristics of the powertrain, and it is often used to analyze and evaluate the response performance of the system to control commands. The main disadvantage is that the model cannot accurately follow the target trajectory (such as vehicle speed), and the following accuracy is mainly affected by the performance of the driver model. Compared with the forward model, the backward model does not include the driver model. The backward model is established provided that the dynamic performance of the vehicle can meet the requirements of the following target state. The energy flow of the vehicle is transmitted forward via the powertrain from the wheel side until the power system, and finally reflects the energy consumption. The advantage of the backward model is that it does not require a large number of high-order differential equations to describe the dynamic process of the powertrain as in the forward model. Therefore, the model is faster when used in simulation calculation. Meanwhile, when the dynamic process of the system (such as shifting process) contributes little to the overall fuel consumption of the vehicle, the oil consumption prediction accuracy of the model meets the requirements. In summary, considering that the dynamic programming algorithm itself has a large amount of computation and a complex computational process, and considering that the study here focuses on the vehicle fuel consumption, rather than evaluating the dynamic response performance of the powertrain to the control command, the longitudinal vehicle dynamic model is established according to the backward model modeling method.

216

4.4.1.2

4 Energy Management Strategy Techniques for New Energy Vehicles

Powertrain Structure

The object of study in this section is a single-axle parallel, non-plug-in, petrol-electric hybrid city bus, whose powertrain structure is shown in Fig. 4.27. Like most buses of the same type, the powertrain of bus adopts RR layout. By disengaging and engaging the clutch between the motor and the engine, the powertrain can cut off and intervene in the engine power during driving. Main vehicle parameters are shown in Table 4.4.

Clutch

Front axle

Main reducer

Transmission

Engine Motor

Fig. 4.27 Powertrain structure

Table 4.4 Main vehicle parameters Part

Configuration/value

Engine

Inline six cylinder diesel engine, 6.49 L, 2500 r/min@147W

Motor

PM synchronous, 2800 r/min@60 kW, 0–1140 r/min@500 N·m

Battery

Lithium ion battery/336V30Ah/3P148S

Degree of mixing

HR = 0.29

Transmission

AMT/(6.39/3.97/2.4/1.48/1/0.73)

Main reducer

Speed ratio 6.43

Vehicle weight

Curb weight: 10700 kg Full load: 18,000 kg

Drag coefficient

0.65

Rolling resistance coefficient

0.015

Frontal area

6.3 m2

Powertrain efficiency

0.931

Wheel radius

0.486 m

4.4 Optimal Energy Management Strategies for Hybrid Electric Vehicles Batter

Motor

Driving cycle

Driving resistance

217

Change

Powertrain Engine Fuel

Fig. 4.28 Schematic diagram of longitudinal vehicle dynamic model

According to the structure of the power system and the backward modeling method adopted, a schematic diagram of the longitudinal vehicle dynamic model is established, as shown in Fig. 4.28. The model consists of three parts, namely, the vehicle driving resistance model, powertrain model and the power system model composed of the motor, battery and engine. According to the acceleration and speed of the driving cycle, the required speed at the wheel edge and torque/power can be determined. Through the transmission effect of the driving resistance model via the powertrain, the change of the battery power and the fuel consumption can be calculated through the power system model composed of motor, battery and engine.

4.4.1.3

Design of Dynamic Programming Process of Energy Management Strategy

Figure 4.29 is the schematic diagram of the dynamic programming process of energy management strategy. The whole process consists of four parts, namely, the known driving cycle, the longitudinal vehicle dynamic model, the main program of the dynamic programming algorithm and the data storage module. Among them, the longitudinal vehicle dynamic model, including the driving resistance model, powertrain model and power system model, is to calculate the required power and speed for the driving cycle according to the vehicle and acceleration trajectory of the driving cycle and take

Whole vehicle

Driving cycle

Dynamic programming algorithm Required power

Vehicle Vehicle

Accelerat

Revolvin

Data storage

Energy consumption

Time

Vehicle driving resistance model Torque Vehicle powertrain model Vehicle power system model

Discretization Reachable state set determination Fuel consumption matrix calculation Energy distribution trajectory solution

Fig. 4.29 Schematic diagram of dynamic programming process of energy management strategy

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4 Energy Management Strategy Techniques for New Energy Vehicles

them as the inputs to the dynamic programming algorithm on the one hand, and to calculate the corresponding energy consumption (power consumption and fuel consumption) of the vehicle according to the torque command output by the dynamic programming algorithm program on the other hand. The main program of dynamic programming algorithm, including discretization, reachable state set determination, fuel consumption matrix calculation and energy distribution trajectory solution, is to output all possible energy distribution modes (torque command) at each moment to the vehicle energy consumption model in turn according to the required power at each moment, traverse the whole driving cycle, obtain the fuel consumption matrix, and finally solve the energy distribution trajectory with minimum fuel consumption by recursive calls. It is worth noting that the cost function in this section refers only to fuel consumption. The dynamic programming is solved numerically. First, the time and system state are discretized, and the computational grid of the battery SOC is divided along the time direction of the driving cycle. According to the known driving cycle, the longitudinal vehicle dynamic model is applied to calculate the required power and speed of the power source along the time direction in the driving cycle. According to the constraints of the motor, battery and engine, the reachable boundary of the system in the whole driving cycle is obtained from the initial state and the termination state of the system respectively. Then, within the reachable boundary range, the reachable state set R and the fuel consumption matrix of the whole driving cycle can be obtained according to the forward calculation of the designed cost function under the system constraints. Finally, by means of recursive calls, the ergodic optimization process is completed from the termination state backward to the initial state, the energy distribution trajectory (control trajectory) that minimizes fuel consumption is obtained, and the calculation result is output.

4.4.1.4

Implementation of Dynamic Programming Algorithm Program for Energy Management Strategy

According to the designed dynamic programming process of energy management strategy, the design of dynamic programming algorithm program is completed based on MATLAB software platform, including four parts: discretization, reachable state set determination, fuel consumption matrix calculation and energy distribution trajectory solution. 1. Discretization Because the dynamic programming is solved numerically, it is necessary to discretize the time and system state. Figure 4.30 is the schematic diagram of discretization. Among them, the operating range of SOC (upper limit and lower limit) is determined according to the common operating range of real vehicle battery, and shall not affect the service life due to deep battery charging and discharging. Considering that the speed of the driving cycle is updated once per second, the time discretization step length is set as 1 s; the SOC discretization grids are isometric grids, with

4.4 Optimal Energy Management Strategies for Hybrid Electric Vehicles

219

Upper limit

Initial value

Final value

Lower limit

Fig. 4.30 Schematic diagram of discretization of time and system state

the size determined according to the battery capacity (0.01% for the model battery discretization grid of the prototype vehicle). With the increase of battery capacity, the SOC grid size shall be appropriately reduced in order to keep the electric power value corresponding to each grid change basically unchanged and ensure the calculation accuracy. 2. Reachable state set determination In the process of optimization calculation, due to the existence of system constraints and the limit of the battery operating range, the operating range of the power system in the whole driving cycle is bounded. The system state variables and control variable constraints are discretized and are unified in the same unit with the battery power constraints. The power constraints of the engine and motor are described as follows PI C E min ≤ PI C E (k) ≤ PI C E max

(4.17)

PE M min ≤ PE M (k) ≤ PE M max

(4.18)

where PICE and PEM represent the power of the engine and motor, respectively. At the same time, the initial and termination states of the battery are constrained to be the same, so as to ensure the total battery balance of the vehicle at the end of the driving cycle S OCstar t = S OCter minal

(4.19)

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4 Energy Management Strategy Techniques for New Energy Vehicles

Fig. 4.31 Schematic diagram of feasible region of battery SOC

At stage k, under the condition that the above constraints are met, according to the required power of the vehicle and peak power of the engine, the maximum charge and discharge power of the motor can be expressed as PE M (k) = Pr eq (k) − PI C E max (k)

(4.20)

According to the constrained upper and lower limits of battery SOC, 

∗ S OCmin = max S OCmin , S OCstar t_lowlimit , S OCter minal_lowlimit

(4.21)



∗ S OCmax = max S OCmax , S OCstar t_uplimit , S OCter minal_uplimit

(4.22)

Figure 4.31 shows the feasible region of battery SOC. It can be seen that the feasible region of battery SOC is diamond-like and SOC starts from the initial state SOCstart . Under the condition that various constraints of the power system are satisfied, at each stage k, the battery is charged and discharged with the maximum allowable power Pbatt (k) until it reaches the set upper and lower limits SOCmax and SOCmin . At the same time, in order to ensure that the battery SOC finally returns to the set termination state SOCterminal , it is pushed back from the termination point until it reaches the upper and lower limits, so as to ensure that the hybrid system is always in the feasible interval during the optimization process. In summary, the coordinate set of reachable states of the battery SOC in the whole driving cycle can be expressed as |  | S OCmax (k) − S OC(k) | R = (m, k)| 1 ≤ k ≤ N , m ∈ S OCstep

(4.23)

where SOC step represents the SOC discretization grid step length; S OC(k) = S OC(k − 1) + ΔS OCmax (k − 1), 2 ≤ k ≤ N

(4.24)

4.4 Optimal Energy Management Strategies for Hybrid Electric Vehicles Vehicle speed Driving cycle

221

Required power Resistance model

Acceleration

Fuel Engine power

Battery power Battery

Internal

Motor power Motor

SOC variation

Fig. 4.32 Schematic diagram of fuel consumption calculation process

3. Fuel consumption matrix calculation According to the identified reachable state stet of the battery SOC, the battery power and motor power can be calculated reversely from the power system model. On the premise of known required power, the corresponding engine power can be calculated according to the power balance principle and finally the fuel consumption value is obtained by look-up table using the established engine fuel consumption model (static fuel consumption MAP). In this way, the fuel consumption matrix can be obtained by traversing the whole feasible region. The schematic diagram of the fuel consumption calculation process is shown in Fig. 4.32. The calculation of fuel consumption at stage k is described as L(x(k), u(k)) = f uel(k) =

f 1 (n I C E , TI C E (k)) · PI C E (k) 3600ρ

(4.25)

where x(k) is the set of feasible state points of power source speed (vehicle speed) and battery SOC at stage k; u(k) is the allowed control set of the power source torque (power) at stage k; ρ is fuel density, 0.85 g/cm3 ; fuel(k) is the fuel consumption set corresponding to stage k. The fuel consumption matrix of the whole driving cycle is denoted as F = { f uel(k) | 1 ≤ k ≤ N }

(4.26)

4. Energy distribution trajectory solution According to the designed optimization objective, on the basis of the fuel consumption matrix F obtained, the global optimization problem is transformed into a multistage decision problem by Bellman principle and calculated step by step. That is, taking the minimum cumulative fuel consumption from each stage k to the termination state as the programming objective, the method of recursive call is adopted

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4 Energy Management Strategy Techniques for New Energy Vehicles

to infer backward from the termination state to the initial state for solution. The established recursive call equation is as follows: At stage N − 1: JN∗ −1 (S OC(N − 1)) = min [ f uel(S OC(N − 1), TE M (N − 1), TI C E (N − 1)] μ(N −1)

(4.27) Stage k (1 ≤ k ≤ N − 1):   ∗ Jk∗ (S OC(k)) = min f uel(S OC(k), TE M (k), TI C E (k) + Jk+1 (S OC(k + 1))) μ(k)

(4.28) where Jk∗ (S OC(k)) represents the minimum cumulative fuel consumption from stage K to termination stage N. In the algorithm, the system state SOC(k) corresponding to Jk∗ (S OC(k)) is stored as a sequence along the time direction. The energy distribution trajectory sequence of minimum fuel consumption is   ∗ U = arg min f uel(S OC(k), TE M (k), TI C E (k) + Jk+1 (S OC(k + 1))) μ(k)

(4.29)

where U is the sequence of energy distribution trajectory (power source torque/power) (1 ≤ K ≤ N − 1). The schematic diagram of SOC trajectory programming results is shown in Fig. 4.33. From the above dynamic programming solution process, it can be found that, the backward inference of the control quantity by using the discretized state quantity effectively avoids the possible problem in the calculation process that the actual system state does not fall exactly on the discrete state grid points, so a large number

SOC trajectory with minimum cumulative fuel consumption

Fig. 4.33 Schematic diagram of SOC trajectory programming results

4.4 Optimal Energy Management Strategies for Hybrid Electric Vehicles

223

of interpolation calculations have to be carried out in the whole operation process, which greatly improves the computational efficiency. Starting from the initial state and the termination state of the system, the system constraints are used to obtain the feasible region of SOC, ensure the SOC balance, avoid the phenomenon that the cost function value increases with the SOC trajectory deviation from the initial state during the optimization and improve the reliability of the optimization results. To verify the program, CCBC (China City Bus Cycle) is selected, and the dynamic programming results are shown in Fig. 4.34. From the trajectory of the SOC, it can be clearly seen that the dynamic programming program ensures the balance of the SOC during the optimization and finds the energy distribution trajectory that minimizes the driving cycle fuel consumption. The results show that the 100 km fuel consumption is 26.68 L, an economic increase of 29.04% compared with the traditional prototype of 37.60 L. This result is the solution that the current power system can achieve the minimum fuel consumption under the CCBC driving cycle. It should be emphasized that in the process of dynamic programming implementation, the strategy that the motor recovers the braking energy as much as possible shall be adopted for the braking energy recovery (that is, when the braking torque provided by the motor cannot meet the braking torque demand, the additional torque will be provided by the mechanical braking). In addition, the gear is not taken as the planned control variable here, considering that the gear shifting strategy of a real

Fig. 4.34 Dynamic programming results of CCBC driving cycle

224

4 Energy Management Strategy Techniques for New Energy Vehicles Real vehicle shift curve

Throttle opening/(%)

Fig. 4.35 Shift schedule of prototype vehicle

Vehicle speed/(km/h)

vehicle is finally determined by integrating many indicators such as vehicle dynamic performance, fuel economy and NVH performance through a series of simulation optimization and experimental calibration, rather than solely taking the best fuel economy as the evaluation index, Therefore, the gear trajectory in this paper is obtained by simulating the driving cycle of a traditional prototype vehicle (equipped with a 200 kW engine as the power source), and it is used as the known input of the dynamic programming optimization program. Figure 4.35 shows the shift schedule of the prototype vehicle (1 → 2 in the figure means shifting from gear 1 to gear 2, and so on for the other meanings).

4.4.1.5

Brief Summary

According to the high complexity of energy distribution in the HEV powertrain with driving conditions, the dynamic programming algorithm which is widely recognized and adopted at present is selected as the global optimization algorithm of energy management strategies, and the dynamic programming problem of the energy management strategies is analyzed in detail in this section. According to the characteristics of the dynamic programming algorithm, considering the vehicle fuel consumption prediction by the longitudinal vehicle dynamic model as the main objective, the backward modeling method is selected to establish a longitudinal vehicle dynamic model composed of the vehicle driving resistance model, powertrain model and power system model on the platform of an existing hybrid bus relying on a large number of test data, and combined with knowledge of the vehicle longitudinal dynamics and the basic electrical theory; with the minimum cumulative fuel consumption in the driving cycle as the optimization objective, in accordance with the idea of the discretization process, reachable state set determination, fuel consumption matrix calculation and energy distribution trajectory solution, this section also

4.4 Optimal Energy Management Strategies for Hybrid Electric Vehicles

225

completes the dynamic programming process design and algorithm implementation relying on MATLAB software platform, tests the program with the known cycle of CCBC and obtains the energy distribution trajectory with minimum cumulative fuel consumption in CCBC.

4.4.2 Optimization-Based Energy Management Strategies by Pontryagin’s Minimum Principle 4.4.2.1

Pontryagin’s Minimum Principle

Optimization-based energy management strategies can be classified into global optimization and instantaneous optimization energy management strategy. The global optimization energy management strategy combines the latest control theory and optimization algorithm to find the optimal distribution method for the given working condition data. The dynamic programming is the most popular method. Zhang Bingli et al. proposed a design idea of energy management strategy for fuel cell city buses based on stochastic dynamic programming, simulated the driver’s required power as a discrete stochastic dynamic process, established the corresponding Markov model and optimized the energy management strategy by strategy iteration algorithm on this basis. Jin Zhenhua et al. designed an optimized energy management strategy according to the characteristics of vehicle fuel cell hybrid electric power system, globally optimized the target driving cycle using the dynamic programming algorithm, analyzed the optimal energy allocation strategy, and extracted the corresponding control rules. Based on the idea of optimization, the instantaneous optimization energy management usually takes a sampling time as the optimization interval to establish the optimization objective function, adopts the optimization algorithm for solution and finally obtains the instantaneous optimal operating point. The objective of the instantaneous optimization strategy is to achieve the optimization of the instantaneous control objective, but it cannot guarantee the optimal objective in the whole operation interval, and the calculation is also complicated. For example, Pontryagin’s minimum principle (PMP) and the equivalent consumption minimum strategy (ECMS) belong to this kind of energy management strategy. For both economy and durability, this section puts forward a hierarchical energy management method for the fuel cell hybrid system based on the Pontryagin minimum principle based on satisfactory optimization (SOPMP). The SOPMP is used to improve and optimize the durability of the battery, the PMP is used to improve the economy of the system, and the load power is effectively distributed. In this section, the SOPMP-based energy management is achieved by experiment with the fuel cell/battery hybrid sightseeing experimental vehicle developed by the laboratory as the prototype, and the measured working condition as the object, and is compared with PMP in terms of the power fluctuation rate and hydrogen consumption.

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4 Energy Management Strategy Techniques for New Energy Vehicles

Fig. 4.36 Fuel cell/lithium battery experimental vehicle

Table 4.5 Key parameter table Value

Parameter

Parameter

Value 30

Vehicle weight/kg

1350

Maximum speed/(km/h)

Passenger capacity

11

Maximum climbing slope/(%) 30

Load/kg

800

Bus voltage/V

60

Dimensions/(mm × mm × mm) 5200 × 1490 × 2080

4.4.2.2

Fuel Cell Hybrid Vehicle (FCHV) and Key Components

The lithium battery experimental vehicle used in this section is shown in Fig. 4.36 and its key parameters are shown in Table 4.5. The experimental vehicle uses PEMFC as the main power source, lithium battery as the energy storage device and auxiliary power source, and adopts an active hybrid structure. That is, the PEMFC is connected to the bus by a unidirectional DC– DC converter, and the output current of the PEMFC is controlled by the DC–DC converter; the lithium battery is directly connected to the bus, and the DC bus drives the AC traction motor after the three-phase inverter. Figure 4.37 shows the electrical system topology of the vehicle.

4.4.2.3

SOPMP-Based Energy Management Method

According to the characteristics of the fuel cell hybrid system, we have designed a top-down hierarchical energy management method based on satisfactory optimization. The first-level priority layer is the system rigid constraints, which must be satisfied under any circumstances to ensure the normal operation of the system.

4.4 Optimal Energy Management Strategies for Hybrid Electric Vehicles

227

Signal flow Energy flow

Vehicular hydrogen storage tank

Unidirectional DC-DC converter

Three-phase inverter Energy management system (EMS) for hybrid system

Battery management system BMS

Lithium battery pack

Voltage regulator module of different voltage levels (DC-DC)

AC traction motor Auxiliary electric equipment

Fig. 4.37 Electrical system topology of experimental vehicle

Therefore, the first-level priority layer will be applied at any time of energy management. The second-level priority layer is set as the auxiliary control index. That is, in the optimization process of the secondary control objective, the optimal solution is no longer forced, and the satisfactory optimization principle is used instead of the optimal solution, so as to obtain wider feasible region and control degrees of freedom. The three-level priority layer is the main control index. When the optimization reaches this level, PMP optimization calculation shall be carried out in the feasible region obtained by satisfactory optimization to obtain the optimal load power distribution under the load demand state, so as to ensure the uniqueness of the optimization solution of the whole system. Figure 4.38 shows the process of obtaining the optimal power distribution solution (Pfc-opt , Pbat-opt ) by SOPMP. First, the feasible regions of all power distribution solutions are obtained according to the rigid constraints of the system (power demand, power source output limit, etc.), and Pfc-min and Pfc-max are used as the boundary of PEMFC output power; then, the feasible region range is narrowed based on the established durability satisfactory optimization function, the feasible regions meeting the satisfactory requirements are reserved and those not meeting the requirements are discarded, so as to obtain the feasible region of PEMFC output power bounded by Pfc-conmin and Pfc-conmax . Finally, in [Pfc-conmin , Pfc-conmax ], based on Pontryagin’s minimum principle, the unique optimal output power of PEMFC and lithium battery is calculated, so that the optimal power distribution solution is obtained. The design principles of each layer are introduced in detail below. The first-level priority layer refers to the rigid constraints of the system. In a fuel cell hybrid system, there are the following constraints that must be met by the system or power supply equipment during operation, including: load power demand CSO, fuel cell output power limit and lithium battery output power limit.

228

4 Energy Management Strategy Techniques for New Energy Vehicles All available power distribution solutions A feasible power distribution solution after satisfactory optimization Final optimal power distribution solution

Fig. 4.38 Hierarchical energy management method idea

P f c (k) + Pbat (k) = Pload (k)

(4.30)

P f c min ≤ P f c (k) ≤ P f c max

(4.31)

Pbat min ≤ Pbat (k) ≤ Pbat max

(4.32)

The optimization problems of which the optimal solutions are not clear and are difficult to grasp are generally solved by following the “satisfactory optimization principle”, which enables the human intelligence to effectively solve various complex information processing problems. Different from the traditional optimal control methods, this method does not pursue the optimization of a certain index. Instead, it is aimed to obtain a higher integrated satisfaction after coordination of multiple indexes. Currently, the satisfactory optimization problems exist widely, and have been provided with some effective application methods and models. For fuel cell system, durability and economy are two optimization objectives with game relation in the energy management system. In order to alleviate the conflict of multi-objectives and take into account the global optimization of multi-objective interests, we have designed a second-level priority layer with the durability of fuel cells and lithium batteries as the auxiliary control index based on the satisfactory optimization principle. The trade-offs of control variables at the second-level priority layer will affect the quality of the whole optimization control result. At the secondlevel priority layer designed here, the integrated satisfaction of the control effect is considered as the objective instead of the traditional optimal solution objective to obtain wider feasible region and degrees of freedom. In order to avoid no solution to optimization, according to the characteristics of the vehicle power system mentioned above, the satisfaction judgment method based on fuzzy decision is introduced. That is, the cut-off point of satisfaction/out of control

4.4 Optimal Energy Management Strategies for Hybrid Electric Vehicles

229

is not clearly set. Instead, a multi-segment piecewise function is used to characterize the change of satisfaction. Figure 4.39 compares the judgment methods for the PEMFC system durability satisfaction δ based on hysteresis and fuzzy decision. The essential difference between the two methods is that the hysteresis decision based method adopts the judgment method of either 1 or 0. When the fluctuation of the fuel cell output power is within the maximum range of the limit, the satisfaction is considered as 1; otherwise it is 0. In contrast, the fuzzy decision based method sets the satisfaction function, whose value decreases slowly with the fluctuation of fuel cell output power, and is bounded by multiple piecewise points. The change of satisfaction function is characterized by the linear or quadratic piecewise function. This method can effectively reduce the influence of power fluctuation rate on the integrated satisfaction function, so as to avoid the occurrence of no solution to optimization. Figure 4.40 shows the comparison of the optimization without solution before and after modifying the satisfaction function. When the flag bit is 0, it indicates that the stepwise optimization control can be completed. When the flag bit is 1, it indicates that the optimization has no solution. By comparison, it can be seen that the fuzzy decision based satisfaction function can avoid the unsolved optimization and guarantee the stable operation of the system. The third-level priority layer corresponds to the optimal control of the fuel cell hybrid system. Our research object is a fuel cell/lithium battery experimental vehicle, the energy management problem of whose hybrid system can be transformed into an SDOF control problem. The control variable μ(t) is the output power of PEMFC, the state variable x (t) is the SOC of lithium battery, and the control objective is to minimize the hydrogen consumption in a single control cycle, i.e. 

tf

J = min

C H2 (x(t), μ(t))dt

(4.33)

0

where C H2 is the hydrogen consumption in a single control cycle, which is linearly related to the output power of PEMFC; t f is the time of termination of control.

Hysteresis decision Fuzzy decision

Fig. 4.39 Comparison of satisfaction δ based on hysteresis and fuzzy decisions

4 Energy Management Strategy Techniques for New Energy Vehicles

Solution flag bit

230

No solution to optimization (before modifying satisfaction function)

No solution to optimization (after modifying satisfaction function)

Fig. 4.40 No solution to optimization

The system state equation is S OC = F(S OC, μ(t), x(t)) = −

Ibat (S OC, μ(t)) Q bat

(4.34)

where Ibat =

VOC −

/

2 VOC − 4Rint Pbat

2Rint

(4.35)

where I bat is the charge and discharge current of the lithium battery, with the positive and negative respectively representing the discharge and charge process; Pbat is the charge and discharge power of lithium battery; Rint is the battery charge and discharge internal resistance; V oc is the open-circuit voltage of the battery. The constraint of the third-level priority layer is the feasible region of control variables gradually narrowed and restricted by the first two priority layers. Therefore, in order to transform a constrained problem of finding the system minimum into an unconstrained problem, Hamilton function shall be constructed according to Pontryagin’s minimum principle. The general form of the Hamilton function is H (x, μ, λ, , t) = L(x, μ, t) + λ f (x, μ, t)

(4.36)

In this system, the Hamilton function is H (x, μ, λ, t) = C(μ) + λS OC

(4.37)

where λ is the Lagrange multiplier. When SOC fluctuates in a small range, its influence on the charge and discharge internal resistance and open-circuit voltage of the lithium battery can be ignored. Then the function is simplified as a canonical equation:

4.4 Optimal Energy Management Strategies for Hybrid Electric Vehicles

λ(t) = λ(t0 ) = λ0

231

(4.38)

In addition, the optimal output power of PEMFC required in each control cycle can be obtained by finding the minimum value of the corresponding equation. H (xopt , μopt , λ, t) = min H (xopt , μopt , λ, t)

(4.39)

In this section, a hierarchical energy management method for the fuel cell hybrid system based on the SOPMP is proposed to solve the problem that the energy management method of fuel cell hybrid power system does not take into account both economy and durability. This method performs load power distribution in layers. The first layer takes the system rigid constraints as the main body, and obtains all load power distribution combinations that meet the required power requirements; in the second layer, fuzzy decision based satisfaction function is formulated, and the durability of the system targeted to narrow the feasible region of the load power distribution combination; the third layer takes economy as the control objective and uses the PMP based method to realize the only effective distribution of load power.

4.4.3 Real-Time Optimization Energy Management Strategy Based on Approximate Minimum Principle In order to improve the fuel economy of vehicles, it is an effective method to design online energy management strategies based on the minimum principle, however, the difficulty lies in how to avoid the iterative calculation of co-state variables. Based on the reasonable assumptions of the characteristics and output power of the power battery pack, the relationship between the co-state variables and the open-circuit voltage of the power battery pack is derived by using the state equation and co-state equation. Through the approximate solution of the relation equation, it is concluded that the ratio of the above two can be regarded as a constant. The online energy management strategies designed based on this conclusion will be applied to different actual working conditions, and the results be compared with the global optimal solution. The EREV becomes an ideal transition model from traditional vehicles to battery electric vehicles because of its advantages of online extended driving range, convenient use and low maintenance cost. In order to improve the fuel economy of the vehicle, it is a feasible solution to distribute the output power of the auxiliary power unit (APU) and the power battery using the energy management strategies. Existing energy management strategies can be divided into two categories: rule-based and optimization-based: The former does not need to know the full working condition information and can be applied online, but with limited optimization effect, mainly including deterministic rule-based strategies represented by power consumptionpower maintenance strategy as well as various fuzzy rule-based strategies. The latter

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4 Energy Management Strategy Techniques for New Energy Vehicles

requires the full working condition information to be known, but the global optimal solution can be obtained offline. It mainly including the dynamic programming based and minimum principle based strategies. PMP is one of the most possible optimization methods for online applications, but it needs to solve the problem that co-state variables are difficult to determine online. Here, the SOC of the power battery is selected as the state variable, and the output power P of the power battery is taken as the control variable. In the study, the SOC of the start and end states of the power battery is given, so the objective function is to minimize the fuel consumption of the APU:  min J =

tf

m˙ f.A PU (PA PU (t))dt

(4.40)

0

The state equation is ·

S OC = f (S OC(t), Pbat (t))

(4.41)

The constraints of this optimization problem include: S OCmin ≤ S OC(t) ≤ S OCmax

(4.42)

Pbat,min (t) ≤ Pbat (t) ≤ Pbat,max (t)

(4.43)

where SOC min and SOC max are the minimum and maximum values of the state variable SOC, respectively; Pbat.min (t) and Pbat.max (t) are the minimum and maximum values of control variable Pbat (t) at any time, respectively, both of which are determined by the charge and discharge power limits of the power battery and the power balance equation. Pr eq (t) = 1000PA PU (t) + Pbat (t)

(4.44)

where Preq (t) is the input power (W) at the bus end of a drive motor to meet the dynamic requirements. When the minimum principle is used to solve the above optimization control problem, the Hamilton function is defined: ·

H = m˙ f.A PU t + λ(t) S OC(t)

(4.45)

where λ(t) is a time-varying co-state variable. The necessary conditions satisfied by the optimal control trajectory are: λ(t) =

∗ (t), λ∗ (t), Pr eq (t)) ∂ H (S OC ∗ (t), Pbat ∂ S OC

(4.46)

4.5 Intelligent Energy Management Strategies for Hybrid Electric Vehicles

S OC ∗ (t) = −

∗ (t) Ibat 3600Q min

233

(4.47)

S OC ∗ (0) = S OC0

(4.48)

S OC ∗ (t f ) = S OCmin

(4.49)

∗ H (S OC ∗ (t), Pbat (t), λ∗ (t), Pr eq (t)) ≤ H (S OC ∗ (t), Pbat (t), λ∗ (t), Pr eq (t)) (4.50)

where * denotes the optimal solution. In solving the energy management problem of the extended-range city bus by the minimum principle, a law that the ratio of the co-state variable to the opencircuit voltage of the power battery can be approximated as a constant is deduced by the co-state equation and the state equation. This law solves the problem of online determination of the co-state variable and can be used to design the online energy management strategy. It is found that this strategy is an optimal energy management strategy which can be applied online when it is applied to different practical conditions.

4.5 Intelligent Energy Management Strategies for Hybrid Electric Vehicles 4.5.1 Instantaneous Optimization Energy Management Strategy Based on Online Self-Learning Adjustment For a plug-in hybrid electric bus with variable running lines, it is difficult to use the neural networks to learn the optimal engine output power sequence due to the great differences in the operating characteristics of different lines. In this section, energy management strategies suitable for variable lines will be developed, and the rational use of energy in the battery pack will be realized by learning the macroscopic law of change of the optimal SOC trajectory in the knowledge base, so as to improve the overall efficiency of the drive system. In this section, the neural networks and adaptive neutral fuzzy inference system are designed respectively to learn the changes of the optimal SOC trajectory. The neural networks are suitable for learning the changes of small-sample optimal SOC trajectories, while the adaptive neural fuzzy inference system is suitable for learning the changes of large-sample optimal SOC trajectory. At the beginning of the working condition, the SOC reference trajectory is constructed, and the energy management problem is transformed into the SOC following problem. From the perspective of

234

4 Energy Management Strategy Techniques for New Energy Vehicles

online use, combined with the analysis and learning of the optimal engine output power, the adaptive fuzzy logic energy management strategy is first designed. 1. Energy planning The complexity in the energy management of the plug-in hybrid electric vehicle lies in the variable initial SOC of the battery pack, but it has to reach a low level after operation. Therefore, researchers have considered energy planning to reasonably arrange the charge and discharge of the battery pack. Tulpule et al. first assumed that the battery pack SOC decreased linearly with increasing driving range, the advantage of this assumption is that the assumption is simple and practical since the complex SOC trajectory change law may not be considered. When the initial SOC of the battery pack is high, this assumption has high accuracy, but when the initial SOC is low, there is a large difference between the constructed SOC reference trajectory and the optimal SOC trajectory. Onori and Tribioli also adopted this method of constructing SOC reference trajectory in their subsequent studies. In order to improve the relative accuracy of SOC reference trajectory, Feng et al. proposed an energy planning method: ΔS OCi (s) = (S OCini − S OC f in )

vsid,i E i vaver,i Si N2 ∑ j=1

vsid, j vaver, j

·s

(4.51)

Ej

where E i and E j represent the energy of sections i and j respectively; S i is the length of section i; s is the length of the section traveled. In this energy planning method, SOC at the beginning and end of the section, the standard deviation of the working condition speed sequence, average vehicle speed and other information are used. From its conclusion analysis, it can be seen that there is little gap between the SOC reference trajectory constructed by this method and the optimal SOC trajectory obtained by dynamic programming. However, this energy planning method uses the standard deviation of the speed sequence, which is not easy to obtain at the beginning of vehicle operation. You et al. proposed an energy planning method for plug-in hybrid electric buses: n−1 ∑

S OCr = S OCini − (S OCini − S OC L )

  n−1 ∑ ρi li + ρn S − li

i=1

i=1 k ∑

(4.52)

ρi li

i=1

This method needs to use information such as initial SOC, low SOC threshold, mileage from the departure station, length of section i and average required power of section i, among which the average required power of section i is difficult to obtain. The above method for constructing SOC reference trajectory using formulas lacks theoretical basis and degenerates into the energy planning method proposed by Tulpule et al. when the initial SOC of the battery pack is low, which is obviously

4.5 Intelligent Energy Management Strategies for Hybrid Electric Vehicles

235

quite different from the optimal SOC trajectory. However, in the two studies, the driving conditions are divided into several driving condition segments. According to the standard deviation of the speed sequence of each driving condition segment, the average required power and other parameters reflecting part of the driving condition information, the idea of constructing SOC reference trajectory is of enlightening significance. With the development of intelligent transportation system, some driving condition information such as road mileage, average speed, low/high speed section ratio can be easily obtained, which provides a new way to reasonably construct the SOC reference trajectory. 2. Adaptive neutral fuzzy inference system to learn large-sample optimal SOC trajectory changes The adaptive neural fuzzy inference system integrates neural networks and fuzzy logic and its structure is similar to neural network, that is, to implement input and output mapping by inputting and outputting the membership function and weight parameter using Takagi–Sugeno fuzzy inference. The adaptive neural fuzzy inference system is suitable for learning the change law of the large-sample optimal SOC trajectory because of its advantages of short training time and difficult overfitting. The adaptive neutral fuzzy inference system consists of four input parameters and one output parameter. The four input parameters are the ratio of low speed section, the ratio of high speed section, the percentage of remaining mileage and the initial SOC of the section, respectively, and the output parameter is the SOC at the section terminal. In order to cope with the increasing lines and working conditions and simplify the acquisition of training data, each line is divided into 10 segments of equal length in this study. The percentage of remaining mileage is reduced from 100 to 10% at an interval of 10%, and the initial SOC of the battery pack is reduced from 100 to 30% at an interval of 10%. A total of 80 training data sets can be constructed in one working condition, as shown in Fig. 4.41 (in which, Lrp is the percentage of remaining mileage; L sr is the low speed ratio; H sr is the high speed ratio). In this study, 1120 groups of training data sets for the adaptive neutral fuzzy inference system have been constructed using 14 working conditions of 4 lines, 1020 groups of which are randomly selected for training, and the remaining 100 for verification. The type and number of membership functions of the adaptive neutral fuzzy inference system can be specified arbitrarily, and all parameters related to membership functions are changed through the learning process. Three gbell type membership functions (low, medium and high respectively) are selected for the four input parameters in this study, defined as: f (x; a, b, c) =

1 1+

x−c2b a

(4.53)

where a/b/c are shape parameters. The adaptive neutral fuzzy inference system uses a hybrid learning algorithm combined with the least square method and back propagation. The training error is measured using RMSE:

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4 Energy Management Strategy Techniques for New Energy Vehicles

Time/s Fig. 4.41 Construction of training data for adaptive neutral fuzzy inference system

/ RMSE =

n 1∑ (S OCout put (i) − S OCoptimal (i))2 n i=1

(4.54)

The error bound is used to establish the criteria for stopping training. When the training error remains within this bound, the training will be stopped. This value is set to 0. The training error of the adaptive neural fuzzy inference system is 0.0233 under the condition of zero error bound. The membership functions of the four input parameters obtained by learning is shown in Fig. 4.42, and the corresponding output surfaces are shown in Fig. 4.43. Energy planning can only give the overall trend of the battery pack SOC variation. At the beginning of vehicle operation, the initial SOC is determined, the percentage of remaining mileage is 100%, and the low speed ratio and high speed ratio are obtained from the intelligent transportation system. These parameters are input into the trained adaptive neutral fuzzy inference system to obtain the target SOC when

4.5 Intelligent Energy Management Strategies for Hybrid Electric Vehicles

Membership function

Low

Low

Medium

Medium

237 High

High

Initial SOC Low

Low

Medium

Medium

High

High

Fig. 4.42 Input membership functions obtained by adaptive neutral fuzzy inference system learning

the remaining mileage is 90%, This target SOC serves as the initial SOC of the next working condition segment. As the iteration process continues, the contours of SOC variation can be constructed, which are composed of 11 SOC points. In order to obtain the complete SOC reference trajectory, it is also assumed in this study that the SOC trajectory change in the working condition segment decreases linearly with the increase of driving mileage.

4.5.2 Energy Management Strategy Based on Neural Network Speed Prediction 4.5.2.1

Theory of Wavelet Analysis

Wavelet analysis is a new mathematical analysis method developed in recent years. Due to its excellent time–frequency localization and zoom capability, it has been widely used in the field of nonlinear science. Wavelet has high time resolution in the high frequency part of a signal and high frequency resolution in the low frequency part, so the effective information in the signal can be obtained by wavelet analysis. If ψ(ω) ∈ L 2 (R) and the permissive condition is satisfied:

4 Energy Management Strategy Techniques for New Energy Vehicles

Target SOC

Target SOC

238

10

Target SOC

Target SOC

Initial SOC

Target SOC

Target SOC

Initial SOC

Initial SOC

Fig. 4.43 Output surfaces obtained by adaptive neutral fuzzy inference system learning



+∞

−∞

ψ(ω)2 dω < 0 |ω|

(4.55)

where ψ(ω) is the Fourier transform of ψ(x), then ψ(ω) is called a basic wavelet or mother wavelet. Wavelet transform is a time–frequency joint analysis method of variable scale, which is a process of signal decomposition into approximations and details. The relationship among the signal, scale and displacement is represented by the mother wavelet functional expression. The generating function ψ(ω) is scaled and shifted to get:

4.5 Intelligent Energy Management Strategies for Hybrid Electric Vehicles

  1 x −b ψa,b (ω) = √ ψ a a

239

(4.56)

Equation (4.56) is a set of wavelet sequences, so ψa,b (ω) is also called wavelet basis function, where a and b are called scalability factor and shift factor respectively, that is, the wavelet basis function is obtained by a basic wavelet through different scale and shift. There are three commonly used one-dimensional wavelet basis functions, namely Haar wavelet basis function, Shannon wavelet basis function and Morlet wavelet basis function. The Morlet wavelet basis function is as follows: ψ(t) = cos(1.75t) exp(−0.5t 2 ) 

x −b ψ a



      x −b x −b 2 = cos 1.75 exp −0.5 a a

(4.57)

(4.58)

The Morlet wavelet basis function is used here. After scale and shift, a set of wavelet basis functions are obtained as         x − bk x − bk 2 x − bk = cos 1.75 exp −0.5 ψ (4.59) ak ak ak Figure 4.44 shows the basic function curve of Morlet wavelet basis function. After shift and scale, the purpose of local amplification analysis by the wavelet function can be achieved. The wavelet neural network (WNN) is a model of neural network formed on the basis of wavelet transform. The wavelet transform has the time–frequency local characteristics and zoom capability, but the application of wavelet theory is generally limited to a small scale, mainly because of high cost for the storage and construction Fig. 4.44 Morlet wavelet basis function curve

240

4 Energy Management Strategy Techniques for New Energy Vehicles

of the wavelet basis in large-scale application. The artificial neural network (ANN) is a powerful tool to deal with large-scale problems, and the neural network is capable of self-learning, self-adaptation and generalization, as well as robustness and fault tolerance. The concept of wavelet neural network is put forward by combining the advantages of the wavelet theory and neural network. The wavelet neural network inherits the time–frequency local characteristic of wavelet analysis, the self-learning ability of neural network and many other advantages and has the strong ability of fault tolerance. Meanwhile, the network structure scale and learning parameters are selected based on the wavelet theory. Therefore, the WNN is better than the traditional neural network in the application of residual power estimation of the HEV battery pack.

4.5.2.2

Structure and Design of Battery SOC Estimation Based on WNN

BP neural network is a kind of multilayer feedforward artificial neural network that includes the input layer, hidden layer and output layer, which does not require a precise mathematical model to model the uncertain and nonlinear system of the battery SOC estimation, so as to effectively solve the problems of low accuracy and poor real-time performance of the common estimation methods in battery SOC estimation. The neural network based on Morlet wavelet established in this study is a three-layer network model, as shown in Fig. 4.45. In order to overcome the disadvantage that the BP neural network is easy to fall into local minimum point and cannot get the global optimal solution, the method of WNN based SOC estimation of power battery pack is adopted. The Morlet WNN has stronger learning ability and faster convergence speed, the hidden node function of conventional single-hidden layer feedforward neural networks (SLFN) is replaced by wavelet function, and the corresponding weights and thresholds from the input layer to the hidden layer are replaced by the scale and shift parameters of the wavelet Fig. 4.45 BP neural network model

4.5 Intelligent Energy Management Strategies for Hybrid Electric Vehicles

241

Fig. 4.46 Schematic diagram of WNN structure

function, respectively. In this way, the only adjustable parameters are scale factor and shift factor. This is a widely used structure, as shown in Fig. 4.46. Using the MANHATON road condition in MATLAB/ADVISOR, combined with the battery model established, the ADVISOR software is run, and the data obtained from driving under MANHATON road conditions is used as the training data of Morlet WNN model. By running MATLAB/ADVISOR, we can know the driving speed and other information of the vehicle under MANHATON road conditions. According to the detailed road condition information and vehicle driving information provided by ADVISOR, we can obtain the voltage, current and temperature changes of the lithium-ion power battery pack under MANHATON road conditions, as well as the charge and discharge efficiency data during driving. The data can be extracted as training data for several neural networks.

4.5.2.3

Network Training and Simulation of Several Models

Figure 4.47 shows the SOC estimation model of Morlet WNN battery. The input variables of the model are the current, voltage, temperature, charge/discharge efficiency of the power battery pack model, and the output variable is the estimated battery SOC value. Figure 4.48 shows the input variable data of neural network. Based on the MATLAB/ADVISOR electric vehicle simulation software platform, the voltage, current and temperature changes of the lithium-ion power battery pack, as well as the charge and discharge efficiency data during the driving are obtained under the MANHATON conditions and are used as training data for several neural networks.

242

4 Energy Management Strategy Techniques for New Energy Vehicles

Input 1 current

Input 2 voltage

Input 3 temperature

Morlet WNN

Output estimated battery SOC value

Input 4 charge efficiency

Input 5 discharge efficiency

Fig. 4.47 Morlet WNN battery SOC estimation model

4.5.2.4

Analysis of WNN Output Error

Figures 4.49, 4.50 and 4.51 show the comparison curves of estimated SOC value and actual SOC value of the battery pack after the hybrid electric vehicle operates under MANHATON conditions using different network models respectively. It can be seen that the initial SOC value of the lithium-ion power battery pack is about 70%, and the SOC termination value is about 55%, falling in the range of 40–80% for the SOC of lithium-ion battery packs of hybrid electric vehicles. Figures 4.52, 4.53 and 4.54 show the error curves between the estimated battery SOC value and the expected value after the hybrid electric vehicle operates under Man-Haton conditions based on different algorithms respectively. The estimation error of battery SOC based on general artificial neural network is obviously larger than that based on BP neural network and WNN algorithms, which cannot make reasonable and accurate estimation of battery SOC. However, the battery SOC estimation based on BP neural network and WNN algorithms also has some problems that their initial SOC values cannot be consistent with the actual battery SOC initial values. Meanwhile, the error of the BP neural network is about 7%, which basically meets the precision requirement for the lithium-ion battery packs for hybrid electric vehicles to control the SOC estimation error within 8%. However, the BP neural network has the defect that it is easy to fall into local minimum point and difficult to jump out; the error of the WNN is about 5% and it is necessary to improve the estimation accuracy and the network training speed. The artificial neural network, BP neural network and WNN algorithms are used respectively to estimate the battery SOC of hybrid electric vehicles. The equivalent fuel consumption and the specific content of emission pollutants obtained by driving

Current/A

Voltage/V

4.5 Intelligent Energy Management Strategies for Hybrid Electric Vehicles

Time/s

(a) Voltage of the power battery pack

(b) Current of the power battery pack

Efficiency/(%)

Efficiency/(%)

Time/s

Time/s

(d) Discharge efficiency

SOC value

Temperature/℃

Time/s

(c) Charge efficiency

Time/s (e) Temperature of power battery pack

Fig. 4.48 Neural network input variable data

Time/s (f) Target output battery SOC value

243

244

4 Energy Management Strategy Techniques for New Energy Vehicles

Fig. 4.49 SOC estimation curve of artificial neural network

Estimated battery SOC

SOC value

Actual battery SOC

Time/s Fig. 4.50 SOC estimation curve of BP neural network

Estimated battery SOC

SOC value

Actual battery SOC

Time/s

Fig. 4.51 SOC estimation curve of WNN

Estimated battery SOC

SOC value

Actual battery SOC

Time/s

4.5 Intelligent Energy Management Strategies for Hybrid Electric Vehicles

Error/(%)

Fig. 4.52 Error curve based on general artificial neural network algorithm

Time/s

Error/(%)

Fig. 4.53 Error curve based on BP neural network algorithm

Time/s

Error/(%)

Fig. 4.54 Error curve based on WNN algorithm

Time/s

245

246

4 Energy Management Strategy Techniques for New Energy Vehicles

Fig. 4.55 Results of three algorithms in ADVISOR

under the road conditions provided in the ADVISOR are shown in Fig. 4.55. It can be obviously seen that with the increase of the battery SOC estimation accuracy, the utilization rate of battery in hybrid electric vehicle running increases significantly, the fuel consumption for 3.3 km is significantly reduced, and the emission of harmful substances is also significantly reduced with the reduction of fuel consumption.

4.5.2.5

Brief Summary

Neural networks do not need an accurate mathematical model to model the uncertain and nonlinear system of battery SOC estimation, so as to effectively solve the problems of low accuracy and poor real-time performance of common estimation methods in the battery SOC estimation. In order to overcome the disadvantage that the BP neural network is easy to fall into local minimum point and cannot get the global optimal solution, the method of WNN based SOC estimation of power battery pack is adopted. The Morlet WNN has stronger learning ability and faster convergence speed, but its SOC estimation accuracy and network convergence speed of the lithium-ion power battery pack for hybrid electric vehicles need to be further improved.

Bibliography Chen Z, Xiong R, Wang K et al (2015) Optimal energy management strategy of a plug-in hybrid electric vehicle based on a particle swarm optimization algorithm. Energies 8(5):3661–3678 Chen Z, Xiong R, Wang C et al (2017) An on-line predictive energy management strategy for plugin hybrid electric vehicles to counter the uncertain prediction of the driving cycle. Appl Energy 185(2):1663–1672 Deep K, Singh KP, Kansal ML et al (2009) A real coded genetic algorithm for solving integer and mixed integer optimization problems. Appl Math Comput 212(2):505–518 Gu B, Rizzoni G (2006) An adaptive algorithm for hybrid electric vehicle energy management based on driving pattern recognition. In: ASME 2006 international mechanical engineering congress and exposition, vol 13951, pp 49–258

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Gurkaynak Y, Khaligh A, Emadi A (2011) Neural adaptive control strategy for hybrid electric vehicles with parallel power train. In: 2010 IEEE vehicle power and propulsion conference. IEEE Homchaudhuri B, Lin R, Pisu P (2016) Hierarchical control strategies for energy management of connected hybrid electric vehicles in urban roads. Transp Res Part C Emerg Technol 62(JANA):70–86 Jager BD, Steinbuch M, Keulen TV (2008) An adaptive sub-optimal energy management strategy for hybrid drive-trains. IFAC Proc:102–107 Liu Y, Gao J, Qin D et al (2018) Rule-corrected energy management strategy for hybrid electric vehicles based on operation-mode prediction. J Clean Prod 188:796–806 Onori S, Serrao L (2011) On adaptive-ECMS strategies for hybrid electric vehicles. In: Proceedings of the international scientific conference on hybrid and electric vehicles, Malmaison, France, December Onori S, Serrao L, Rizzoni G (2016) Hybrid electric vehicles: energy management strategies. Encyclopedia of Energy 277(4):197–213 Paganellig, Delprat S, Guerra TM et al (2002) Equivalent consumption minimization strategy for parallel hybrid powertrains. In: IEEE vehicular technology conference. IEEE Panday A, Bansal HO (2014) A review of optimal energy management strategies for hybrid electric vehicle. Int J Veh Technol:160510 Poursamad A, Montazeri M (2008) Design of genetie-fuzzy control strategy for parallel hybrid electric vehicles. Control Eng Pract 16(7):861–873 Rezaei A, Burl JB, Zhou B (2017a) Estimation of the ECMS equivalent factor bounds for hybrid electric vehicles. IEEE Trans Control Syst Technol Rezaei A, Burl JB, Zhou B et al (2017b) A new real-time optimal energy management strategy for parallel hybrid electric vehicles. IEEE Trans Control Syst Technol 27(2):830–837 Sabri MFM, Danapalasingam KA, Rahmat MF (2016) A review on hybrid electric vehicles architecture and energy management strategies. Renew Sustain Energy Rev 53:1433–1442 Serrao L, Onori S, Rizzoni G (2009) ECMS as a realization of Pontryagin’s minimum principle for HEV control. In: American control conference. IEEE Serrao L, Onori S, Rizzoni G (2011) A comparative analysis of energy management strategies for hybrid electric vehicles. J Dyn Syst Meas Control 133(3):1–9 Sun C, Sun F, He H (2016) Investigating adaptive-ECMS with velocity forecast ability for hybrid electric vehicles. Appl Energy 185(2):1644–1653 Takao W, Eiji T, Masaki E et al (2016) High efficiency electromagnetic torque converter for hybrid electric vehicles. SAE Int J Alternative Powertrains 5(2) Wu J, Zhang CH, Cui NX (2008) PSO algorithm-based parameter optimization for HEV powertrain and its control strategy. Int J Autom Technol 9(1):53–59 Yuping Z, Yang C, Guiyue K et al (2018) Energy management for plug-in hybrid electric vehicle based on adaptive simplified-ECMS. Sustainability 10(6) Zhang P, Yan F, Du C (2015) A comprehensive analysis of energy management strategies for hybrid electric vehicles based on bibliometrics. Renew Sustain Energy Rev 48:88–104 Zheng C et al (2018) An energy management strategy of hybrid energy storage systems for electric vehicle applications. IEEE Trans Sustain Energy 99

Part II

Engineering Practice and Test

Chapter 5

NVH Test and Optimization for New Energy Vehicle Powertrain

5.1 NVH Test Technology The automobile NVH performance refers to the performance of a vehicle in terms of noise, vibration and harshness. It is directly related to the ride comfort and ride quality of drivers and passengers, and directly affects the vehicle quality of vehicles, so has been paid attention to by the majority of vehicle manufacturers and related researchers. Relevant statistics show that foreign advanced automobile manufacturers began to study the NVH relatively early. In particular, since the 1990s, engineering research centers of large automobile companies such as Toyota Motor, Honda Motor, Nissan Motor, General Motors, Ford, Chrysler, and Mercedes-Benz have set up NVH divisions to study NVH problems in automobiles. Because of strong inheritance and rich database of foreign automotive technology, foreign automobile enterprises are still leading many domestic automobile enterprises only from the technical point of view. According to the statistics of relevant departments, some automobile after-sales services are related to the automobile NVH. In order to make their automobile brands more competitive, major domestic automobile companies have invested a large amount of funds and test benches in research to solve the NVH problem. For the vibration and noise problems of automobiles, many relevant test standards in China are being improved constantly. To improve the independent research and development ability of domestic independent brands of pure electric buses and the core competence in terms of harshness, some domestic companies and universities have established a semi-anechoic chamber for the NVH test of the devices under test, such as China Automotive Technology & Research Center, Zhejiang Geely Automobile Co., Ltd., Changan Automobile Asian Research and Development Center in Chongqing, CAERI Acoustic Wind Tunnel in Chongqing, Shanghai NIO Vehicle Semi-Anechoic Chamber, Beijing University of Aeronautics and Astronautics, Tongji University, Chongqing University, Hefei University of Technology and

© Huazhong University of Science and Technology Press and Springer Nature Singapore Pte Ltd. 2023 Y. Chen, New Energy Vehicle Powertrain Technologies and Applications, Key Technologies on New Energy Vehicles, https://doi.org/10.1007/978-981-19-9566-8_5

251

252

5 NVH Test and Optimization for New Energy Vehicle Powertrain

Fig. 5.1 Rendering of semi-anechoic chamber

Hebei University of Technology. Figure 5.1 shows the rendering of the semi-anechoic chamber under construction in Hebei University of Technology. According to the statistics of major new energy vehicle manufacturers, the proportion of NVH problems of each subsystem of a battery electric vehicle in the NVH problems of the whole system is obtained, as shown in Fig. 5.2. For new energy vehicles, especially battery electric vehicles, NVH problems include electric drive system and electromechanical system NVH, body NVH, chassis system NVH, wind noise, tyre noise and vehicle acoustic insulation NVH, among

Vehicle acoustic insulation NVH Power system NVH Electromechanical system NVH Chassis system NVH Wind noise NVH

Fig. 5.2 Distribution of NVH problems in each subsystem of a battery electric vehicle

5.1 NVH Test Technology

253

which, the NVH problems in the electromechanical system and powertrain account for about 60% of the NVH problems of battery electric vehicles. The power source of the battery electric vehicle is changed from the original internal combustion engine to the electric motor, resulting in the lack of the masking effect of the internal combustion engine. Moreover, due to the motor characteristics of high torque, low speed and transition under accelerating conditions, the NVH of the EV powertrain is highlighted. NVH performance analysis has become the main analysis part in the development and design of EV powertrain products. The transmission is the main component of NEV powertrain, so it is also the main source of noise in electric vehicles.

5.1.1 Foundation of Engineering Noise When the sound source of an object vibrates, it excites the air particles around to vibrate, making the particle closest to the sound source move away from its original equilibrium position, thus pushing the motion of neighboring particle. That is, the neighboring medium is compressed and creates a force against the compression, bringing the particle back to its original equilibrium position. Because of inertia, the particle will pass through its original equilibrium position and compress the neighboring medium on the other side, and that medium will generate a force against the compression and push the particle back to its original equilibrium position. Due to the elasticity and inertia of the medium, the particle oscillates back and forth in its equilibrium position. For the same reason, the particle that initially vibrates will push its nearest and further particles to vibrate at their respective equilibrium positions, but there is a certain time delay in the vibration of each particle. This propagation of the mechanical motion of the medium particle from near to far is called acoustic wave, which is a kind of mechanical wave. Because of the compressibility of air, when sound propagates in the air, the air around the vibrating object alternately compresses and expands, and gradually propagates outward under the interaction of particles, thus forming acoustic waves. The acoustic wave propagation is not the movement of matter, but the propagation of energy. In other words, the particle does not spread forward with the acoustic wave, but only vibrates near its original equilibrium position and induces vibration of neighboring particles under the interaction between particles, so that the vibration can propagate around and form waves. A wave of a particle whose vibration direction is parallel to the propagation direction is called longitudinal wave, while a wave of a particle whose vibration direction is perpendicular to the propagation direction is called transverse wave. When acoustic waves propagate in air, only compression and expansion can occur. The vibration direction of air particles is consistent with the propagation direction of acoustic waves, so acoustic waves in air are longitudinal waves. Acoustic waves usually propagate as longitudinal waves in liquids, but they propagate as both longitudinal and transverse waves in solids. Acoustic waves can only propagate as longitudinal waves in gases and liquids because they cannot withstand shear forces. Acoustic

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waves can propagate as both longitudinal and transverse waves in solids because the solids can withstand shear forces.

5.1.2 Powertrain NVH Test Technology The vehicle NVH control technology mainly studies how to avoid or reduce the noise and vibration of each assembly or component during vehicle operation. In recent years, as the new development concept of green and environmental protection has taken root in people’s hearts, the comfort and sound quality of automobiles have attracted more and more attention. The passenger vehicle powertrain consists of the clutch, transmission, transfer case, transmission shaft, main reducer, differential and drive shaft. It is one of the core systems of automobile, and its basic function is to transmit the power of the engine to the drive wheel, and realize the connection and interruption of the power transmission.

5.1.2.1

Powertrain NVH Problems and Phenomenon

NVH problems may occur in the clutch, transmission, transfer case, drive shaft and main reducer in the powertrain, which are manifested as roaring, run-over and slideslip in the vehicle, howling or knocking sound in the transmission, bonding sound or knocking sound in the clutch, transfer case and main reducer, jitter, resonance, torsion imbalance and other problems in the drive shaft. The powertrain NVH problems are classified in the following four parts for explanation. 1. Roar The main excitation force of the vehicle roar comes from the combustion and expansion work in the engine cylinder, especially the torque ripple caused by the power transmission changes during the vehicle acceleration. The noise propagation path and sound location involve many aspects and are related to the overall vehicle layout and the performance of acoustic insulation materials. In addition, the bending, twisting, resonance of vehicle tyres will also produce a roar. The propagation paths of vehicle roar caused by engine are shown in Fig. 5.3. 2. Gear drive noise When a gear pair meshes, the meshing stiffness of the gear pair fluctuates with the meshing of the gear pair. At the same time, the gear pair meshes in the form of a higher pair. The higher pair includes point contact and line contact and has large stress per unit and easy wear compared with the surface contact in the lower pair. The gear meshing is also affected by the support stiffness of the gear shaft as well as the assembly and machining errors, which increase the gear meshing transmission errors. With the advent of the era of automobile electrification and intelligence, the motor develops towards high speed. At a high running speed, the gear pair will be

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Combustion pressure Cylinder head Inertia force

Piston rod

Cranks haft

Cylinder block Transmi ssion

Mount

Drive shaft

Exhaust system

Acoustic Vehicle insulation body

Cab

Suspen sion Noise elimination structure

Fig. 5.3 Propagation paths of engine-induced roar

subject to strong impact and relatively large friction force, resulting in a certain degree of vibration and noise. The internal dynamic excitation of gear is the fundamental cause of gear drive noise. It is mainly classified into stiffness excitation, error excitation and meshing impact excitation. According to the gear drive principle, there is no speed difference of the gear meshing points in the vertical direction, but there is sliding in the tangent direction. The friction force between the gear teeth also has the direction changed at this position, and the friction force forms a pulsating periodic excitation. The stiffness of meshing gear is small, and the elastic deformation of gear under load is large. For spur gear, when the gear turns to the double meshing zone, the load of the gear is small, the stiffness of the single meshing gear is large, and the load elastic deformation of the gear will be small. In the process of continuous rotation of the gear system, single tooth meshing and double tooth meshing occur alternately, and the elastic deformation of the gear under load also changes periodically with time. The sudden change of load will generate dynamic excitation to the gear, resulting in vibration and noise. Automobile power drive gears are mainly composed of helical gears. Error excitation refers to the displacement excitation of gears formed when the meshing tooth profile of gears deviates from the theoretical position and the gear meshing dislocates due to manufacturing error, installation error and support stiffness. In the process of gear transmission, the gear will undergo elastic deformation due to gear error and torque, and the instantaneous gear engaging-in and engaging-out impact will deviate from the theoretical meshing point, resulting in gear engaging-in and engaging-out impact. The meshing impact will cause periodic pulsation changes of angular speed, resulting in vibration and noise. Compared with the error excitation, the meshing impact is the regular impact excitation, while the error excitation is the displacement excitation of the gear deviating from the theoretical engaging position. The meshing error of gear pair is caused by the manufacturing and assembling error of gears. It is a main dynamic excitation in the working process of the gear pair. The gear meshing error makes the actual meshing tooth profile different from the theoretical error-free tooth profile, which destroys the proper gear meshing, causes the sudden change in the instantaneous gear ratio of the gear and causes the teeth of the gear pair to collide with each other, thus leading to the displacement dynamic error excitation of the gear pair in the working process. The results show that the pitch error, tooth profile error and tooth alignment error are the most important factors

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affecting the gear vibration and noise, and the dynamic excitation caused by other errors will be reflected in the influence of the pitch error and tooth profile error on the gear vibration and noise. Therefore, the gear error excitation is mainly to study the two error forms of pitch error and tooth profile error. The pitch error and tooth profile error are shown in Fig. 5.4. The pitch error is the offset from the ideal tooth profile (shown by dotted line) to the transitional tooth profile (shown by dotted line), and the tooth profile error is the offset from the transitional tooth profile to the actual tooth profile (shown by solid line). These two offsets are measured in the direction of the meshing line and collectively referred to as the meshing deviation of the gear teeth. The tooth profile error contributes greatly to the gear vibration and noise, and it is analyzed concretely. As shown in Fig. 5.5, when tooth A with an ideal involute tooth profile on the drive wheel meshes with tooth A' with an actual tooth profile on the driven wheel, according to the meshing principle, tooth A and tooth A' should mesh at point a in the figure ideally. However, due to the error of tooth profile, tooth A does not continuously mesh along the ideal tooth profile of the tooth A' , but actually contacts at the point a outside the meshing line, which causes the sudden change in the instantaneous gear ratio of the gear pair, leading to dynamic excitation, affecting the stability of gear drive and becoming an important contributing factor to the vibration and noise. 3. Shafting and bearing vibration and noise Shafting vibration and noise are generally produced by dynamic unbalance, bending deformation or torsional deformation; the bearing vibration and noise are generally caused by gear impact, bearing operation characteristics, assembly errors and failure wear. 4. Starting Jitter When the vehicle transitions from idle state to starting state, the output torque of the engine increases, and the amplitude of the powertrain increases under the action of torque reaction force. The torque increase causes torsional vibration of the powertrain Fig. 5.4 Pitch error and tooth profile error

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Fig. 5.5 Mechanism of dynamic excitation caused by tooth profile error

and the transmission system, which is transmitted to the body through the engine mount system, and then causes the jitter of the cab console, steering wheel, seat, auxiliary dashboard and other components. The noise caused by the transmission system NVH mainly includes axle noise, gear noise and resonance noise. The transmission system noise will not only reduce the riding comfort, but also affect the reliability of the vehicle transmission system, and then affect the dynamic performance, economy and durability of the automobile. Continuously improving the NVH performance of the transmission system has become a new technical breakthrough point and an important development direction for major automobile enterprises.

5.1.2.2

Modal Test and Analysis

Modal analysis is a common method to explore structure attributes, including frequency, mode of vibration and damping. If the external excitation frequency is close to the natural frequency of the system, the system will produce relatively large vibration, which should be avoided as much as possible during the structural design. There are two methods of modal analysis: computational modal analysis, which can be realized by computer simulation technology; and experimental modal analysis, which is a method for obtaining modal parameters by collecting and post-processing the experimental data with the help of test equipment. In practical engineering problems, the research system is mostly linearized in the modal analysis to solve the inherent characteristic parameters of the system and provide data support for fault diagnosis, vibration characteristic analysis and subsequent structural optimization of the system. Understanding the natural frequency and mode of vibration of the

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system can help the designer develop a system with better performance in vibration and noise. The modal information of a structure is the inherent attributes of the structure itself and independent from external factors. Modal analysis can be roughly divided into five stages: analysis theory, test conditions, test procedure, simulation analysis and result comparison. 1. Theory of modal analysis The modal analysis can be made to get the natural mode of vibration of each order of the part and the natural frequency corresponding to the mode of vibration of each order. It is to replace the physical coordinates in the original differential equation of the system with modal coordinates, so as to get the system response, providing a certain theoretical basis for studying the vibration and radiation noise of the parts. The most critical of modal analysis is to solve and analyze the modal parameters, which are mainly related to the properties of materials, the quality, thickness and shape of parts and other main parameters. The general form of the kinematic differential equation is [M]{X '' (t)} + [C]{X ' (t)} + [K ]{x(t)} = {F(t)}

(5.1)

where [M] is the mass matrix of the system; [C] is the damping matrix of the system; [K] is the stiffness matrix of the system; {X '' (t)},{X ' (t)} and {X(t)} are the acceleration, velocity and displacement vector of the system; {F(t)} is the external load of the system. The mass, stiffness, damping matrix and other element characteristics of the system are obtained based on the principle of virtual displacement. The process is as follows: Assuming that the virtual displacement generated by the node unit under the action of external load is {δq}e , resulting in the virtual displacement generated in the node of {δd}, and the virtual strain of {δε}, then its virtual strain is ¨ δU = {δε}T {σ }dV (5.2) V

where {σ } is element stress. In addition to the external excitation, the node is also subject to the inertia force ρ{d '' }dV and damping force v{d ' }dV . The density of the material is ρ, and the linear damping coefficient of the material is v. Based on this, the virtual work of the element is ˚ ¨ T δW = {δd} {PV }dV + {δd}T {PS }dA + {δd}T {PC } V

A

˚

''

˚

ρ{δd} d dV +

−

T

V

V

c{δd}T d ' dV

(5.3)

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where {Pv },{Ps } and {Pc } are the dynamic volume force, dynamic surface force and dynamic concentrated point force acting on the node; V and A are the element volume and element area, respectively. Since {d} = [N ]{q}e , {ε} = [B]{q}e . Where, [N] is only related to the coordinates x, y and z, representing the position matrix; [B] is strain matrix; {d} is the distance vector. So  {d} = [N ]{q ' }e (5.4) {d ' } = [N ]{q '' }e  {δd} = [N ]{δq}e (5.5) {δε} = [B]{δq}e where {δd} is virtual displacement; {δε} is virtual strain; {δq}e is virtual displacement. According to the virtual displacement theory, δU = δW

(5.6)

where δU is the virtual strain energy; δW is the virtual work of the element. Through the above derivation, the motion equation can be obtained: [m]e {q '' }e + [c]e {q ' }e + [k]e {q}e = {R(t)}e

(5.7)

where [k]e , [m]e and [c]e are the stiffness matrix, mass matrix and damping matrix of the element, i.e. ˚ [k]e = [B]T [D][B]dV (5.8) V

˚

[m] = e

[N ]T ρ[N ]dV

(5.9)

[N ]T v[N ]dV

(5.10)

V

˚ [c]e = V

where [D] is the elastic matrix; [N] is the position matrix; [B] is the strain matrix; ρ is the material density; v is the linear damping coefficient; V is unit volume. The differential equation of undamped free vibration of the system is [M]{X '' (t) + [K ]{X (t)} = 0 The simplified form of the solution can be obtained by analysis

(5.11)

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5 NVH Test and Optimization for New Energy Vehicle Powertrain

{X (t)} = {ϕ} sin ωt

(5.12)

where ω is circular frequency; {ϕ} is formation matrix. The equation can be obtained by the above two equations: ([K ] − ω2 [M]){ϕ} = 0

(5.13)

The condition for this equation to have a nonzero solution is | | |[K ] − ω2 [M]| = 0

(5.14)

Through Eq. (5.14), the natural frequency ωi and the natural mode of vibration {ϕ}i of the system can be obtained. 2. Modal test conditions Through the modal test of the transmission case, we can not only understand the basic parameters of the transmission case, such as the modal shape, natural frequency and damping of each order of modal, but also verify the accuracy of the finite element model of the transmission. Because the constrained modal can be calculated from the test results of the free modal, the free modal of the transmission case is mainly studied here. The hammering method is used for the free modal test. That is, a nylon hammer is used for the free modal test of single point excitation and multi-point response, and a force sensor is used to detect the hammering force of the nylon hammer to ensure that the force of each hammer is in a certain range, clean and nonadhesive. The test system mainly includes vibration excitation system (mainly force hammer/vibration exciter), response system (three-way acceleration sensor) and post-processing analysis system, as shown in Fig. 5.6. In order to reduce the influence of the supports on the free modal test results of the transmission case, the transmission case can be supported by hanging rubber rope in the modal test. To measure the overall modal shape of vibration of the transmission case, the free modal of the transmission case can be tested by mobile sensor method. Figure 5.7 shows the schematic diagram of the modal test. Vibration excitation force hammer Transmission case

Vibration acceleration sensor Data acquisition front end

Fig. 5.6 Modal test system

LMSTest.Lab analysis software

Modal parameters (modal shape and natural frequency, etc.)

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(a) Layout diagram of modal test points (b) Layout diagram of measuring points in modal test site Fig. 5.7 Schematic diagram of modal test

The nylon hammer is the excitation source of the modal test, which has high requirements on the hammering technique of the test personnel, and it is necessary to segment each hammering clearly without adhesion. Therefore, in order to improve the hammering efficiency of the test personnel, prevent the leakage of vibration energy and study the low-order modal of the transmission case, it is only necessary to measure the main modal parameters in the frequency band below 2500 Hz. The relationship of acceleration response with time is obtained by measurement, and the frequency response function is obtained by fast Fourier transform in the modal analysis module of LMSTest.Lab software. Then the frequency response function is post-processed to obtain the free modal shapes and natural frequencies of each order as shown in Fig. 5.8. Through the above analysis, it can be seen that the natural frequency of the first five orders of the measured transmission case are mainly concentrated within 500– 2500 Hz, and its local vibration is mainly manifested in the front case of the transmission, which makes the dynamic excitation force of gear meshing acting on the transmission case easily cause the vibration of the front case of the transmission. It can be seen that the front case of the transmission has fewer stiffeners and a larger panel area, so its stiffness is relatively weak. It is necessary to rearrange the stiffeners of its case to reduce the presence of large planes. 3. Transmission case modal test (1) Test purpose The modal analysis can be made to get the natural mode of vibration of each order of the part and the natural frequency corresponding to the mode of vibration of each order. It is to replace the physical coordinates in the original differential equation

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(a) First-order modal test shape pattern (942Hz)

(c) Third-order modal test shape pattern (1320Hz)

(b) Second-order modal test shape pattern (1290Hz)

(d) Fourth-order modal test shape pattern (1550Hz)

(e) Fifth-order modal test shape pattern (2130Hz)

Fig. 5.8 Free modal shape and natural frequency of each order

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of the system with modal coordinates, so as to get the system response, providing a certain theoretical basis for studying the vibration and radiation noise of the parts. The main modal frequency of the transmission case of a new energy bus produced by a company can be obtained through modal analysis. The transmission noise is mainly propagated in the form of structure borne noise. The propagation process of the structure borne noise is that the meshing dynamic response force of gear teeth is transmitted to the transmission case through gear shaft, bearings and other parts. When the frequency of the response force is close to the natural frequency of an order of the transmission case, the transmission case will produce a certain degree of resonance. Since the inherent characteristics of the transmission case are closely related to the transmission vibration and noise, the study of the inherent characteristics of the transmission case has certain guiding significance for the transmission vibration and noise reduction. (2) Test method The vibration excitation is generated by the hammering method using a nylon hammer (if the frequency range concerned is higher, a hammer with larger stiffness is selected). This test is conducted by single point excitation and multi-point response. The case under test is supported freely, that is, it is suspended by a hanging rubber rope to simulate free boundary conditions. (3) Test equipment The AremisClassical vibration and noise test system produced by HEAD Company is used for the transmission case modal test. The BW13510 piezoelectric force transducer is used to measure the acceleration, and the piezoelectric acceleration transducer is used to measure the response of each measuring point (each measuring point is measured in x, y and z directions simultaneously). The acquired signal is transmitted to ME’scopeVES v5.1 test and analysis system, and the data is processed by a microcomputer. (4) Test procedure According to the test requirements, the modal parameters of the test transmission case in each order in 500–3000 Hz frequency band are measured, including natural frequency, damping ratio and model shape. A total of 79 measuring points are arranged in the test. The acceleration response signals in x, y and z directions shall be tested at each measuring point, totaling 237 “point direction” response signals. The excitation—response time history is recorded four times at each measuring point, and then averaged as a time history to further eliminate the interference of noise signals. Figure 5.9 shows the layout of the measuring point coordinate system. The analysis bandwidth of the test is 32784 Hz, and the time history of a total of 79 force signals and 237 acceleration responses is recorded. The force signal of each excitation and the acceleration signal data of three directions at each measuring point collected in the test are processed on the modal analysis software with fast Fourier transform as the core. A total of 237 frequency response functions are obtained, and all of them are lumped, as shown in Fig. 5.10.

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Fig. 5.9 Layout of measuring point coordinate system

Fig. 5.10 Frequency response function lumping results

4. Modal simulation analysis In Hypermesh, Tetramesh method is used to generate tetrahedral meshes with the size controlled at 4 mm. Among them, 482,785 tetrahedral meshes can be obtained in the front cover, and 386,838 obtained in the back cover, a total of 869,623, as

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Fig. 5.11 Comparison between transmission case meshes and model

shown in Fig. 5.11. The transmission material is defined as cast aluminum (performance parameters: elasticity modulus of 70 GPa, Poisson’s ratio of 0.33, density of 2710 kg/m3 ), and the bolted part of the transmission is replaced by RBE2 unit. The finite element of transmission case is applied with zero displacement and six degrees of freedom constraint at the bolting point according to the actual driving cycle. The boundary conditions are added to the divided meshes, and the corresponding constraints and loads are added to calculate the constrained modal to obtain the modal shape and modal frequency of first 20 orders. 5. Results and comparison of modal test and simulation analysis (1) Comparison of modal results of transmission case of an electric bus The modal test and simulation analysis are carried out on the transmission case of an electric bus, and the results are compared in Table 5.1. The mode shapes of each order are shown in Figs. 5.12, 5.13, 5.14, 5.15 and 5.16. From the comparison between the modal test and simulation results, it can be seen that the modal shapes obtained by the test and simulation are basically consistent, Table 5.1 Comparison of natural frequency of modal test with simulation analysis results

Modal order

Natural frequency

Length × width × height

Test value/Hz

Calculated value/Hz

Relative error/(%)

1

942

1.02E03

8.28

2

1.29E03

1.35E03

4.65

3

1.32E03

1.41E03

6.82

4

1.55E03

1.57E03

1.29

5

2.13E03

2.17 E03

1.88

Note E03 represents ×

103

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Fig. 5.12 First-order modal simulation and test modal shape pattern

Fig. 5.13 Second-order modal simulation and test modal shape pattern

and the modal frequency differs little (< 10%), which basically indicates that the modal test is successful and the modal simulation model is more accurate and can be used for the next simulation and calculation. (2) Comparison of modal results of transmission case of an electric vehicle The computational modal analysis is made on the finite element model of the transmission case of an electric vehicle to obtain the natural frequencies under different order. After the test data is post-processed in the software, the modal shape and frequency of the tested specimen can be obtained. Table 5.2 shows the test results and simulation results of the first six orders of natural frequency.

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Fig. 5.14 Third-order modal simulation and test modal shape pattern

Fig. 5.15 Fourth-order modal simulation and test modal shape pattern

The comparison between the test results and simulation results of the modal shape of the transmission case is shown in Fig. 5.17. In the modal shape test results, the black line represents the original state of the transmission case, and the red line represents the position of the transmission case after vibration amplification. The accuracy of the finite element model is judged by comparing the error between the natural frequency of the case obtained by the test and the simulation result, and the similarity between the test modal shape and the simulation result. As can be seen from Table 5.2, the error between the simulation result of natural frequency and the test result fluctuates in the range of 1.3–9.6%, and the two results are relatively close. As can be seen from Fig. 5.17, the test modal

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Fig. 5.16 Fifth-order modal simulation and test modal shape pattern

Table 5.2 Natural frequency test results and simulation results Modal order

Natural frequency test result/Hz

Natural frequency simulation result/Hz

Relative error/(%)

1

1309

1337

2.1

2

1360

1491

9.6

3

1560

1581

1.3

4

1996

1951

2.3

5

2111

2155

2.1

6

2127

2217

4.2

shape of the same order is consistent with the simulation result, so the established finite element model is accurate and reliable.

5.2 NVH Optimization Technology 5.2.1 Powertrain NVH Optimization Technology With the continuous improvement of the BEV performance, the multi-gear automatic transmission will become the development trend of the electric drive system in the future. The NVH performance of the transmission system is extremely important for the battery electric vehicles, compared with traditional vehicles, because there is no engine noise coverage. Therefore, it is prospective and necessary to carry out research on the NVH performance of the multi-gear automatic transmission in battery electric vehicles.

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Fig. 5.17 Comparison between modal shape test results and simulation results

5.2.1.1

Analysis and Optimization of Internal Transmission System of Motor—Transmission

According to the design of the transmission drive route, a transmission system model of “motor rotor-transmission shaft gear” is established in Romax software, as shown in Fig. 5.18. Specific modeling steps are as follows:

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Fig. 5.18 “Motor rotor-transmission shaft gear” transmission system model

(1) Establish the models of the motor rotor, transmission shaft, gear pair, synchronizer, bearing and other parts, and define the design parameters, size, material properties, load spectrum and other model requirements of each part; (2) Assemble each part model according to the transmission system design drawing; (3) Add the power flow, run the model, and verify the feasibility of the model. In this case, the most common conditions are analyzed, namely, the transmission input speed of 9000 r/min, and the input torque of 84 N · m. In the “motor rotor-transmission gear” transmission system model, the moment of inertia of the motor stator is set to 0.04 kg · m2 according to the motor design parameters. The parameters of each meshing gear in the transmission are shown in Table 5.3. Table 5.3 Summary of parameters of each gear Gear No.

Number of teeth

Modulus/mm

Tooth width/mm

Pressure angle/(°)

Helical angle/(°)

Drive gear 1

19

1.989

24.5

20

34

2.106

23

18.5

30

2.288

33

20

25

Driven gear 1

57

Drive gear 2

36

Driven gear 2

43

Drive gear of final reduction drive

21

Driven gear of final reduction drive

82

19 22.9

32.4

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Table 5.4 Comparison of modal natural frequencies Order

Calculation frequency of finite element software/Hz

Calculation frequency of Romax software/Hz

1

1059

1176

11.0

2

1223

1212

−0.8

3

1269

1370

7.9

4

1713

1485

−13.3

5

1806

1839

1.8

6

1921

1961

2.1

7

1978

2013

1.8

8

2070

2120

2.4

9

2194

2209

0.7

10

2242

2341

4.4

5.2.1.2

Error/(%)

Modal Analysis

In order to verify the accuracy of the model, we compared the modal natural frequencies of the first 10 orders of the transmission case solved by different simulation analysis software, and the results are shown in Table 5.4. From the natural frequency, it can be seen that the calculation results obtained by the two analytical methods are basically consistent. The first three orders of modal shapes are compared, as shown in Fig. 5.19. The modal shape comparison results show good consistency, which fully demonstrates the reliability of the transmission model established by the finite element analysis software, and provides a basis for the accuracy of the following simulation analysis.

5.2.1.3

Transfer Error Analysis

If a perfect pair of gears meshes at zero load, the involute geometry dictates that the length of the contact point of the driven gear is equal to that of the drive gear and that the rotation angles are proportional to the number of teeth. However, due to the machining error, assembly error and other factors, the driven gear is in the front or rear of the theoretical position. From the perspective of measured rotation angle, the gear transfer error can be expressed as TE = θ2 rb2 − θ1rb1

(5.15)

where TE is the transfer error; θ2 and θ1 are the rotation angles of the driven gear and drive gear respectively; rb2 and rb1 are the radius of the base circle of the driven gear and the drive gear respectively.

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Fig. 5.19 Comparison between modal shape analysis by finite element software and by Romax software

In the process of torque transfer, the gear is affected by gear deformation and gear error, and the gear transfer error fluctuates with time and position. As a kind of dynamic excitation, the fluctuating gear transfer will lead to load fluctuation on the gear, resulting in vibration and noise. Therefore, reducing the gear transfer error fluctuation can reduce the gear vibration and noise. The contact spot on tooth surface is one of the important indexes to measure the gear meshing quality. Due to the manufacturing and installation errors, support rigid deformation, bearing clearance and load deformation of each component, the gear meshing will usually deviate from the ideal position. The uneven load distribution on the tooth surface will cause the partial load in the gear drive process, resulting in the drive instability, vibration and noise. The size, position and shape of the contact spots on the tooth surface will have a significant impact on the meshing stability, strength and life of the gear, as well as the vibration and noise of the transmission. Micro modification of gear teeth is a good method to reduce vibration and noise for the transmission, which can compensate for the meshing deviation caused by the deformation of the gear shaft and gear teeth, so as to reduce the fluctuation of meshing transfer error of the gear pair. However, the micro modification of gear

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Table 5.5 Optimal modification parameters of each gear Gear No.

Profile crowning/μm

Axial helical angle/(°)

Axial crowning/μm

Profile slope/μm

Drive gear 1

2

6

3

0

Drive gear 2

1.5

2

4

0

Drive gear of final reduction drive

2

12

4

−2

has little effect on the overall structure of the transmission. The micro modification of gear mainly includes axial modification and profile modification, and the main modification parameters are crowning and helical angle. (1) Crowning modification. During gear meshing, certain backlash effect will occur, which will cause stress concentration and depression on the local area of the tooth surface, and the gear will undergo elastic deformation such as bending and torsion after load. Therefore, micro crowning profile and axial modifications can be performed to improve the distribution of gear meshing stress. (2) Helical angle modification. Increasing the helical angle of the tooth surface can improve the coincidence degree and stiffness of the tooth surface and adjusting the helical angle can improve the tooth contact area. According to the above modification theory, the drive gears of the three pairs of meshing gears are modified in Romax. After multiple comparisons, the optimal modification parameters are shown in Table 5.5. The contact stress distribution on the tooth surface before and after modification is shown in Fig. 5.20, where the abscissa is the tooth surface distance (unit: mm) and the ordinate is the rolling angle (unit: °). The shade of color in the figure indicates the magnitude of the contact stress. As can be seen from Fig. 5.20, the stress concentration distribution on the tooth surface shifts from the edge of the gear surface to the center of the gear surface after modification, improving the gear partial load. After overall consideration, although the unit length load of gear 2 is only increased by 9.6%, the distribution uniformity of the tooth surface stress and the partial load are greatly improved, which still plays a positive role in reducing the vibration and noise in the process of gear drive. Figure 5.21a–e shows the fluctuation of the transfer error before and after modification of gear 1 under different driving cycles. After gear modification, the displacement along the meshing line is increased, but the fluctuation is significantly reduced, the curve becomes more regular and smooth, and the gear drive process is more stable. Figure 5.21f shows the changes of the transfer error peak-valley values under different input torques before and after the modification of gear 1. Except for a small increase under the 20% torque condition, the transfer error peak-valley values under other driving cycles decrease significantly, a decrease of 50% under the 40% torque condition, and a decrease of more than 30% under the 60% torque and 80% torque conditions. Since the transmission is commonly used at 40–70% torque, the modification solution has achieved the desired effect.

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5 NVH Test and Optimization for New Energy Vehicle Powertrain Load per unit length (N/mm)

(a) Gear 1 before modification Load per unit length (N/mm)

(c) Gear 2 before modification Load per unit length (N/mm)

(e) Drive gear of final reduction drive before modification

Load per unit length (N/mm)

(b) Gear 1 after modification Load per unit length (N/mm)

(d) Gear 2 after modification Load per unit length (N/mm)

(f) Drive gear of final reduction drive after modification

Fig. 5.20 Contact stress distribution on tooth surface of drive gear of each meshing gear pair before and after modification

Figure 5.22a–e shows the fluctuation of the transfer error before and after modification of gear 2 under different driving cycles. After gear modification, the displacement along the meshing line is increased, but the fluctuation is significantly reduced, the curve becomes more regular and smooth, and the gear drive process is more stable. Figure 5.22f shows the changes of the transfer error peak-valley values under different input torques before and after the modification of gear 2. The transfer error peak-valley values after gear modification are significantly decreased compared with those before gear modification under different driving cycles, a decrease of more than 50% at 40–80% torque, indicating that the gear modification effect is significant. Figure 5.23a–e shows the fluctuation of the transfer error before and after modification of the gear of the final reduction drive under different driving cycles. After gear modification, the displacement along the meshing line is increased, but the fluctuation is significantly reduced, the curve becomes more regular and smooth, and the gear drive process is more stable. Figure 5.23a–e shows the fluctuation of the transfer error before and after modification of the gear of the final reduction drive

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Fig. 5.21 Statistics of transfer errors before and after modification of gear 1 under different driving cycles

under different driving cycles. The transfer error peak-valley values after gear modification are significantly decreased compared with those before gear modification under different driving cycles, a decrease of more than 60% at 60% and 80% torque and more than 50% at 40% and 100% torque, indicating that the modification solution has achieved the desired effect.

5.2.2 Vibration and Noise Optimization of Electric Drive Powertrain 1. Case meshing

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Fig. 5.22 Statistics of transfer errors before and after modification of gear 2 under different driving cycles

The transmission case and motor case models are imported into the finite element analysis software. The transmission case is divided into 5 mm tetrahedral meshes, and the motor case is divided into 4 mm tetrahedral meshes. A total of 884,008 nodes and 488,136 units are obtained. The bolted connection among the transmission case, motor case and external suspension is simulated by RBE unit. According to the specification of the powertrain bench test, the bolted connection among the transmission, motor and bench is constrained by six degrees of freedom. Figure 5.24 shows the model diagram after introduction of the outer case into Romax. 2. Vibration response analysis Vibration response distribution point: From the case meshing nodes, Node 128,058 is selected for the vibration acceleration acquisition of the input shaft, Node 123,512 for

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Fig. 5.23 Statistics of transfer errors before and after modification of the gear of the final reduction drive under different driving cycles

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Fig. 5.24 Model diagram after introduction of the outer case into Romax

the vibration acceleration acquisition of the intermediate shaft and Node 133,714 for the vibration acceleration acquisition of the differential shaft, as shown in Fig. 5.25. The vibration acceleration simulation analysis is carried out in Romax, and the vibration acceleration values of the transmission case before and after modification are compared by solving and measuring the three nodes. First, the vibration acceleration cloud diagram of the transmission case at each gear meshing frequency is solved, as shown in Fig. 5.26. The gear meshing frequency is the speed of the gear multiplied by the number of teeth. The gear meshing frequency Fig. 5.25 Schematic diagram of vibration acceleration simulation points

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of gear 1 is 1583 Hz, and the gear meshing frequency of the final reduction drive of gear 1 is 583 Hz. The gear meshing frequency of gear 1 is 5400 Hz, and the gear meshing frequency of the final reduction drive of gear 2 is 2637 Hz. Second, build an acoustic meshes. In the acoustic simulation software, set the case material to aluminum alloy, the density to 2700 kg/m3 , Poisson’s ratio to 0.33, and Young’s modulus to 7.1 × 1011 N/m2 . The surface meshes are used to generate acoustic meshes, and the fluid material is set to air. The resulting acoustic mesh envelope is shown in Fig. 5.27. Finally, the data at the up, down, left, right, front and rear noise measuring points are calculated and collected on the established sound field, and each measuring point is set to be 1 m away from the case. In the range of 100–2000 Hz, the radiation noise data of the transmission case at two gear meshing frequencies are calculated, as shown in Figs. 5.28 and 5.29.

Fig. 5.26 Cloud diagram of vibration acceleration on the case surface at the meshing frequency of each gear

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Fig. 5.27 Acoustic mesh envelope Up measuring point Down measuring point Front measuring point Rear measuring point Left measuring point

Noise/dB

Right measuring point

Frequency/Hz Fig. 5.28 Frequency response curve at meshing frequency of gear 1

The calculated noise value is below 75 dB, in line with the requirement for the BEV reducer noise lower than 83 dB in the automobile industry standard QC/T 1022– 2015 Technical Specification for Reduction Gearbox of Battery Electric Passenger Cars. Based on the above analysis, it can be concluded that the modification of the microscopic parameters of the transmission drive system gears can effectively reduce the vibration and noise generated by the transmission itself, thus playing a positive role in the NVH performance optimization process of the electric drive powertrain. The axial and profile modification of the crowning and helical angle of the main microscopic parameters reduces the gear transfer error and optimizes the load distribution on tooth surface. Through the co-simulation of finite element software and

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Up measuring point Down measuring point Front measuring point Rear measuring point Left measuring point

Noise/dB

Right measuring point

Frequency/Hz Fig. 5.29 Frequency response curve at meshing frequency of gear 2

Romax software, the vibration response and radiation noise of transmission before and after gear modification are calculated, and the improvement of NVH performance of transmission and electric drive powertrain by gear modification is verified.

5.3 Practical Case of Vibration and Noise Optimization of Pure Electric Bus Powertrain 5.3.1 Vehicle NVH Performance Test The vehicle NVH is a comprehensive problem of automobile manufacturing quality that gives automobile users the most direct and apparent feelings. It is one issue of concern in the international automobile manufacturers and parts enterprises. Statistics show that about 1/3 of vehicle faults are related to the vehicle NVH, and companies spend nearly 20% of their R&D expenses on solving the NVH problem.

5.3.1.1

Test Overview

Define the test purpose and make the test preparations When conducting the vehicle NVH test. Test and study the NVH problem of the powertrain of a self-owned electric bus: clarify the main frequency content of the powertrain that affects the interior noise; test the main interior and powertrain NVH problems under vehicle condition; test the

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interior and powertrain NVH problems under different speed and torque conditions under bench condition. In the vehicle NVH test, there are some differences between the bench test and vehicle road test. The structure of the powertrain is not consistent. The powertrain is equipped with a clutch in the vehicle state and not equipped with a clutch in the bench test; the load form of the powertrain is road load in the vehicle state and “back to back” in the bench test, which is quite different from the actual road test load condition; the test environment is the road condition of the real vehicle in the vehicle state, in line with the actual operating condition of the vehicle, while the test environment is a diffusion field in the bench test, with the background noise required to be considered. Therefore, the test results of the powertrain in the whole vehicle and the bench conditions have certain differences and only have mutual reference significance. Test preparation includes vehicle road test preparation and bench test preparation. 1. Vehicle road test preparation (1) (2) (3) (4) (5)

Test vehicle: a pure electric bus of a self-owned brand. Test equipment: Landtop 24-channel vibration and noise test module. Test road surface: smooth asphalt road surface with a certain slope. Powertrain: Powertrain equipped with clutch. Weather conditions: good weather with low wind speed.

2. Bench test preparation (1) Motor: power 120/180 kW, torque 573/1400 N · m and speed 2000/4000 (r/min). (2) Transmission: drive ratio 4.396 in gear 1, 2.427 in gear 2, 1.483 in gear 3, 1 in gear 4, maximum input torque of 1000 N · m. (3) Test equipment: Landtop 24-channel vibration and noise test module. (4) Test environment: bench and diffusion field. This test is based on the test bench in the semi-anechoic chamber. According to the provisions of the Rig Testing Method for Auto Manual Transmission Assembly, the transmission input torque is greater than or equal to 700 N · m, which belongs to the heavy-duty transmission. The bench is placed in a semi-anechoic chamber, which provides a test environment with low background noise and half free field. The powertrain system consisting of the drive motor and transmission is installed on a test bench with sufficient stiffness. The transmission input shaft axis is not less than 400 mm from the ground during installation. The transmission oil temperature is controlled at about 60 °C. Four measuring points are arranged in the left, right, top and front of the transmission under test, of which, the left, right and front measuring points shall be as high as the transmission input shaft axis. The sound level meter arranged at each measuring point is aligned with the measured surface at zero incidence angle. According to the standard, if the transmission axial distance is greater than or equal to 300 mm, the distance from the measuring point to the transmission case shall be 300 mm. The test conditions shall be specified according to the actual situation and

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the data is collected under the specified conditions; according to the standard, the acquisition time of each group of data shall be greater than or equal to 10 s.

5.3.1.2

Test Procedure

1. Test content and steps (1) Vehicle test The vehicle test channels are set as shown in Table 5.6. Solution 1: In the original state, there are a total of 12 measuring points in the vehicle and powertrain for 24-channel vibration and noise test, as shown in Fig. 5.30. Solution 2: When the overall powertrain is shielded, there are a total of 12 measuring points in the vehicle and powertrain for 24-channel vibration and noise test, as shown in Fig. 5.31. Solution 3: When the single transmission is shielded, there are a total of 12 measuring points in the vehicle and powertrain for 24-channel vibration and noise test, as shown in Fig. 5.32. (2) Bench test Table 5.6 Vehicle test channel settings Channel name

Corresponding measuring point (noise)

Channel name

Corresponding measuring point (vibration)

1

Interior

7–9

Gearbox-front

2

Gearbox-front

10–12

Gearbox-left

3

Gearbox-left

13–15

Gearbox-up

4

Gearbox-up

16–18

Gearbox-rear

5

Gearbox-rear

19–21

Clutch

6

Motor

22–24

Motor

Fig. 5.30 Solution 1

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Fig. 5.31 Solution 2

Fig. 5.32 Solution 3

To analyze the powertrain NVH level, the back-to-back loading test is performed on the powertrain bench using the two same pairs of powertrain. The test cannot be carried out in the vehicle state under the powertrain full acceleration condition and can be carried out only under the steady-state condition. In addition, considering that the test is conducted in a reverberation chamber, a background test shall be performed at the beginning of the test to exclude background noise effect. Due to the use of the “back-to-back” test format, the powertrain noise test results will be different from the whole vehicle case. (3) Sensor layout Microphones are arranged at noise measuring points: Gearbox-front, Gearbox-up, Gearbox-rear, Gearbox-left, Gearbox-right, Motor-rear; Three-way acceleration sensors are arranged at vibration measuring points: Clutch, Gearbox-up, Gearbox-rear, Gearbox-left, Gearbox-right, Motor-rear. (4) Background noise test Test the gear 2 and gear 3 of the powertrain system at different speeds and torches, and record relevant sensor data. The test conditions are shown in Table 5.7. 2. Test procedure diagram

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Table 5.7 Powertrain bench test conditions Rotational speed/(r/min) 900 1100 1300 1500 1800

Torque/(N · m) 200 √

300 √

400 √

500 √

600 √

700 √

800 √

√

√

√

√

√

√

√

√

√

√

√

√

√

√

√

√

√

√

√

The vehicle for the vehicle test, the damping plate sealing and the test bench are shown in Figs. 5.33, 5.34 and 5.35 respectively. The measuring points for the vehicle test are arranged in Figs. 5.36 and 5.37. The red dots in the figure represent the noise measuring points. Figure 5.38 shows the layout of 6 sound pressure sensor measuring points in the vehicle state. The noise test point near the powertrain is 100 mm away from the surface of the powertrain case. Fig. 5.33 Vehicle for the vehicle test

Fig. 5.34 Damping plate sealing

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Fig. 5.35 Test bench

Fig. 5.36 Arrangement of measuring points for vehicle test

Fig. 5.37 Arrangement of measuring points relative to the powertrain

The measuring points for the bench test are arranged in Fig. 5.39. The red blocks in the figure represent the vibration measuring points and the red dots represent the noise measuring points.

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Fig. 5.38 Arrangement of 6 sound pressure sensor measuring points in the vehicle state

Fig. 5.39 Arrangement of vibration measuring points in bench test

5.3.1.3

Test Results and Analysis

The subjective feeling of interior noise obtained by the three solutions is as follows: Solution 1: In the original state, subjectively feel that the high-frequency noise of the motor and transmission in the vehicle is at an intolerable level; the powertrain

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noise of gear 2 and gear 3 is higher than that of gear 4; the shift gap noise will disappear; the noise will continue to increase during acceleration. Solution 2: When the whole powertrain is covered with sound-absorbing cotton, subjectively feel that the high-frequency whistling sound of the motor and transmission in the vehicle is improved significantly. Solution 3: When the transmission is wrapped with sound-absorbing cotton, subjectively feel that the motor noise in the vehicle is relatively large, and the high-frequency whistling sound of the transmission is improved significantly.

5.3.2 Relationship Between Powertrain Parameters and Time in Three Test Solutions of Vehicle Road Test Figures 5.40, 5.41 and 5.42 show the relationship between the vehicle speed, motor speed, motor torque and time in the road test, and Table 5.8 shows the change interval of each test parameter.

Fig. 5.40 Relationship between vehicle speed and time

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Fig. 5.41 Relationship between motor speed and time

Fig. 5.42 Relationship between motor torque and time

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Table 5.8 Change interval of test parameters

Test parameters

Change interval 20–54

Vehicle speed/(km/h) Motor speed/(r/min)

Gear 2 Gear 3

1250–2150–1300 1300–2000–1300 723–920

Motor torque/(N · m)

5.3.3 Order Analysis of Vehicle Powertrain Transmission and Motor Vibration and Noise 5.3.3.1

Calculation of Vibration and Noise Order of Main Gear Sets of Transmission Vibration and noise order of normally engaged gear set = number of drive gear teeth of normally engaged gear

(5.16)

Order of vibration and noise of shift gear set of gear 2 = number of drive gear teeth of normally engaged gear/ number of driven gear teeth of normally engaged gear × number of drive gear teeth of shift gear set of gear 2

(5.17)

Order of vibration and noise of shift gear set of gear 3 = number of drive gear teeth of normally engaged gear/ number of driven gear teeth of normally engaged gear × number of drive gear teeth of shift gear set of gear 3

(5.18)

The number of teeth of each gear set of the transmission used in this test is shown in Table 5.9. Equations (5.16), (5.17) and (5.18) are used to calculate the transmission gear meshing order combined with the data listed in Table 5.9, and the calculation results are shown in Table 5.10. Table 5.9 Number of teeth of each gear set

Number of teeth

Gear Normally engaged gear Output stage gear 2 Output stage gear 3

Drive gear

30

Driven gear

46

Drive gear

24

Driven gear

38

Drive gear

31

Driven gear

30

5.3 Practical Case of Vibration and Noise Optimization of Pure Electric … Table 5.10 Transmission gear meshing order

5.3.3.2

291

Rotation order

Normally engaged gear

Output stage gear 2

Output stage gear 3

Order 1

30

15.6

20.2

Order 2

60

31.3

40.4

Order 3

90

46.9

60.6

Calculation of Motor Vibration and Noise Order

Radial electromagnetic force vibration and noise order = 2 × p ×

Stator cog harmonic vibration and noise order = Z ×

N ×h 60 (5.19)

N ×h 60

Torque ripple vibration and noise order = LC M(Z , 2P) ×

N ×h 60

Tangential electromagnetic force vibration and noise order = 2 × p ×

(5.20) (5.21) N ×h 60 (5.22)

where Z is the number of stator cogs; p is the number of rotor pole pairs; N is the motor speed; LCM means the least common multiple; h is the noise order.

5.3.4 Vibration Test Results and Analysis for Powertrain in Road Test (1) See Figs. 5.43 and 5.44 for the vibration Gearbox-front in gear 2 and gear 3. (2) See Figs. 5.45 and 5.46 for the vibration Gearbox-right in gear 2 and gear 3. (3) See Figs. 5.47 and 5.48 for the vibration Gearbox-up in gear 2 and gear 3. (4) See Figs. 5.49 and 5.50 for the vibration Gearbox-rear in gear 2 and gear 3. (5) See Figs. 5.51 and 5.52 for the vibration Clutch in gear 2 and gear 3. (6) See Figs. 5.53 and 5.54 for the vibration Motor in gear 2 and gear 3. According to the analysis of the test results:

test results of the measuring point test results of the measuring point test results of the measuring point test results of the measuring point test results of the measuring point test results of the measuring point

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Fig. 5.43 Vibration test results of measuring point Gearbox-front in gear 2

(1) By observing the vibration acceleration order of each measuring point in gear 2 and gear 3, it can be found that the orders 15.6 and 30 in gear 2 and orders 20.2 and 30 in gear 3 have large amplitudes, indicating that the meshing noise of transmission gears is serious, and the NVH of relevant gears shall be observed. (2) By observing the vibration acceleration order of the measuring points on the motor case, it can be found that the order 96 has large amplitude, indicating that the stator cogs of the motor produce large vibration and noise, and it is necessary to optimize the motor part. (3) By observing the vibration acceleration order of each measuring point in gear 2 and gear 3, it can be found that the vibration acceleration amplitude in gear 3 is significantly higher than that in gear 2, and order is multiplied. The gear 3 shall be the focus of optimization in the NVH optimization of the transmission gear.

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Fig. 5.44 Vibration test results of measuring point Gearbox-front in gear 3

5.3.5 Interior Noise Test Results in Vehicle Road Test (1) See Figs. 5.55 and 5.56 for the test results of interior noise in gear 2 and gear 3. (2) See Figs. 5.57, 5.58 and 5.59 for the relationship between the noise of each order in the two gears and the speed as well as their mean values. According to the test results: (1) The noise in gear 2 is mainly the shift gear meshing noise in the low and high speed sections and mainly normally engaged gear noise in the medium speed section. (2) The noise in gear 3 is mainly the shift gear meshing noise;

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Fig. 5.45 Vibration test results of measuring point Gearbox-right in gear 2

(3) Of the gear meshing noise in gear 2 and gear 3, the shift gear meshing noise in gear 3 is the most serious, followed by the shift gear meshing noise in gear 2. Therefore, the optimization design of transmission gear shall be based on the optimization of shift gears in gear 2 and gear 3. According to the NVH test results in the vehicle state, the powertrain system shielding and the bulk shielding have significantly improved the interior noise. Meanwhile, combined with the interior noise waterfall diagram, and by reference to the experience of other projects, it can be known that this electric bus can improve the interior noise comfort by matching the powertrain system with a suitable sound insulation cover. According to the vehicle NVH test, the main gears affecting the interior noise are the shift gear 3 and shift gear 2, followed by the normally engaged gear.

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Fig. 5.46 Vibration test results of measuring point Gearbox-right in gear 3

5.4 Practical Case of Vibration and Noise Optimization of Two-Speed Automatic Transmission for Battery Electric Vehicles 5.4.1 Test Purpose and Preparation The purpose of this test is to obtain the main frequency content of the influence of the powertrain on the interior noise in the bench state; test the powertrain NVH problem at different speed and torque under test bench conditions; test the contribution of the motor and transmission to the powertrain noise.

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Fig. 5.47 Vibration test results of measuring point Gearbox-up in gear 2

The equipment required for the test includes Landtop 24-channel vibration, noise test module, noise sensor, acceleration sensor, lead sheath, semi-anechoic chamber and test bench. This test is based on the test bench in the semi-anechoic chamber. According to the provisions of the Rig Testing Method for Auto Manual Transmission Assembly, the transmission input torque is greater than or equal to 700 N · m, which belongs to the heavy-duty transmission. The bench is placed in a semi-anechoic chamber, which provides a test environment with low background noise and half free field. The powertrain system consisting of the drive motor and transmission is installed on a test bench with sufficient stiffness. The transmission input shaft axis is not less than 400 mm from the ground during installation. The transmission oil temperature is controlled at about 60 °C. Four measuring points are arranged in the left, right, top and front of the transmission

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Fig. 5.48 Vibration test results of measuring point Gearbox-up in gear 3

under test, of which, the left, right and front measuring points shall be as high as the transmission input shaft axis. The sound level meter arranged at each measuring point is aligned with the measured surface at zero incidence angle. According to the standard, if the transmission axial distance is greater than or equal to 300 mm, the distance from the measuring point to the transmission case shall be 300 mm. The test conditions shall be specified according to the actual situation and the data is collected under the specified conditions; according to the standard, the acquisition time of each group of data shall be greater than or equal to 10 s. In this bench test, the powertrain vibration and noise test, the motor unit noise test (lead sheath wrapped transmission), and the transmission unit noise test (lead sheath wrapped motor) are carried out. When the motor and transmission are wrapped in dense lead sheath, the measured noise is more similar to the unit noise.

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Fig. 5.49 Vibration test results of measuring point Gearbox-rear in gear 2

5.4.2 Test Procedure The test procedure is shown in Fig. 5.60.

5.4.2.1

Arrangement of Measuring Points in Bench Test

The measuring points and channels are shown in Fig. 5.61 and Table 5.11. Figures 5.62 and 5.63 show the arrangement of noise and vibration measuring points in the bench test, respectively. Six microphones are arranged on the shaft axis of the transmission input shaft 300 mm away from the case, and six acceleration

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Fig. 5.50 Vibration test results of measuring point Gearbox-rear in gear 3

sensors are respectively placed on the case corresponding to the microphones to read and record the data of the acceleration sensor in three directions.

5.4.2.2

Test Content and Steps

1. Test content Test the radiation noise level of the transmission unit and motor unit in the powertrain at different speed and torque in gear 2 and gear 3 working conditions respectively, test the radiation noise level of the transmission and motor unit in case of wrapped motor and wrapped transmission using the leading method respectively and record relevant sensor data.

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Fig. 5.51 Vibration test results of measuring point Clutch in gear 2

2. Test steps First, measure the background noise in the semi-anechoic chamber before the powertrain is driven, and then test in following three states respectively. State 1: Vibration and noise test of the whole powertrain, as shown in Fig. 5.64. A total of 12 measuring points (6 noise sensors and 6 acceleration sensors) are arranged for 24-channel vibration and noise test. State 2: Noise test of the lead sheath wrapped transmission and motor unit, as shown in Fig. 5.65. A total of 6 measuring points (6 noise sensors) are arranged for 6-channel noise test. State 3: Noise test of the lead sheath wrapped motor and transmission unit, as shown in Fig. 5.66. A total of 6 measuring points (6 noise sensors) are arranged for 6-channel noise test.

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Fig. 5.52 Vibration test results of measuring point Clutch in gear 3

5.4.2.3

Test Conditions

Test the powertrain system, transmission unit and motor unit at different speed and torque in gear 2 and gear 3, and record the relevant sensor data. The acquisition time under each driving cycle is set as 10 s according to the standard. See Table 5.12 for specific test conditions, and Table 5.13 for gear meshing frequency and motor excitation force. Clarify the vibration spectrum characteristics of the powertrain by analyzing the characteristics of powertrain vibration frequency and amplitude at different speed and torque in gear 2 and gear 3 according to the actual situation of the powertrain bench test.

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Fig. 5.53 Vibration test results of measuring point Motor in gear 2

(1) Tables 5.14, 5.15, 5.16, 5.17, 5.18 and 5.19 show the gear meshing frequency at different torque in gear 2. (2) Tables 5.20, 5.21, 5.22, 5.23 and 5.24 show the gear meshing frequency at different torque in gear 3. (3) Gear 2 and Gear 3 at 500 N · m are selected. Their speed and vibration acceleration amplitude are shown in Table 5.25, and the drawn curve is shown in Fig. 5.67.

5.4.3 Result Analysis According to the test data, the following results are obtained:

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Fig. 5.54 Vibration test results of measuring point Motor in gear 3

(1) At different speed and torque in gear 2 and gear 3, the vibration frequency of the powertrain transmission is consistent with the meshing frequency of the normally engaged gear and the shift gears of gear 2 and gear 3, that is, the frequency of the test results corresponds well with the theoretical calculated frequency. This shows that the normally engaged gear of the transmission and the shift gears of gear 2 and gear 3 are the main reason for transmission vibration. (2) At low speed (below 1200 r/min), the vibration acceleration amplitude of the normally engaged gear is lower than that of the shift gear. When the speed exceeds 1200 r/min, the vibration acceleration amplitude of the normally engaged gear is higher than that of the shift gear. (3) The vibration acceleration amplitude of the shift gear in gear 3 is higher than that in gear 2, indicating that the vibration problem of the transmission gear 3 is more serious.

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Fig. 5.55 Interior noise in gear 2

(4) The vibration of Gearbox-front is more obvious than that at other measuring points. 5.4.3.1

Comparison of Vibration Comparison at Each Measuring Point of Motor and Transmission

The vibration test results of the motor and transmission at 800 N · m–1400 r/min are selected for comparative analysis. In the following vibration results, red is the vibration in the x direction, green is the vibration in the y direction, and blue is the vibration in the z direction. (1) See Figs. 5.68, 5.69, 5.70, 5.71, 5.72 and 5.73 for the vibration at each measuring point of the motor/transmission in gear 2.

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Fig. 5.56 Interior noise in gear 3. Note The main gear noise orders are 15.6 and 30 in gear 2 and 20.2 and 30 in gear 3

(2) See Figs. 5.74, 5.75, 5.76, 5.77, 5.78 and 5.79 for the vibration at each measuring point of the motor/transmission in gear 3. (3) According to the above statistical vibration results, the following conclusions can be drawn: ➀ The powertrain vibration at 0–3500 Hz is mainly caused by the transmission, wherein 365 and 1095 Hz are the meshing frequencies of two shift gears; 700 and 1400 Hz are the meshing frequencies of the normally meshing gear; 2240 Hz is the stator cog harmonic frequency of the motor. ➁ The powertrain vibration at 3500–6000 Hz is mainly caused by the motor, wherein 448 and 5552 Hz are the switching frequencies of the motor.

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Fig. 5.57 Change of the noise at each order in gear 2 with rotation speed

Fig. 5.58 Change of the noise at each order in gear 3 with speed

5.4 Practical Case of Vibration and Noise Optimization of Two-Speed …

307

Fig. 5.59 Average noise value at each order in gear 2 and gear 3

Powertrain Semi-anechoic chamber

Transmission wrap Bench

Motor wrap

Fig. 5.60 Test procedure

Signal acquisition

308

5 NVH Test and Optimization for New Energy Vehicle Powertrain

Drive motor Transmissi on

Load motor Assistant transmission

Fig. 5.61 Top view of semi-anechoic chamber and measuring point arrangement. 1—Post treatment equipment; 2—Signal acquisition front end; 3—Wiring harness; 4—Bench; 5—Drive motor; 6—Transmission; 7—Semi-anechoic chamber; 8—Transmission shaft; 9—Assistant transmission; 10—Load motor; 11, 12, 13, 14, 15, 16—Noise sensor; 21, 22, 23, 24, 25, 26—Vibration acceleration sensor

Table 5.11 Test channel settings Channel name

Corresponding measuring point (noise)

Channel name

Corresponding measuring point (vibration)

1

Gearbox-front

7–9

Gearbox-front

2

Gearbox-up

10–12

Gearbox-up

3

Gearbox-left

13–15

Gearbox-left

4

Gearbox-right

16–18

Gearbox-right

5

Motor-up

19–21

Motor-up

6

Motor-rear

22–24

Motor-rear

➂ The transmission vibration is the main vibration at low frequency, and the motor vibration is the main vibration at high frequency. ➃ Comparing the vibration at 4 measuring points of transmission, it is found that the vibration is most severe at Gearbox-front; comparing the vibration at 2 measuring points of the motor, it is found that the vibration at Motor-rear is slightly larger than that at Motor-up. 5.4.3.2

Test Results and Analysis of Transmission and Motor Unit Motor

Combined with the actual driving cycles of the electric vehicle, the actual driving cycles of the vehicle are simulated on the bench in the semi-anechoic chamber, with

5.4 Practical Case of Vibration and Noise Optimization of Two-Speed …

309

Fig. 5.62 Arrangement of noise measuring points in bench test

Fig. 5.63 Arrangement of vibration measuring points in bench test

the focus on the typical driving cycles of the vehicle (600 N · m–1800 r/min, 700 N · m–1600 r/min, 800 N · m–1400 r/min) for comparative analysis of the powertrain radiation noise. The typical driving cycles are shown in Table 5.26. The following is an analysis of the noise level at the near field measuring point of the motor and transmission when the motor noise and transmission noise are shielded respectively at gear 2, so as to clarify the contribution of the motor and transmission to the noise. Figures 5.80, 5.81 and 5.82 show the noise test results under three typical driving cycles respectively.

310

5 NVH Test and Optimization for New Energy Vehicle Powertrain

Fig. 5.64 State 1

Fig. 5.65 State 2

Fig. 5.66 State 3

The above test results can be summarized as follows: (1) Comparing the near field (1 m) of the motor and the transmission, it can be seen that the transmission radiation noise is higher than the motor radiation noise on the whole; (2) Ranking of noise contribution degree at each measuring point of the transmission: Gearbox-left > Gearbox-right > Gearbox-up;

5.4 Practical Case of Vibration and Noise Optimization of Two-Speed …

311

Table 5.12 Bench test conditions Revolving speed 800 r/min 1000 r/min 1200 r/min 1400 r/min 1600 r/min 1800 r/min 2000 r/min 2200 r/min

Torque 500 N · m √

600 N · m √

700 N · m √

800 N · m √

900 N · m √

950 N · m √

√

√

√

√

√

√

√

√

√

√

√

√

√

√

√

√

√

√

√

√

√

√ √

(3) Ranking of noise contribution degree at each measuring point of the motor: motor-rear > motor-up. Calculate the root mean square (RMS) value of the noise test results at each measuring point under the three driving cycles selected in gear 2 to obtain the contribution of noise sources at each measuring point, as shown in Table 5.27.

5.4.3.3

Comparative Analysis of Noise Results of Gear 2 and Gear 3

(1) See Figs. 5.83, 5.84 and 5.85 for the comparison of the noise at each measuring point in gear 2 and gear 3. Comparing and analyzing the radiation noise of the powertrain in gear 2 and gear 3, it can be seen that the influence of the noise in gear 3 is greater than that in gear 2, and the noise in gear 3 shall be optimized first. (2) The changes in the noise RMS value at each measuring point in gear 2 and 3 under different driving cycles are shown in Figs. 5.86, 5.87, 5.88, 5.89, 5.90, 5.91, 5.92, 5.93, 5.94 and 5.95. It can be seen from the above changes that the noise RMS value at each measuring point increases with the speed at the same torque; at the same speed, the noise RMS value at each measuring point increases with torque; the noise RMS value level at each measuring point in gear 3 is higher than that at each measuring point in gear 2.

5.4.3.4

Noise at Each Measuring Point Before and After Motor/Transmission Wrapping

The noise results at each measuring point before and after the wrapping of the motor and transmission at 700 N · m–1600 r/min are shown in Figs. 5.96, 5.97, 5.98 and 5.99.

1600 1600

1280 213

Torque ripple frequency/Hz

Tangential electromagnetic force/N 267

267

1280

270

Stator cog harmonic frequency (order k)/Hz

Meshing frequency of gear 3/Hz 213

1000 500

Radial electromagnetic force (order k)/N

209

400

800 337

261

Rotational speed/(r/min)

Meshing frequency of gear 2/Hz

Parameter

320

1920

1920

320

600

1200

Table 5.13 Gear meshing frequency and theoretical analysis of motor excitation force

404

313

1400

373

2240

2240

373

700 472

365

1600

427

2560

2560

427

800

539

417

1800

480

2880

2880

480

900

607

470

2000

533

3200

3200

533

1000

674

522

312 5 NVH Test and Optimization for New Energy Vehicle Powertrain

3.63

261 3.28

272 10.94

608

600 7.24

320

313

1200 r/min

8.25

704

700 4.44

368

365

1400 r/min

4.28

784

800

4.49

416

417

1600 r/min

8.45

896

900

4.26

464

470

1800 r/min

26.08

1008

1000

11.2

528

522

2000 r/min

Note The two columns of parameters at each speed in the table correspond to the normally engaged gear and shift gear respectively; the vibration is expressed by vibration acceleration amplitude, the same in the rest tables

1.58

1.62

Vibration/(m/s2 )

512

500

209

208

400

400

Calculated frequency/Hz

Analysis frequency/Hz

1000 r/min

800 r/min

Parameter

Table 5.14 Gear meshing frequency at 500 N · m torque

5.4 Practical Case of Vibration and Noise Optimization of Two-Speed … 313

800 r/min

400

400

1.65

Parameter

Calculated frequency/Hz

Analysis frequency/Hz

Vibration/(m/s2 )

1.58

208

209 3.03

496

500 3.23

256

261

1000 r/min

Table 5.15 Gear meshing frequency at 600 N · m torque

10.38

608

600 9.3

320

313

1200 r/min

10.81

688

700 4.54

368

365

1400 r/min

4.54

800

800

5.13

416

417

1600 r/min

8.19

912

900

4.71

480

470

1800 r/min

314 5 NVH Test and Optimization for New Energy Vehicle Powertrain

5.4 Practical Case of Vibration and Noise Optimization of Two-Speed …

315

Table 5.16 Gear meshing frequency at 700 N · m torque Parameter

800 r/min

1000 r/min

1200 r/min

1400 r/min

1600 r/min

Calculated frequency/Hz

400

209

500

261

600

313

700

365

800

417

Analysis frequency/Hz

400

208

512

272

608

320

688

368

800

416

Vibration/(m/s2 ) 1.99

1.8

3.19

3.83

11.16

10.68

9.71

5.68

5.85

5.88

Table 5.17 Gear meshing frequency at 800 N · m torque Parameter

800 r/min

1000 r/min

1200 r/min

1400 r/min

Calculated frequency/Hz

400

209

500

261

600

313

700

365

Analysis frequency/Hz

400

208

512

272

608

320

704

368

Vibration/(m/s2 )

2.14

1.15

3.23

3.67

8.98

11.11

10.34

7.19

Table 5.18 Gear meshing frequency at 900 N · m torque Parameter

800 r/min

Calculated frequency/Hz

400

1000 r/min 209

500

1200 r/min 261

600

313

Analysis frequency/Hz

400

208

512

272

608

320

Vibration/(m/s2 )

2.52

1.73

2.83

3.59

8.95

15.27

261

600

Table 5.19 Gear meshing frequency at 950 N · m torque Parameter

800 r/min

Calculated frequency/Hz

400

1000 r/min 209

500

1200 r/min 313

Analysis frequency/Hz

400

208

496

256

608

320

Vibration/(m/s2 )

2.95

1.7

3.01

3.78

7.89

17.29

Tables 5.28 and 5.28 show the comparison of noise results at each measuring point before and after the motor/transmission wrapping in gear 2 and gear 3. According to the above statistical chart, at 700 N · m–1600 r/min, the noise contribution degree at each noise measuring point of the powertrain is ranked as Gearbox-right > Gearbox-left > Gearbox-up > Motor-rear > Motor-up.

5.4.3.5

Analysis of Noise Composition of Powertrain Unit

1. Analysis of noise composition of powertrain unit when transmission is in gear 2 (1) The noise composition of Gearbox-left at 600 N · m–1800 r/min is shown in Fig. 5.100.

400

400

1.5

Calculated frequency/Hz

Analysis frequency/Hz

Vibration/(m/s2 )

4.66

272

270

800 r/min

Parameter

2.96

496

500 5.88

336

337

1000 r/min

Table 5.20 Gear meshing frequency at 500 N · m torque

11.83

592

600 7.27

400

404

1200 r/min

12.99

688

700 10.01

464

472

1400 r/min

20.05

800

800

6.19

528

539

1600 r/min

14.22

896

900

11.37

592

607

1800 r/min

30.69

1008

1000

16.31

672

674

2000 r/min

316 5 NVH Test and Optimization for New Energy Vehicle Powertrain

5.4 Practical Case of Vibration and Noise Optimization of Two-Speed …

317

Table 5.21 Gear meshing frequency at 700 N · m torque Parameter

800 r/min

1000 r/min

1200 r/min

1400 r/min

1600 r/min

Calculated frequency/Hz

400

270

500

337

600

404

700

472

800

539

Analysis frequency/Hz

400

272

496

336

592

400

688

464

816

544

Vibration/(m/s2 ) 1.57

5.9

2.54

6.25

14.85

7.55

13.61

14.54

22.98

9.04

Table 5.22 Gear meshing frequency at 800 N · m torque Parameter

800 r/min

1000 r/min

1200 r/min

1400 r/min

Calculated frequency/Hz

400

270

500

337

600

404

700

472

Analysis frequency/Hz

400

272

496

336

608

416

704

464

Vibration/(m/s2 )

1.53

7.1

2.54

6.7

15.76

7.53

12.5

13.15

Table 5.23 Gear meshing frequency at 900 N · m torque Parameter

800 r/min

Calculated frequency/Hz

400

1000 r/min 270

500

1200 r/min 337

600

404

Analysis frequency/Hz

400

272

496

336

608

416

Vibration/(m/s2 )

1.63

7.81

3.25

7.8

17.34

7.54

337

600

Table 5.24 Gear meshing frequency at 950 N · m torque Parameter

800 r/min

Calculated frequency/Hz

400

1000 r/min 270

500

1200 r/min 404

Analysis frequency/Hz

400

272

496

336

608

416

Vibration/(m/s2 )

2.08

8.23

3.18

7.95

17.36

7.1

According to the contribution degree of powertrain noise, the main factors causing powertrain noise are as follows: ➀ ➁ ➂ ➃ ➄

Noise of normally engaged gear of transmission 910 Hz; Noise of shift gear in gear 2 of transmission 479 Hz; Noise at 2 times frequency of normally engaged gear of transmission 1803 Hz; Motor stator cog harmonic frequency 2900 Hz; Noise at 5 times frequency of shift gear in gear 2 of transmission 2395 Hz.

(2) The noise composition of Gearbox-left at 700 N · m–1600 r/min is shown in Fig. 5.101.

800 r/min

1.58

4.66

1.62

1.5

Revolving speed

Gear 2

Gear 3

2.96

3.63 5.88

3.28

1000 r/min 11.83

10.94 7.27

7.24

1200 r/min 12.99

8.25 10.01

4.44

1400 r/min 20.05

4.28

6.19

4.49

1600 r/min

Table 5.25 Speed and vibration acceleration amplitude of transmission gear 2 and gear 3 at 500 N · M (m/s2 )

14.22

4.37

4.26

1800 r/min 8.45

30.69

16.31

11.2

2000 r/min 26.08

318 5 NVH Test and Optimization for New Energy Vehicle Powertrain

5.4 Practical Case of Vibration and Noise Optimization of Two-Speed …

319

Fig. 5.67 Vibration acceleration amplitude at different speeds at 500 N · m torque

Fig. 5.68 Vibration results at Gearbox-front

According to the contribution degree of powertrain noise, the main factors causing powertrain noise are as follows: ➀ ➁ ➂ ➃ ➄

Noise of normally engaged gear of transmission 800 Hz; Noise of shift gear in gear 2 of transmission 417 Hz; Noise at 5 times frequency of shift gear in gear 2 of transmission 2085 Hz; Noise at 3 times frequency of normally engaged gear of transmission 2400 Hz; Noise at 3 times frequency of shift gear in gear 2 of transmission 1251 Hz.

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5 NVH Test and Optimization for New Energy Vehicle Powertrain

Fig. 5.69 Vibration results at Gearbox-left

Fig. 5.70 Vibration results at Gearbox-right

(3) The noise composition of Gearbox-left at 800 N m–1400 r/min is shown in Fig. 5.102. According to the contribution degree of powertrain noise, the main factors causing powertrain noise are as follows: ➀ Noise of normally engaged gear of transmission 700 Hz; ➁ Noise of shift gear in gear 2 of transmission 365 Hz; ➂ Noise at 7 times frequency of shift gear in gear 2 of transmission 2555 Hz;

5.4 Practical Case of Vibration and Noise Optimization of Two-Speed …

321

Fig. 5.71 Vibration results at Gearbox-up

Fig. 5.72 Vibration results at Motor-up

➃ Noise at 3 times frequency of normally engaged gear of transmission 2100 Hz; ➄ Noise at 4 times frequency of normally engaged gear of transmission 2800 Hz. 2. Analysis of noise composition of powertrain unit when transmission is in gear 3. (1) The noise composition of Gearbox-left at 600 N · m–1800 r/min is shown in Fig. 5.103.

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5 NVH Test and Optimization for New Energy Vehicle Powertrain

Fig. 5.73 Vibration results at Motor-rear

Fig. 5.74 Vibration results at Gearbox-front

According to the contribution degree of powertrain noise, the main factors causing powertrain noise are as follows: ➀ ➁ ➂ ➃ ➄

Noise of shift gear in gear 3 of transmission 604 Hz; Noise at 2 times frequency of normally engaged gear of transmission 1805 Hz; Noise of normally engaged gear of transmission 900 Hz; Noise at 2 times frequency of shift gear in gear 3 of transmission 1202 Hz; Noise at 4 times frequency of shift gear in gear 3 of transmission 2413 Hz.

5.4 Practical Case of Vibration and Noise Optimization of Two-Speed …

323

Fig. 5.75 Vibration results at Gearbox-up

Fig. 5.76 Vibration results at Gearbox-left

(2) The noise composition of Gearbox-left at 700 N · m–1600 r/min is shown in Fig. 5.104. ➀ Noise of shift gear in gear 3 of transmission 539 Hz; ➁ Noise of normally engaged gear of transmission 800 Hz; ➂ Noise at 3 times frequency of shift gear in gear 3 of transmission 1617 Hz;

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5 NVH Test and Optimization for New Energy Vehicle Powertrain

Fig. 5.77 Vibration results at Gearbox-right

Fig. 5.78 Vibration results at Motor-up

➃ Noise at 5 times frequency of shift gear in gear 3 of transmission 2695 Hz; ➄ Noise at 2 times frequency of shift gear in gear 3 of transmission 1078 Hz. (3) The noise composition of Gearbox-left at 800 N · m–1400 r/min is shown in Fig. 5.105.

5.4 Practical Case of Vibration and Noise Optimization of Two-Speed …

Fig. 5.79 Vibration results at Motor-rear Table 5.26 Test conditions Item

Torque–speed

Power/kW

Condition 1

600 N · m–1800 r/min

113.1

Condition 2

700 N · m–1600 r/min

117.2

Condition 3

800 N · m–1400 r/min

117.2

Fig. 5.80 Noise test results at 600 N · m–1800 r/min

325

326

5 NVH Test and Optimization for New Energy Vehicle Powertrain

Fig. 5.81 Noise test results at 700 N · m–1600 r/min

Fig. 5.82 Noise test results at 800 N · m–1400 r/min

➀ ➁ ➂ ➃ ➄

Noise at 2 times frequency of shift gear in gear 3 of transmission 944 Hz; Noise of normally engaged gear of transmission 700 Hz; Noise of shift gear in gear 3 of transmission 472 Hz; Noise at 4 times frequency of shift gear in gear 3 of transmission 1888 Hz; Motor stator cog harmonic excitation noise 2240 Hz.

5.4 Practical Case of Vibration and Noise Optimization of Two-Speed … Table 5.27 Contribution of noise sources at each measuring point under different driving cycles in gear 2

327

Measuring point

Noise source contribution (RMS value)/dB(A) 600 N · 700 N · 800 N · m–1800 r/min m–1600 r/min m–1400 r/min

Motor-up

86.38

82.15

87.25

Motor-rear

91.15

91.34

90.27

Gearbox-up

87.75

86.94

85.90

Gearbox-left

94.02

90.16

92.61

Gearbox-right 92.04

89.60

91.40

Fig. 5.83 Noise at each measuring point of two gears at 600 N · m–1800 r/min

Fig. 5.84 Noise at each measuring point of two gears at 700 N · m–1600 r/min

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5 NVH Test and Optimization for New Energy Vehicle Powertrain

Fig. 5.85 Noise at each measuring point of two gears at 800 N · m–1400 r/min

Fig. 5.86 Change in noise RMS at Gearbox-up in gear 2 under all conditions

Fig. 5.87 Change in noise RMS at Gearbox-left in gear 2 under all conditions

5.4 Practical Case of Vibration and Noise Optimization of Two-Speed … Fig. 5.88 Change in noise RMS at Gearbox-right in gear 2 under all conditions

Fig. 5.89 Change in noise RMS at Motor-up in gear 2 under all conditions

Fig. 5.90 Change in noise RMS at Motor-rear in gear 2 under all conditions

Fig. 5.91 Change in noise RMS at Gearbox-up in gear 3 under all conditions

329

330 Fig. 5.92 Change in noise RMS at Gearbox-left in gear 3 under all conditions

Fig. 5.93 Change in noise RMS at Gearbox-right in gear 3 under all conditions

Fig. 5.94 Change in noise RMS at Motor-up in gear 3 under all conditions

Fig. 5.95 Change in noise RMS at Motor-rear in gear 3 under all conditions

5 NVH Test and Optimization for New Energy Vehicle Powertrain

5.4 Practical Case of Vibration and Noise Optimization of Two-Speed …

331

Fig. 5.96 Noise before wrapping of motor/transmission in gear 2

Fig. 5.97 Noise before wrapping of motor/transmission in gear 3

3. Analysis conclusion of powertrain noise in gear 2 and gear 3 of the transmission. (1) In gear 2, the noise of the normally engaged gear of the transmission and the noise of the shift gear in gear 2 are the main noise sources, followed by the motor stator cog harmonic excitation noise; (2) In gear 3, the noise of the normally engaged gear of the transmission and Main noise of the shift gear in gear 3 are the main noise sources, followed by the motor stator cog harmonic excitation noise;

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5 NVH Test and Optimization for New Energy Vehicle Powertrain

Fig. 5.98 Noise after wrapping of motor/transmission in gear 2

Fig. 5.99 Noise after wrapping of motor/transmission in gear 3 Table 5.28 Comparison of noise results at each measuring point before and after wrapping the motor/transmission in gear 2 (unit: dB(A)) Measure point and No

RMS value before wrapping

RMS value after wrapping

Sound pressure level difference before and after wrapping

Gearbox-up-2

87.53

85.07

2.46

Gearbox-left-3

88.57

87.81

0.76

Gearbox-right-4

88.97

85.98

2.99

Motor-up-5

84.66

83.28

1.38

Motor-rear-6

89.72

85.01

4.71

5.4 Practical Case of Vibration and Noise Optimization of Two-Speed …

333

Table 5.29 Comparison of noise results at each measuring point before and after wrapping the motor/transmission in gear 3 (unit: dB(A)) Measure point and No

RMS value before wrapping

RMS value after wrapping

Sound pressure level difference before and after wrapping

Gearbox-up-2

92.10

90.38

1.72

Gearbox-left-3

94.64

89.28

5.36

Gearbox-right-4

92.77

91.88

0.89

Motor-up-5

88.84

84.57

4.27

Motor-rear-6

98.24

88.89

9.35

Fig. 5.100 Noise composition of Gearbox-left at 600 N · m–1800 r/min in gear 2

(3) The noise optimization objectives of powertrain in each gear include transmission and motor noise optimization; the low and medium frequency part is mainly transmission noise, and the high frequency part is mainly motor noise. 5.4.3.6

Conclusion

(1) The normally engaged gear of the transmission and the shift gears of gear 2 and gear 3 are the main reason for transmission vibration. At low speed, the vibration acceleration amplitude of the normally engaged gear is low, while at high speed, the vibration acceleration amplitude of the normally engaged gear is high; the vibration acceleration amplitude of the shift gear in gear 3 is higher than that in gear 2, indicating that the vibration problem of the transmission gear 3 is more serious. The above three gears should be taken as the focus in

334

5 NVH Test and Optimization for New Energy Vehicle Powertrain

Fig. 5.101 Noise composition of Gearbox-left at 700 N · m–1600 r/min in gear 2

4 times frequency of Normally engaged 7 times frequency of shift normally engaged gear in gear of transmission gear in gear 2 of gear 2 of transmission transmission 2555Hz 700Hz 2800Hz

Motor switching frequency 4448Hz

Shift gear in gear 2 of transmission 365HZ

3 times frequency of normally engaged gear of transmission 2100 HZ

Amplitude

Sound pressure level/dB(A)

Motor switching frequency 5568Hz

Frequency/HZ

Fig. 5.102 Noise composition of Gearbox-left at 800 N · m–1400 r/min in gear 2

the gear optimization design, especially the normally engaged gear in the high speed range. (2) The overall noise of the transmission is higher than that of the motor, and the noise at the left measuring point of the transmission is higher than that at other measuring points; the noise on the left side of the transmission is mainly caused by the meshing excitation of the shift gear and the normally engaged gear, so it needs to be optimized.

5.4 Practical Case of Vibration and Noise Optimization of Two-Speed …

335

Frequency/HZ

Fig. 5.103 Noise composition of Gearbox-left at 600 N · m–1800 r/min in gear 3

Normally engaged gear of transmission 800Hz

3 times frequency of shift gear in gear 3 of transmission 1617HZ

5 times frequency of shift gear in gear 3 of transmission 2695HZ

Motor stator cog harmonic frequency 2810Hz

Motor switching frequency 5613Hz

Amplitude

level/dB(A)

Sound pressure

Shift gear in gear 3 of transmission 539Hz

2 times frequency of shift gear in gear 3 of transmission 1078Hz

Motor switching frequency 4350Hz

Frequency/HZ

Fig. 5.104 Noise composition of Gearbox-left at 700 N · m–1600 r/min in gear 3

(3) The vibration of the motor is excited by the stator cog and PWM excitation. The vibration amplitude generated by the PWM excitation increases with the speed, the higher the peak, the greater the influence. The optimization of motor shall focus on the stator cog and PWM. (4) The noise generated by the powertrain is divided into two parts: low frequency and high frequency. The low frequency noise is mainly generated by the transmission, and the high frequency noise is mainly generated by the motor, which needs local optimization.

336

5 NVH Test and Optimization for New Energy Vehicle Powertrain

Fig. 5.105 Noise composition of Gearbox-left at 800 N · m–1400 r/min in gear 3

(5) The vibration at Gearbox-front is more obvious than that at other measuring points, so the optimization of the Gearbox-front shall be emphasized in the case optimization.

5.4.4 Optimization Design of Transmission Gear Micro Modification 5.4.4.1

Principle of Gear Micro Modification

During the actual work of the transmission gear powertrain, the gears will inevitably experience load fluctuation, velocity jump, uneven load distribution along the teeth and engaging-in and engaging-out phenomena under the influence of machining error, installation error and deformation under load and heat, which will reduce the transmission precision and carrying capacity, shorten the service life and generate the vibration and noise composed by different vibration modes and frequencies. Although the transmission performance can be improved by improving the machining, manufacturing and assembly accuracy, the gear machining cost will increase significantly, and the practical effect is not always ideal. In the early stage when the gear macroscopic parameters have been developed and designed, it is very effective to solve the vibration and noise generated by the gear transmission system due to manufacturing, assembly and elastic deformation by the gear micro modification, so as to improve the gear transmission performance significantly, enhance the loading performance and reliability, and significantly improve its NVH performance. Therefore, the micro gear modification has been widely studied and applied in various research institutes and automobile companies.

5.4 Practical Case of Vibration and Noise Optimization of Two-Speed …

337

There are a variety of gear modification methods. The commonly used gear modification solutions include (axial) modification along the direction of tooth width and (profile) modification along the direction of tooth profile. The interaction (3D modification) between axial modification and profile modification should be considered comprehensively. 1. Axial modification Axial modification usually includes axial crowning modification, axial helical angle (axial slope) modification and end relief. The proper axial modification can compensate the tooth alignment errors caused by the manufacturing and installation errors and the load deformation in the gear engagement process to a certain extent, so that the load of the gear is reasonably distributed along the tooth width, and the gear transmission performance is effectively improved. (1) Axial crowning modification Crowning modification refers to the machining and grinding of the gear surface with the shape of crowning in the middle along the direction of tooth width and symmetry on both sides, as shown in Fig. 5.106a. In this way, when the gear teeth transmit the load, the tooth surface near the middle part of the direction of the tooth width will contact first, and then extend to the whole tooth surface, so that the load distribution on the tooth surface is more uniform, the transmission is more stable, and the generation of vibration and noise is reduced. The effect of the crowned teeth is shown in Fig. 5.106b–e. Figure (b) shows the crowned teeth modified by the crowning modification; Figure (c) shows the tooth surface contact before loading; Figure (d) shows the load along the tooth width after elastic deformation of the gear teeth under loading, and Figure (e) shows the load curve. It can be seen that the partial load is significantly improved. The design of axial crowning parameters is the key to the crowning modification, which will significantly affect the effect of axial crowning modification. Too large crowning amount will worsen the partial load of gears, aggravate the wear of tooth

Fig. 5.106 Schematic diagram of axial crowning modification and modification effect

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5 NVH Test and Optimization for New Energy Vehicle Powertrain

surface, and shorten the service life; too small crowning amount will not compensate for the tooth alignment error, shift the load distribution on the tooth surface, deteriorate its bearing performance and produce greater vibration noise. Therefore, it is very important to select the proper axial crowning. The crowning amount can be calculated using empirical formula. There are several empirical formulas for calculating the axial crowning amount. (1) The empirical formula proposed by the ISO standard only considers the initial meshing misalignment, and the formula for calculating the axial crowning Cβ is as follows: Cβ ≈ 0.5Fβ xcv

(5.23)

where Fβxcv is the equivalent meshing misalignment of the gear, expressed as the meshing misalignment Fxcv before gear modification. (2) The empirical formula proposed by JMSE in Japan mainly considers the influence of gear accuracy, and the calculation formula of crowning amount is Cβ = 0.25b × 10−3 + 0.5 f g f g = A(0.1b + 10)

(5.24)

where b is tooth width; Fg is the tooth alignment error, which is determined by the gear accuracy class; A is the coefficient determined by the accuracy class. (3) The empirical formula proposed by the British BS company mainly considers the gear contact deformation, and the formula for calculating the crowning amount is Cβ = 0.7 ×

Fm b

(5.25)

where b is tooth width; Fm is the circumferential force uniformly distributed on the gear reference circle. (2) Axial helical angle modification In general, helical gears can be modified along the axial helical angle during the crowning modification to compensate for the change of helical angle under different loads and further reduce the axial partial load. As shown in Fig. 5.107, the helical angle modification is a tiny change to the helical angle according to the meshing of the gear pairs. Figure 5.108 shows the schematic diagram of helical angle modification. Before gear modification, the helical line is line a, and its expanded spiral angle is β. After the helical angle is increased by Δβ, the helical line becomes line b, and its expanded spiral angle is β + Δβ. Thus, the butt meshing of helical gear can be improved, the gear meshing is tangent instead of cutting, and the load distribution is more uniform.

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339

Fig. 5.107 Schematic diagram of axial helical angle modification

Fig. 5.108 Schematic diagram of helical angle modification

A lot of research and practice show that the tooth error will have obvious influence on the vibration and noise generated during the gear transmission. During the process of gear transmission, the tooth shape and pitch errors of a gear caused by manufacturing errors and the load deformation will cause instantaneous impact during gear transmission, resulting in vibration and noise. 2. Profile modification The contact ratio and overlap ratio of the automobile transmission is usually higher than 1, so alternating meshing of single tooth pair and multi-tooth pairs will appear during gear transmission. Through profile modification, the interference caused by the basic pitch deviation on the gear teeth is modified, which can improve the load fluctuation during the alternating meshing of single tooth pair and multi-tooth pairs, so as to reduce the engaging-in and engaging-out impact, enhance the stability of gear transmission, and reduce the generation of vibration and noise. The profile modification method usually includes tip relief, tooth root edge modification, profile crowning modification, and profile pressure angle modification.

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Fig. 5.109 Tip relief

Driven wheel

Drive wheel

Fig. 5.110 Schematic diagram of profile crowning modification

The tip relief is shown in Fig. 5.109. The tip relief part is the dark part of the driven gear tip in the figure. The tip relief can be performed on both the drive wheel and the driven wheel of the gear pair, or only on the drive wheel or the driven wheel. In order to reduce the change of gear shape due to gear contact deformation and improve the gear transmission performance, the profile crowning modification and profile pressure angle modification are used more and more frequently in the gear design in addition to the tip relief and root edge modification, as shown in Fig. 5.110 and Fig. 5.111. The profile crowning modification is mostly selected in aerospace and other large and precision gear transmission fields. Now the profile crowning modification and profile pressure angle modification are also widely used in the automobile industry.

5.4.4.2

Gear Modification Optimization Based on Orthogonal Optimization Method

It can be seen from existing studies that there is no uniform regulation on the determination of gear micro modification parameters, and the empirical formula is quick but has certain limitations, insufficient considerations and cannot be used for effective modification of a specific gear. Moreover, it cannot take the variable driving cycles of

5.4 Practical Case of Vibration and Noise Optimization of Two-Speed …

341

Fig. 5.111 Schematic diagram of profile pressure angle modification

the gear transmission system into account. Therefore, it is necessary to formulate a gear modification solution that fully considers the characteristics of the transmission to be optimized and has good results under different driving cycles. In this study, the orthogonal optimization sorting method is adopted to develop the modification according to the characteristics of the two-speed transmission of battery electric vehicles and its actual operating conditions and can accurately, conveniently and efficiently determine the primary and secondary effect order and influence degree of each factor on the evaluation index, obtain the advantages of the optimal combination and achieve the purpose of multi-objective optimization according to the characteristics of transmission under different driving cycles. Before introducing the gear modification by orthogonal optimization sorting method, it is necessary to understand the influence law of modification parameters on the transfer error and gear surface load. 1. Study on the influence law of modification parameters on the transfer error and gear surface load In this section, four gear micro modification parameters, namely, axial crowning modification amount Cb , axial helical angle modification amount FHβ , profile crowning modification amount Ca and profile pressure angle modification amount FH α , are adjusted. Taking gear 1 as an example, the single factor influence of micro modification parameters on the transfer error and gear surface load under various driving cycles is analyzed. In order to simulate the actual operation of the transmission as much as possible, 20–100% of the maximum torque is applied to the power input, so as to optimize the optimal parameter level by orthogonal optimization. The change levels of profile crowning modification amount Ca are set as 0, 2, 4, 6, 8 μm, and other modification amounts are set to 0. The transfer error and the load per unit length of tooth surface of different profile crowning modification amount under 20–100% torque are recorded and statistically analyzed. The analysis results are shown in Figs. 5.112 and 5.113. It can be seen from Fig. 5.112 that the transfer error is relatively small when the profile crowning modification amount is 2 and 4 μm, and the transfer error keeps increasing with the input torque. It can be seen from Fig. 5.113 that the load per unit length of the tooth surface increases with the profile crowning modification amount on the whole, and also increases with the input

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5 NVH Test and Optimization for New Energy Vehicle Powertrain

torque. Based on Figs. 5.112 and 5.113, the profile crowning modification amount 2 and 4 μm are selected as the horizontal quantities to be selected for orthogonal optimization. The change levels of profile pressure angle modification amount f Hα are set as 0, 2 , 4, 6, 8 μm, and other modification amounts are set to 0. The transfer error and the load per unit length of tooth surface of different profile pressure angle modification amount under 20–100% torque are recorded and statistically analyzed. The analysis results are shown in Figs. 5.114 and 5.115. It can be seen from Fig. 5.114 that the transfer error is relatively small when the profile pressure angle modification amount is 0 and 2 μm, and the transfer error keeps increasing with the input torque. It can be seen from Fig. 5.115 that the load per unit length of the tooth surface increases with the profile pressure angle modification amount, and also increases with the input torque. Based on Figs. 5.114 and 5.115, the profile pressure angle modification amount 0 and 2 μm are selected as the horizontal quantities to be selected for orthogonal optimization. Fig. 5.112 Relationship between profile crowning modification amount and transfer error

Fig. 5.113 Relationship between profile crowning modification amount and load per unit length of tooth surface

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343

Fig. 5.114 Relationship between profile pressure angle modification amount and transfer error

Fig. 5.115 Relationship between profile pressure angle modification amount and load per unit length of tooth surface

2. Gear micro modification based on orthogonal optimization method For some multi-factor, multi-level and multi-index optimization calculation, it takes a lot of manpower and material resources, time and cost to test all combinations. Therefore, in order to achieve the test results while minimizing the number of tests and saving calculation power, it is necessary to use scientific calculation methods. Orthogonal test is a kind of test method to understand the overall situation by conducting the experimental analysis with a small number of targeted test objects. In 1951, Taguchi Genichi, a statistician, designed the orthogonal table, which became an important means of orthogonal test because of its dispersion and symmetrical comparability. Through the study of orthogonal table, the primary and secondary effect order and influence degree of each factor on the evaluation index can be obtained accurately, conveniently and efficiently, so as to get the optimal combination, and provide the direction and basis for the subsequent optimization study. The optimization of gear modification parameters has the characteristics of multi-factor, multi-level and multi-objective, so the orthogonal optimization method can be used to optimize the gear modification parameters.

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Table 5.30 Factor and level setting table (unit: μm) Horizontal

Factor W1

W2

W3

W4

1

2

2

0

0

2

4

4

2

2

The traditional orthogonal test table can only be optimized for a single evaluation index, and various evaluation indexes cannot be considered globally due to the inconsistency of dimension and order of magnitude. Aiming at the above shortcomings, we have improved the traditional orthogonal test method according to the needs of gear modification optimization. Using multi-index orthogonal experiment comprehensive score method (ranking score), four modification parameters, two modification levels and two evaluation indexes of gear 1 are comprehensively analyzed, in order to obtain the influence law of various modification parameters on the transfer error and tooth surface load and obtain the optimal modification parameter combination of the optimization level to be selected, thus providing relevant basis and direction for further gear modification. In the orthogonal test, the variables that affect the test evaluation indexes are called factors, and the state of the factors is called level. A certain factor that needs several states in the test is called several levels of factor. The design factors of this orthogonal test are four modification parameters, namely, profile crowning modification amount W1 , axial crowning modification amount W2 , profile pressure angle modification amount W3 and axial helical angle modification amount W4 . The horizontal amount of each factor is obtained based on the aforementioned single-factor influence analysis. The factors and levels of this orthogonal test are shown in Table 5.30. The evaluation indexes comprehensively consider the transfer error and tooth surface load, and the comprehensive scoring method is used to carry out the optimization test. In order to make the gear modification solution more consistent with the actual operation of the transmission, it is necessary to set different driving cycles for the test. However, in fact, the modification amount of a gear pair can only realize the optimization of a specific driving cycle, but cannot achieve the ideal optimization effect for all driving cycles. Therefore, when setting the driving cycles based on the test, focus shall be placed on the driving cycles concerned by gear modification based on the actual situation. In order to take care of more driving cycles and focus on modification, the driving cycle weight setting is introduced. As shown in Fig. 5.116, considering the high efficiency area of the battery electric vehicle motor, the common driving cycles of transmission and the characteristics that gear whine occurs more at low torque, the weight of the driving cycles on which the test is based is set, as shown in Table 5.31. The orthogonal test table summarizes the test information by respective symbols, such as L9 (34 ), where, “L” indicates orthogonal table, “9” means that 9 tests are required, “3” means that each factor includes three levels, and “4” means that the test

5.4 Practical Case of Vibration and Noise Optimization of Two-Speed …

345

Fig. 5.116 Table of efficiency interval of two-speed transmission motor of battery electric vehicle

Table 5.31 Weight setting for test conditions Condition

20%T

40%T

60%T

80%T

100%T

Weight/(%)

15

25

30

20

10

has four factors. If all tests are carried out, 34 = 81 tests would be performed; when using the orthogonal test method, only 9 tests are required, which greatly improves the test efficiency. In this orthogonal test, a L8 (27 ) orthogonal table is constructed. Taking the gear pair modification of gear 1 as an example, the driving cycles of the transmission set in the multi-body dynamics simulation software are 20, 40, 60, 80 and 100% of the maximum input torque, the speed of 5000 r/min, and the upper and lower evaluation limits of tooth surface modification of 10 and 90% when the transmission is in gear 1. The obtained results are processed under the driving cycle weights shown in Table 5.31, and the final calculation results are sorted and recorded.

5.4.5 Transmission Vibration and Noise Simulation and Test Analysis 5.4.5.1

Analysis of Influence of Gear Modification Solution on Transmission Vibration

The transmission gear powertrain will produce certain excitation to the gear, shaft and bearing on it under the joint influence of the gear transfer error and dynamic meshing stiffness. The excitation will be transmitted to the case connected with the bearing, produce corresponding vibration, and radiate noise to the outside world. Therefore, on the basis of the full study of gear transfer error and load distribution, sufficient attention shall also be paid to the specific performance of transmission vibration

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5 NVH Test and Optimization for New Energy Vehicle Powertrain

and noise, in order to more intuitively obtain the influence of gear modification on vibration and noise, and evaluate the actual effect of gear modification. 1. Vibration response analysis of transmission case nodes The transfer error obtained from the above analysis is applied to the current power flow, and the dynamic parameters are set. The vibration response of the six finite element bearing nodes of the transmission case as shown in Fig. 5.117 is analyzed and calculated based on the input shaft speed. Figure 5.118 shows the vibration response at different nodes of the case before and after gear modification, It can be seen that through the gear micro modification, the vibration acceleration at different bearing nodes of the transmission case is significantly reduced at most rotational speeds. The vibration acceleration at the case node 1 of the bearing behind the input shaft decreases greatly in the y direction, decreases by about 60% in most speed ranges, decreases most obviously at the input shaft speed of about 7000 r/min; the vibration acceleration decreases by about 50% in most speed ranges in the x direction. The vibration acceleration at other case nodes also decreases to different degrees, verifying the improvement effect of the gear modification solution on the transmission vibration. 2. Vibration response analysis of transmission case surface By analyzing the vibration response of the case surface before and after gear modification, the gear modification effect can be evaluated more intuitively and clearly. In addition, the finite element model of the case is subject to forced vibration to obtain its vibration response effect, which is used as the boundary condition of the radiated noise simulation and the relevant basis of subsequent acoustic simulation. Meanwhile, the vibration at different positions on the transmission case surface has some reference value for the optimization of the case structure. Node 2

Fig. 5.117 Schematic diagram of finite element nodes of transmission case Node 1

Node 3

Node 5

Node 4 Node 6

x direction before modification y direction before modification z direction before modification x direction after modification y direction after modification z direction after modification

Vibration acceleration /(m/s²)

Vibration acceleration /(m/s²)

5.4 Practical Case of Vibration and Noise Optimization of Two-Speed …

Rotational speed /(r/min)

Vibration acceleration /(m/s²)

Vibration acceleration /(m/s²)

(b) Vibration response at case node 2 before and after gear modification

Rotational speed /(r/min)

(e) Vibration response at case node 5 before and after gear modification

Fig. 5.118 Vibration response at each node

(d) Vibration response at case node 4 before and after gear modification

Vibration acceleration /(m/s²)

Vibration acceleration /(m/s²)

Rotational speed /(r/min)

x direction before modification y direction before modification z direction before modification x direction after modification y direction after modification z direction after modification

Rotational speed /(r/min)

(c) Vibration response at case node 3 before and after gear modification x direction before modification y direction before modification z direction before modification x direction after modification y direction after modification z direction after modification

x direction before modification y direction before modification z direction before modification x direction after modification y direction after modification z direction after modification

Rotational speed /(r/min)

(a) Vibration response at case node 1 before and after gear modification x direction before modification y direction before modification z direction before modification x direction after modification y direction after modification z direction after modification

347

x direction before modification y direction before modification z direction before modification x direction after modification y direction after modification z direction after modification

Rotational speed /(r/min) (f) Vibration response at case node 6 before and after gear modification

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5 NVH Test and Optimization for New Energy Vehicle Powertrain

Taking the excitation of two bearings at the front and rear of the input shaft of transmission gear powertrain, two bearings at the front and rear of the intermediate shaft and two bearings at the front and rear of the differential as input, the vibration response of the transmission case surface is analyzed. The transmission case material properties are defined in the finite element preprocessing software, and 6-DOF constraints are added to the connection between the transmission and the motor and to the suspension point of the transmission, as shown in Fig. 5.119. The processed model is imported into the acoustic simulation software, and the excitation forces in x, y and z directions at the bearing node output from the multi-body dynamics software are loaded onto the Spider central node of the bearing block, as shown in Fig. 5.120. After the load is applied, the transmission case will undergo forced vibration. The output excitation at meshing frequency of the transmission gear is an important excitation source to produce vibration. Meanwhile, if the gear meshing frequency is close to the natural frequency of the transmission case, resonance phenomenon will occur, causing severe resonance in some parts of the transmission case, and producing large noise. Therefore, it is necessary to analyze the vibration acceleration of the case surface under the meshing frequency of the transmission. The meshing frequency f of the transmission gear can be solved as follows f =n×z

(5.26)

where f is the gear meshing frequency; n is the speed of the transmission input shaft; z is the meshing order of the gear pair.

Fig. 5.119 Case finite element model

5.4 Practical Case of Vibration and Noise Optimization of Two-Speed …

349

Fig. 5.120 Bearing block Spider unit

The meshing order z is defined as the number of teeth meshed in each revolution of the transmission input shaft. Figure 5.121 shows the schematic diagram of transmission drive route. In the figure, n1 and n2 represent the rotational speed of the input shaft and the intermediate shaft, respectively; z1 and z2 represent the number of teeth of the drive and driven gears of a gear pair in gear 1, respectively; z3 and z4 represent the number of teeth of the drive and driven gears of a gear pair in gear 2, respectively; z5 and z6 represent the number of teeth of the drive and driven gears of the final reduction drive pair, respectively. When the transmission is in gear 1, the meshing frequency of the gear in gear 1 is: f1 = n × z1

(5.27)

Gear meshing frequency of final reduction drive: f2 = n2 × z5 = n1

z1 × z5 z2

(5.28)

When the transmission is in gear 2, the meshing frequency of the gear in gear 2 is: f3 = n1 × z3

(5.29)

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5 NVH Test and Optimization for New Energy Vehicle Powertrain

Drive motor

Load

Load

Fig. 5.121 Schematic diagram of transmission drive route

Gear meshing frequency of final reduction drive: f4 = n2 × z5 = n1

z3 × z5 z4

(5.30)

Figure 5.122 shows the vibration acceleration of the transmission case surface at meshing frequency before gear modification. Figure 5.123 shows the vibration acceleration of the transmission case surface at the gear meshing frequency after gear modification. By comparison, it can be seen that the vibration acceleration at different positions on the transmission case surface decreases to different degrees through gear modification, The modification solution can reduce the transmission vibration effect. The deep red area in the figure is the weak vibration area of the transmission case. The vibration of the transmission can be improved by reinforcing these parts in the later optimization.

(a) 583Hz meshing frequency of gear 1

(b) 1583Hz meshing frequency of gear 1

Fig. 5.122 Vibration acceleration of transmission case surface at the gear meshing frequency before gear modification

5.4 Practical Case of Vibration and Noise Optimization of Two-Speed …

(a) 583Hz meshing frequency of gear 1

351

(b) 1583Hz meshing frequency of gear 1

Fig. 5.123 Vibration acceleration of transmission case surface at the gear meshing frequency after gear modification

5.4.5.2

Analysis of Influence of Gear Modification Solution on Transmission Noise

In order to further study the improvement of the gear modification solution on transmission noise, we use the acoustic simulation software to establish relevant simulation models and conduct corresponding analysis. The research route of acoustic simulation calculation is as follows: (1) The case finite element mesh and related vibration response data are imported into the acoustic simulation software. (2) Repair the finite element mesh of the case, and fill in the bearing holes and other positions to form the sealing surface meshes, as shown in Fig. 5.124. (3) In the simulation calculation of the finite element model, it is generally believed that there are 6 mesh elements in the shortest wavelength of the air fluid, and the mesh element length L shall satisfy: L≤

c 6 f max

(5.30)

where c is the speed of sound propagation in air medium; f max is the maximum calculated frequency.

Fig. 5.124 Transmission case sealing surface meshes

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5 NVH Test and Optimization for New Energy Vehicle Powertrain

If the speed of sound propagation in air is defined as 340 m/s and the maximum frequency is 3000 Hz, the length of the mesh element shall not be greater than 0.0189 m. Considering the calculation workload and accuracy requirements, the length of the mesh element is defined as 10 mm. Build the convex envelope meshes, as shown in Fig. 5.125, and build the acoustic meshes, as shown in Fig. 5.126. (4) The fluid properties are set, and the sound velocity is defined as 340 m/s, the air density as 1.225 kg/m3 , and the reference sound pressure as 2 × 10–5 Pa. (5) To observe the sound pressure response at different field points, according to the noise test specification in the Technical Specification for Reduction Gearbox of Battery Electric Passenger Cars (QC/T 1022–2015), a cubic sound field is established and the front, rear, up, down, left and right measuring points are set at 1 m away from the case for simulation analysis. Figure 5.127 shows the positions of the measuring points. (6) The structured mesh and acoustic mesh of the transmission case are defined by data mapping to complete the data transfer. (7) The acoustic response is solved. Figure 5.128 is the cloud diagram of the radiated noise on the case surface at 1500 Hz. The noise data of 6 measuring points are

Fig. 5.125 Convex envelope mesh

Fig. 5.126 Acoustic mesh

5.4 Practical Case of Vibration and Noise Optimization of Two-Speed … Fig. 5.127 Location diagram of noise measuring points

353

Up measuring point

Rear measuring point Right measuring point

Left measuring point Front measuring point Down measuring point

calculated to obtain the frequency response curves of the transmission case radiated noise under rated conditions of gear 1 and 2 before and after gear modification, as shown in Figs. 5.129 and 5.130. The noise requirement of the battery electric vehicle transmission in the automobile industry standard QC/T 1022–2015 Technical Specification for Reduction Gearbox of Battery Electric Passenger Cars is not more than 83 dB. Through calculation, the noise at the six measuring points all meets the requirements, and the radiated noise of the transmission at each measuring point is significantly reduced through gear modification.

Fig. 5.128 Cloud diagram of radiated noise on case surface

5 NVH Test and Optimization for New Energy Vehicle Powertrain

Up measuring point Down measuring point Front measuring point Rear measuring point Left measuring point Right measuring point

Sound pressure level/dB(A)

Sound pressure level/dB(A)

354

Frequency/Hz

Up measuring point Down measuring point Front measuring point Rear measuring point Left measuring point Right measuring point

Frequency/Hz

(a) Sound pressure frequency response curve of gear 1 at each measuring point before gear modification

(b) Sound pressure frequency response curve of gear 1 at each measuring point after gear modification

Up measuring point Down measuring point Front measuring point Rear measuring point Left measuring point Right measuring point Frequency/Hz (a) Sound pressure frequency response curve of gear 2 at each measuring point before gear

Sound pressure level/dB(A)

Sound pressure level/dB(A)

Fig. 5.129 Frequency response curve of transmission case radiated noise under rated conditions of gear 1 before and after gear modification

Up measuring point Down measuring point Front measuring point Rear measuring point Left measuring point Right measuring point Frequency/Hz (b) Sound pressure frequency response curve of gear 2 at each measuring point after gear

Fig. 5.130 Frequency response curve of transmission case radiated noise under rated conditions of gear 2 before and after gear modification

Figures 5.131 and 5.132 show the statistical results of the root mean square (RMS) of sound pressure level of the noise before and after gear modification. After gear modification, when the transmission is in gear 1, the sound pressure level at the six measuring points decreases by 3.04 dB on average, and the maximum decrease is 3.7 dB at the front measuring point. After gear modification, when the transmission is in gear 2, the sound pressure level at the six measuring points decreases by 2.64 dB on average, and the maximum decrease is 3.34 dB at the right measuring point. This further shows that gear modification can improve the transmission vibration and noise.

5.4 Practical Case of Vibration and Noise Optimization of Two-Speed …

355

Sound pressure level/dB

Before modification After modification

Up

Down

Front

Back

Left

Right

Measuring point position Fig. 5.131 Noise change of gear 1 before and after gear modification

Before modification After modification

Sound pressure level/dB

Fig. 5.132 Noise change of gear 2 before and after gear modification

Up

Down

Front

Back

Left

Right

Measuring point position

5.4.5.3

Analysis of Transmission Bench Test

According to the relevant test standards, a bench vibration test is carried out for a two-speed automatic transmission, and the driving cycles are determined as multiple driving cycles of the transmission. The vibration acceleration at the center of the transmission rear case input shaft is measured below. The frequency response

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5 NVH Test and Optimization for New Energy Vehicle Powertrain

curve of vibration acceleration at this point is obtained through subsequent analysis and compared with the simulation results to prepare for the optimization of the transmission NVH performance. 1. Test equipment The data acquisition front end and test software LMS Test.Lab of Belgium LMS company are used for vibration test. The data acquisition front end and the vibration signal acquisition process interface are shown in Figs. 5.133 and 5.134. The B&W three-way acceleration sensor is used as the vibration sensor, as shown in Fig. 5.135. Fig. 5.133 LMS data acquisition front end

Fig. 5.134 Signal acquisition process interface

Fig. 5.135 Three-way acceleration sensor

5.4 Practical Case of Vibration and Noise Optimization of Two-Speed …

Loading motor 1

Drive motor

1:4 change-o ver speed increase box

Torque sensor

Torque sensor

357

Loading motor 2

Two-speed automatic transmissi on

Torque sensor

Fig. 5.136 Schematic diagram of transmission bench vibration test

2. Bench arrangement The transmission bench vibration test is carried out on the powertrain comprehensive performance test bench that consists of the drive motor providing speed for the transmission, the loading motor providing torque for the transmission, the transmission under test and the speed increase box. The schematic diagram of the transmission bench vibration test is shown in Fig. 5.136. 3. Arrangement of vibration measuring points in bench test The position of measuring points and reference coordinate system on the twospeed automatic transmission test bench of the electric vehicle are shown in Fig. 5.137. A total of three vibration acceleration sensors are arranged in the transmission bench test, located in the center of the input shaft rear case bearing block, the center of the output shaft rear case bearing block, and the left end of the differential rear case bearing block, respectively, to measure the vibration response of the three bearing blocks at the rear case of the transmission respectively. Tables 5.32, 5.33 and 5.34 show the test results of the bench vibration acceleration at measuring points 1, 3 and 5 respectively. By comparing the vibration acceleration at the transmission case measuring points before and after gear modification, it can be seen that the vibration acceleration under various driving cycles significantly decreases after gear modification optimization, indicating that the gear modification solution has a significant effect on reducing the transmission vibration. By comparing the simulation and test results, it can be seen that the vibration acceleration has the same change trend. The simulation results of gear 1 are slightly smaller than the test results, and the simulation results of gear 2 are of good agreement.

5.4.5.4

Brief Summary

Based on the modification solution determined above, the vibration noise of the transmission gear before and after modification is simulated, and the transmission assembled after gear optimization is used for comparative analysis and verification.

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5 NVH Test and Optimization for New Energy Vehicle Powertrain

Measuring point 1

Measuring point 5 Measuring point 3

Fig. 5.137 Transmission measuring point position and reference coordinate system

The vibration response at the case bearing node and the vibration acceleration cloud diagram of the case surface under the meshing frequency are simulated and analyzed. The results show that the vibration acceleration at each bearing node decreases significantly at most speeds after gear modification, and the vibration acceleration of case surface decreases to different degrees at different positions, which fully illustrates the improvement effect of gear modification solution on transmission vibration. In the later stage, the weak case vibration area can be optimized according to the cloud diagram of case surface vibration acceleration. The acoustic simulation software is used to establish an acoustic simulation model of transmission case, calculate the radiated noise and further improve the transmission noise by gear modification solution. From the comparison of the sound pressure frequency response curve and root mean square value of sound pressure level at each measuring point before and after gear modification, it can be seen that the noise at each measuring point has been reduced to different degrees through gear modification, which fully illustrates the improvement effect of gear modification solution on transmission noise. The vibration acceleration at each measuring point of the modified gear is measured on the test bench, and is consistent with the simulation value. By comparing the vibration acceleration of transmission at different measuring points before and after gear modification, it can be seen that the gear modification solution can significantly improve the transmission vibration.

2.04 2.16 3.22 3.71

4.13

4.49

5000 r/min 150 N · m

5000 r/min 175 N · m

4000 r/min 84 N · m 3.76

4000 r/min 98 N · m 4.12

5000 r/min 84 N · m 5.95

5000 r/min 98 N · m 6.89

Gear 2

2.57

2.29

4000 r/min 175 N · m 2.36

1.35

1.33

2.21

4000 r/min 150 N · m

After modification in x (m/s2 )

Gear 1

Before modification in x (m/s2 )

Condition

Gear

3.51

3.18

2.24

2.13

3.12

2.93

2.12

1.86

Before modification in y (m/s2 )

Table 5.32 Vibration acceleration at measuring point 1 of transmission case

1.87

1.71

1.34

1.21

1.55

1.60

1.19

1.05

After modification in y (m/s2 )

3.26

3.16

1.33

1.26

1.74

1.67

1.57

1.24

Before modification in z (m/s2 )

1.88

1.74

0.76

0.70

0.96

0.95

0.75

0.64

After modification in z (m/s2 )

5.4 Practical Case of Vibration and Noise Optimization of Two-Speed … 359

2.31 2.44 4.29 5.00

5.95

6.29

5000 r/min 150 N · m

5000 r/min 175 N · m

4000 r/min 84 N · m 4.33

4000 r/min 98 N · m 4.58

5000 r/min 84 N · m 8.95

5000 r/min 98 N · m 9.71

Gear 2

3.17

3.51

4000 r/min 175 N · m 3.05

1.83

1.62

3.07

4000 r/min 150 N · m

After modification in x (m/s2 )

Gear 1

Before modification in x (m/s2 )

Condition

Gear

11.45

10.61

4.81

4.53

9.67

8.17

4.85

4.43

Before modification in y (m/s2 )

Table 5.33 Vibration acceleration at measuring point 3 of transmission case

6.65

6.30

2.69

2.55

4.99

4.49

2.34

2.11

After modification in y (m/s2 )

9.61

7.32

3.51

3.29

5.25

4.93

2.95

2.84

Before modification in z (m/s2 )

5.20

3.91

1.79

1.70

2.65

2.57

1.58

1.46

After modification in z (m/s2 )

360 5 NVH Test and Optimization for New Energy Vehicle Powertrain

1.50 1.52 1.78 1.76

2.45

2.51

5000 r/min 150 N · m

5000 r/min 175 N · m

4000 r/min 84 N · m 2.75

4000 r/min 98 N · m 2.81

5000 r/min 84 N · m 3.39

5000 r/min 98 N · m 3.54

Gear 2

1.37

1.71

4000 r/min 175 N · m 1.34

0.86

0.80

1.63

4000 r/min 150 N · m

After modification in x (m/s2 )

Gear 1

Before modification in x (m/s2 )

Condition

Gear

3.45

3.31

2.45

2.31

3.17

3.05

2.43

2.21

Before modification in y (m/s2 )

Table 5.34 Vibration acceleration at measuring point 5 of transmission case

1.81

1.74

1.33

1.25

1.63

1.60

1.26

1.15

After modification in y (m/s2 )

5.70

5.57

3.46

3.29

4.17

4.08

2.95

2.81

Before modification in z (m/s2 )

2.92

2.8

1.88

1.77

2.16

2.12

1.57

1.53

After modification in z (m/s2 )

5.4 Practical Case of Vibration and Noise Optimization of Two-Speed … 361

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5.4.6 Prediction and Optimization of Transmission Case Radiated Noise Nowadays, with the rapid development of computer technology, the acoustic boundary element method is relatively mature and widely applied. Its related principle has been introduced in the preceding paragraphs. In this section, the bearing excitation under the condition of 5000 r/min and 175 N · m in gear 1 is connected to the bearing center point of the finite element model, the vibration acceleration of the case is calculated, and the calculation results are used as the boundary conditions for the next step of solving the radiated noise. Then, after the transmission radiated noise calculation, this section calculates the acoustic transfer vector and modal acoustic contribution of the transmission case, uses the calculation results as the basis for the next step of panel partition. Through the calculation of the acoustic contribution of the panel, accurately locate the specific parts with large acoustic contribution (which need noise reduction and reinforcement), formulate the optimization solution, and illustrate the improvement effect of the improved case on the vibration and noise characteristics of the transmission.

5.4.6.1

Simulation Analysis of Forced Vibration of Transmission Case

Before the acoustic simulation of the two-speed mechanical automatic transmission, the finite element model established in the Hypermesh finite element software should be imported into the LMS Virtual.lab to obtain the vibration acceleration cloud diagram of the transmission case at each frequency, and the calculation results should be substituted into the next acoustic calculation to solve the radiated noise. The LMS Virtual.Lab is converted to the Acoustic Harmonic BEM module, where constraints are imposed on the case finite element model. According to the actual working state of the transmission, the fixed connection of the case is fully constrained, as shown in Fig. 5.138. The MeshCoarsening module of Structures is used for mesh coarsening, and then the Skin Mesher is used to extract the structural element surface meshes. There are 48,339 surface mesh nodes, 96,818 elements, and the element type is TRIA3. The beam units are set at the 6 bearings of the transmission case to transmit the excitation. As shown in Fig. 5.139, the central node of the BEAM units is selected as the application point of bearing force, and the vibration signals in X, Y and Z directions at the six bearings calculated in the multi-body dynamics simulation software are loaded to the central node of the bearing in the form of amplitude and phase. The bearing excitation condition is gear 1 condition, with the motor input speed of 5000 r/min, and the input torque of 175 N · m. Taking the input shaft as an example, Figs. 5.140 and 5.141 show the interface of loading the left bearing excitation in the frequency domain to the corresponding position. After connecting the bearing forces in three directions at each bearing block with the point of action successfully, analyze the forced vibration of the transmission

5.4 Practical Case of Vibration and Noise Optimization of Two-Speed …

363

Fig. 5.138 Full degree of freedom constraint model of case

Fig. 5.139 Beam element at the differential bearing block

case, set the analysis frequency to 100–4000 Hz and solve the cloud diagram of the vibration acceleration of the transmission case surface under the meshing frequency of the gear and its doubling frequency. The gear meshing frequency is the product of gear speed and number of teeth. In gear 1, the gear meshing frequency is shown in Eqs. (5.32) and (5.33). In the case of gear 1, the meshing frequency of the gear is f 1 = n 1 × z 1 /60

(5.32)

In the case of gear 1, the gear meshing frequency of the final reduction drive is f2 = n2 × z3 = n1

z1 × z3 z2

(5.33)

where n1 and n2 are the input shaft speed and output shaft speed of gear 1, respectively; z1 , z2 and z3 are the number of teeth of the drive gear in gear 1, the number of teeth

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Fig. 5.140 Y-direction vibration response signal interface

Fig. 5.141 Bearing excitation and node connection interface

5.4 Practical Case of Vibration and Noise Optimization of Two-Speed …

365

Table 5.35 Gear meshing frequency and its doubling frequency within 4000 Hz in gear 1 Doubling frequency

First harmonic generation of final reduction drive in gear 1

Frequency/Hz 583

Second harmonic generation of final reduction drive in gear 1

First harmonic generation of gear in gear 1

Third harmonic generation of final reduction drive in gear 1

Second harmonic generation of gear in gear 1

1166

1583

1749

3166

(a) Cloud diagram of case vibration response at 583Hz

(b) Cloud diagram of case vibration response at 1583Hz

Fig. 5.142 Cloud diagram of case response at meshing frequency

of the driven gear in gear 1, and the number of teeth of the drive gear of the final reduction drive. It is calculated that the gear meshing frequency in gear 1 is 1583 Hz and the meshing frequency of the normally engaged gear of the final reduction drive is 583 Hz. As shown in Table 5.35, the gear meshing frequency and its doubling frequency in gear 1 within 4000 Hz under the driving cycle of 175 N · M and 5000 r/min of the gear 1 are focused in the calculation process. The vibration response of the transmission case is solved to prepare for subsequent noise prediction. The case surface vibration under the gear meshing frequency in gear 1 is shown in Fig. 5.142.

5.4.6.2

Calculation of Transmission Case Radiated Noise and Acoustic Transfer Vector

The study of transmission case radiated noise includes establishment of acoustic boundary element model and rectangular sound field, judgment on whether the model is established and calculated reasonable, and analysis of the radiated noise and acoustic transfer vector. 1. Establishment of acoustic boundary element model

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Before calculating the radiated noise of the two-speed automatic transmission, it is necessary to apply dynamic frequency domain force to the bearing of the fully constrained model of the case to solve the vibration acceleration; and to build an acoustic boundary element model. Assuming that there are 6 mesh elements within the minimum wavelength, the sound propagation speed in the air is set as c, and the maximum calculated frequency in the calculation is f max , then the mesh element length L shall satisfy: L≤

c 6 f max

(5.34)

The speed of sound in the air is 340 m/s, and the maximum calculated frequency is 4000 Hz. The maximum length of the mesh element calculated from Eq. (5.34) is 9.838 mm, Meanwhile, considering the calculation time and the mesh quality of the boundary element mesh, the mesh element size is set as 8.095 mm, and the final acoustic boundary element mesh is shown in Fig. 5.143. Define the fluid material and properties, and assign properties to the material. The reference sound pressure is set to 2 × 10–5 Pa. 2. Establishment of rectangular sound field model In order to consider the radiated noise of the transmission from all directions, the sound field model is a rectangular sound field model 1 m away from the center of the model, in which the front field point is right ahead and at the same height with the center of the case. By using the Spherical Field Point Mesh function of Virtual.Lab, the center coordinates of the model are found to be (− 21.727, 108.995, 86.781), and then the sound field coordinates are calculated, as shown in Fig. 5.144. The position of the field point simulates the position of the acoustic sensor. Here, the sound pressure A weighted method is used to express the response of the human ear to the sound. Figure 5.145 shows the established sound field model. 3. Data mapping

Fig. 5.143 Acoustic boundary element mesh

5.4 Practical Case of Vibration and Noise Optimization of Two-Speed …

367

Fig. 5.144 Rectangular sound field coordinates

Rear field point

Up field point

Right field point

Left field point

Down field point

Front field point

Fig. 5.145 Sound field model

Data mapping is a lateral reflection of the rationality of the previous model establishment and calculation and is a key point in solving the sound field, which mainly transfers the information from the structured mesh to the acoustic mesh. Based on the experience, at least four active nodes shall be selected in this process, as shown in Fig. 5.146. Here, the number of active nodes selected is 8, and the corresponding maximum distance is 26.906 mm. The total number of nodes in the acoustic model is 10598, which is consistent with the total number of nodes involved in the mapping process. Therefore, all nodes in the sound field model are involved in the mapping. Figure 5.147 shows the vibration acceleration mapping cloud diagram at the meshing frequency. Compared with the surface vibration response on the case structured mesh, the maximum value of the vibration acceleration mapped to the case

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5 NVH Test and Optimization for New Energy Vehicle Powertrain

Fig. 5.146 Mapping parameter selection

acoustic boundary element mesh is slightly reduced. For example, when the vibration response on the structured mesh is mapped to the acoustic boundary element mesh model at 583 Hz, the maximum vibration acceleration on the case surface decreases from 0.743 to 0.684 m/s2 . At 1583 Hz, the maximum vibration acceleration of the case surface decreases from 5.73 to 5.63 m/s2 . 4. Radiated noise analysis and field point acoustic results

(a) Mapping cloud diagram of vibration acceleration at 583Hz

(b) Mapping cloud diagram of vibration acceleration at 1583Hz

Fig. 5.147 Mapping cloud diagram of vibration acceleration at meshing frequency

5.4 Practical Case of Vibration and Noise Optimization of Two-Speed …

(a) Sound pressure level cloud diagram of sound field at 583Hz

369

(b) Sound pressure level cloud diagram of sound field at 1583Hz

Fig. 5.148 Sound pressure level cloud diagram at meshing frequency

Figure 5.148 shows the sound pressure level cloud diagram of the sound field at the gear meshing frequency. The sound pressure level (SPL) cloud diagram of gear meshing frequency and its second harmonic generation and third harmonic generation are solved. In the cloud diagram results, the areas with large SPL are mostly distributed near the six field points. SPL at the central node of the six surfaces of the sound field is extracted and the mean SPL at each field point is calculated, as shown in Fig. 5.149. As can be seen from the figure, the mean SPL is largest at the front field point at the meshing frequency, so the front field point is taken as the target field point for radiated noise optimization. 5. Analysis of acoustic transfer vector The surface of the sound source object is divided into several units. Under the condition of small external disturbance, the sound pressure at a certain position in the sound field has a primary relationship with the vibration velocity on the normal line of the sound source object. In this way, the sound pressure at any position r in the sound field under frequency ω is p(r, ω) = {AT V (r, ω)T }{vn (ω)}

(5.35)

where {ATV(r, ω)} is acoustic transfer vector; {vn (ω)} is the vibration velocity in the normal line of the structure surface. After calculating the radiated noise of the transmission, the cloud diagram of the corresponding acoustic transfer vector at the front field point of the transmission at the gear meshing frequency of 1583 Hz in gear 1 can be obtained, as shown in Fig. 5.150. It can be seen that the acoustic transfer vector of the rear case of the transmission is significantly larger than that of the front case under the load condition of gear 1. Therefore, the rear case of the transmission is initially taken as the target area of noise reduction optimization for the front field point of the transmission.

5 NVH Test and Optimization for New Energy Vehicle Powertrain

Mean SPL at field point/dB

370

Front field Rear field point point

Left field point

Right field point

Up field point

Down field point

Field point position Fig. 5.149 Mean SPL at each field point position

(a) Transmission front case

(b) Transmission rear case

Fig. 5.150 Cloud diagram of acoustic transfer vector corresponding to the front field point at 1583 Hz

5.4 Practical Case of Vibration and Noise Optimization of Two-Speed …

5.4.6.3

371

Simulation Analysis of Acoustic Contribution

1. Modal acoustic contribution The object has multi-order modes, and the displacement response of the system in the frequency domain can be obtained by linear superposition of the modal shapes as. {x(ω)} =

n ∑

q j (ω){ϕ} j

(5.36)

j=1

where j is the modal order; n is the total modal order; {ϕ} j is the j-th modal shape; {ϕ}T { f (ω)}

j is the contribution degree of the modal in the displacement q j (ω) = a j (iω−λ j) response calculation, where λj is the eigenvalue, { f (ω)} is the load vector, i is an imaginary unit, and aj is a constant related to the characteristics of the multi-DOF system. The displacement response {x(ω)} of the system in the frequency domain is projected to the normal direction of the structure surface and derivative, and the vibration velocity in the normal direction of the structure can be obtained as

{vn (ω)} = i ω

n ∑

Q j (ω){ϕ}n j

(5.37)

j=1

where {ϕ}n j is the component of each mode shape in the normal direction of the structure surface; Qj (ω) is the modal participation factor of the j-th modal; i is an imaginary unit; N is the modal order involved in the calculation. The sound pressure generated by the j-th modal is denoted by psj (r, ω), and the sound pressure at a certain position in the sound field is p(r, ω) = {AT V (r, ω)}T i ω

n ∑

Q j (ω){ϕ}n j

j=1

=

n ∑

i ωQ j (ω){AT V (r, ω)}T {ϕ}n j

j=1

=

N ∑

ps j (r, ω)

(5.38)

j=1

Each order of modal contributes to the sound pressure at a certain position in the sound field, and the sum of the contributions is the total sound pressure at that point. Assuming that the modal order is j, its acoustic contribution is expressed as

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5 NVH Test and Optimization for New Energy Vehicle Powertrain

Ds j (r, ω) =

| | | ps j (r, ω)| cos(θ p − θ pj ) | p(r, ω)|

(5.39)

where θ p and θ pj are the phases of | p(r, ω)| and ps j (r, ω), respectively. 2. Calculation of modal acoustic contribution of transmission case After the calculation of the acoustic transfer vector of the transmission case, the modal acoustic contribution of the transmission case is calculated, and then the effective modal is determined by the size of the contribution. The area with large normal vibration velocity of the transmission case is determined by the effective modal shape. The acoustic contribution is vector and affected by phase. Some acoustic contributions are positive and some are negative. At the gear meshing frequency 1583 Hz in gear 1, the modal acoustic contribution analysis is made for the front field point of the sound field, and the modal with large contribution to the sound pressure of the front field point is calculated in the first 41 orders of modal, with the acoustic contribution as shown in Fig. 5.151. It can be seen from this figure that the contribution of the 9th order of modal is the largest, reaching 60.51%. The first four modals with large acoustic contribution are in the 9th, 2nd, 6th and 16th orders, and the their modal shape cloud diagram is shown in Fig. 5.152. It can be seen from the modal shape cloud diagram that there are obvious modal shapes in area 1 (panel 1) ~ area 4 (panel 4) on the rear case of the transmission. Therefore, after the calculation of acoustic transfer vector and modal acoustic contribution, the screening results are from area 1 to area 4 on the rear case of the transmission. In order to determine the area with large acoustic contribution more accurately, it is necessary to calculate the acoustic contribution of panel.

Relative modal acoustic contribution/(%)

3. Calculation of acoustic contribution of panel

Modal order number

Fig. 5.151 Acoustic contribution of each order of modal at the gear meshing frequency in gear 1

5.4 Practical Case of Vibration and Noise Optimization of Two-Speed …

373

Area 3 Area 1

(a) 2nd order modal

Area 2 (b) 9th order modal

Area 4 (c) 16th order modal

(d) 6th order modal

Fig. 5.152 Modal shape cloud diagram

According to the theory of acoustic computation, {ATV(r, ω)} and {ϕ}nj are expanded to transform Eq. (5.38) into the form shown in Eq. (5.40). p(r, ω) =

N ∑

i ωQ i (ω)

j=1

=

m ∑

AT Vk (r, ω){ϕ}n jk

k=1

N m ∑ ∑

i ωQ i (ω)AT Vk (r, ω){ϕ}n jk

k=1 j=1

=

m ∑

AT Vk (r, ω)vnk (ω) =

k=1

m ∑

pk (r, ω)

(5.40)

k=1

where m is the total number of nodes; k indicates the node number; j is the modal order; {ϕ}n jk is the normal modal displacement. If the study object is composed of a number of panels and each panel contains a number of nodes, when the panel number is c, the number of nodes in the panel is L, pc (r, ω) is the sound pressure contributed by the panel, then pc (r, ω) =

L ∑

pk (r, ω)

(5.41)

k=1

The acoustic contribution Dc (r, ω) of panel c is Dc (r, ω) =

| pc (r, ω)| cos(θ p − θc ) | p(r, ω)|

(5.42)

The calculation of the acoustic contribution of the panel can be used to analyze the panel which plays a major role in the total sound pressure and determine whether the role is positive or negative. The greater the absolute value of the acoustic contribution of a panel, the more obvious the influence of the vibration of the panel on the total sound pressure.

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5 NVH Test and Optimization for New Energy Vehicle Powertrain

4. Calculation of acoustic contribution of transmission case panel In order to accurately find the area (panel) with large acoustic contribution, the panel is divided from area 1 (panel 1) to area 4 (panel 4), as shown in Fig. 5.153. In order to minimize the influence of the number of elements on the analysis results, the number of elements on the four panels shall be basically similar. Figure 5.154 shows the acoustic contribution of the panel at the gear meshing frequency of 1583 Hz for gear 1. At the gear meshing frequency of 1583 Hz in gear 1, panel 4 has the largest acoustic contribution, followed by panel 1. In summary, panel 1 and panel 4 are the areas with large acoustic contribution of two-speed transmission case, and are also the target areas selected by case noise reduction optimization.

Panel 4

Panel 3

Panel 2 Panel 1

Acoustic contribution of panel/(%)

Fig. 5.153 Acoustic mesh panel partitioning

Panel 1

Panel 2

Panel 3

Panel No.

Fig. 5.154 Bar chart of acoustic contribution of panel at 1583 Hz

Panel 4

5.4 Practical Case of Vibration and Noise Optimization of Two-Speed …

5.4.6.4

375

Transmission Noise Reduction Design

The vibration noise of transmission case surface is affected by many factors. The radiated noise of transmission case can be reduced generally by adding stiffeners and pasting damping materials. The vibration amplitude of transmission case is reduced by adding stiffeners to increase local stiffness. Pasting damping material does not change the structure of transmission case. Instead, it converts the vibration energy loss into heat energy, so as to realize the optimization of case noise reduction. In this method, the vibration frequency of the case itself does not change, and the heat dissipation effect of the case may be weakened. Considering that the studied twospeed transmission has no external circulation cooling system, the vibration and noise performance of the transmission is optimized by adding stiffeners locally to the transmission case. Considering the influence of the adding area, shape and number of stiffeners on the structural stiffness of transmission case, a solution of adding arc bars and ribs locally is used in the target area, with the arc bar width of 3 mm, the start-stop end height difference of 138 mm, the rib width of 3 mm, and the height of 76.5 mm. The first solution is to add arc bars at panel 1 and ribs at panel 4. The second solution is to add a rib only at panel 4. Figures 5.155 and 5.156 show the optimization solutions respectively. The model of the optimization solution is re-meshed by finite element method, and the same boundary conditions and loads are applied. First, the free mode is calculated, and then the forced vibration response. Finally, the rectangular sound field with the same distance of 1 m from the transmission case as before is established to Fig. 5.155 Reinforcement schematic diagram of solution 1

Fig. 5.156 Reinforcement schematic diagram of solution 2

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5 NVH Test and Optimization for New Energy Vehicle Powertrain

complete the acoustic response calculation of the radiated noise. The results of modal frequency and modal shape, vibration response and sound field response before and after optimization are compared and analyzed. 1. Comparison of modal frequency and modal shape Figures 5.157 and 5.158 show the comparison of the modal frequency and frequency variations of the first 22 orders (within 4000 Hz) before and after the transmission case optimization. In solution 1, the modal frequency variation in orders 3, 4, 19, 20 and 21 exceeds 95 Hz, in orders 2, 6, 8, 9, 11, 12, 13, 14, 15, 16, 17, 18 and 22 does not exceed 35 Hz, and in the other orders is between 38 to 85 Hz. In solution 2, the modal frequency variation is small. The modal frequency variation in orders 13 and 20 exceeds 90 Hz, in orders 1, 2, 11, 16 and 17 does not exceed 30 Hz and in the others is between 35 and 80 Hz. In addition, the modal frequency in orders 1, 8, 12, 15, 18, 19, 20, 21 and 22 is in the descending state, while in solution 2, the modal frequency in the orders other than orders 10 and 16 is in the descending state. In solution 1 and solution 2, the modal frequency in order 3 is 1724 Hz and 1518 Hz respectively, effectively avoiding the gear meshing frequency 1583 Hz in gear 1.

Frequency/Hz

Fig. 5.157 Comparison of modal frequencies before and after optimization

Before optimization Solution 1 Solution 2

Fig. 5.158 Comparison of modal frequency variations before and after optimization

Frequency variation/Hz

Modal order number

Frequency variation in solution 1 Frequency variation in solution 2

Modal order number

5.4 Practical Case of Vibration and Noise Optimization of Two-Speed …

377

Figures 5.159 and 5.160 are the cloud diagrams of the modal shape of the first 4 orders after optimization in solution 1 and solution 2, respectively. Compared with the cloud diagram of the modal shape of the transmission case before optimization, the modal shape in some orders change and the vibration area caused by the order 2 modal with large acoustic contribution has been improved. 2. Vibration response comparison As shown in Figs. 5.161 and 5.162, at the gear meshing frequency of 1583 Hz, the maximum vibration acceleration of the case decreases from 5.72 m/s2 to 3.42 m/s2 and 2.44 m/s2 after optimization with solution 1 and solution 2, respectively. The maximum vibration acceleration of the case also decreases to a certain extent under the frequency doubling of other meshing frequencies within 4000 Hz. However, at the same time, it is found that under the gear meshing frequency of final reduction drive, the maximum value of vibration acceleration has a slight upward trend, and the

(a) Cloud diagram of modal (b) Cloud diagram of modal (c) Cloud diagram of modal (d) Cloud diagram of modal shape in order 1 at 1350Hz shape in order 2 at 1503Hz shape in order 3 at 1724Hz shape in order 4 at 2030Hz

Fig. 5.159 Cloud diagram of the modal shape of the first 4 orders after optimization with solution 1

(a) Cloud diagram of modal (b) Cloud diagram of modal (c) Cloud diagram of modal (d) Cloud diagram of modal shape in order 1 at 1358Hz

shape in order 2 at 1464Hz

shape in order 3 at 1518Hz

shape in order 4 at 1877Hz

Fig. 5.160 Cloud diagram of the modal shape of the first 4 orders after optimization with solution 2

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5 NVH Test and Optimization for New Energy Vehicle Powertrain

maximum value of vibration acceleration increases from 0.743 m/s2 to 0.953 m/s2 and 0.904 m/s2 . In general, it can be shown that both solutions 1 and 2 have inhibitory effects on the vibration of the transmission case. 3. Comparison of acoustic response of sound field The radiation sound field of the optimized transmission case is calculated. The sound field cloud diagram at the gear meshing frequency is shown in Figs. 5.163 and 5.164. At the gear meshing frequency within 4000 Hz and its doubling frequency, the transmission radiated noise performance is improved to a certain extent. At 1583 Hz, the maximum SPL of the sound field decreases from 71.6 dB to 67.8 dB and 70 dB, respectively. However, at 583 Hz in solution 1 and solution 2, the maximum SPL tends to increase, indicating that the total acoustic contribution of solution 1 and solution 2 to the transmission increases at this frequency. The SPL RMS of the noise in full-frequency band at 5000 r/min in gear 1 before and after optimization is solved within 100–4000 Hz, and the results are shown in Fig. 5.165. It can be seen from Fig. 5.165 that the RMS value of the transmission noise decreases to different degrees after optimization, indicating that the total acoustic contribution of the optimization solution to transmission decreases in the fullfrequency band of 100–4000 Hz. After optimization, the RMS value of noise pressure level decreases by about 2 dB at most. The comparative analysis of modal frequency and modal shape, vibration response and acoustic response of rectangular sound field before and after optimization of the transmission case shows that: By adding arc bars and ribs locally to the transmission case, the area where the vibration of the transmission case is more intense can be suppressed, and the radiated noise of the transmission case is effectively suppressed

(b) Cloud diagram of case response at 1583Hz

(b) Cloud diagram of case response at 1583Hz

Fig. 5.161 Case vibration response cloud diagram in solution 1

5.4 Practical Case of Vibration and Noise Optimization of Two-Speed …

(a) Cloud diagram of case response at 583Hz

379

(b) Cloud diagram of case response at 1583Hz

Fig. 5.162 Case vibration response cloud diagram in solution 2

(a) Sound pressure level cloud diagram of

(b) Sound pressure level cloud diagram of

sound field at 583Hz after optimization

sound field at 1583Hz after optimization

Fig. 5.163 Radiated noise cloud diagram of transmission after optimization with solution 1

in the 100–4000 Hz frequency band. This shows that the optimization solution is effective. The stiffeners not only increase the stiffness of the case, but also enhance the reflection in the process of sound wave propagation. When the transmission case vibrates, the stiffeners will also vibrate, thus becoming a noise source. The transmission radiated noise can be reduced only by adding stiffeners in a reasonable area. Both solutions 1 and 2 are effective, and the optimization effect of solution 1 is better than that of solution 2, indicating that areas 1 and 4 have large acoustic contributions. The addition of stiffeners in these two areas does not cause significant increase of acoustic contributions in other areas, and areas 1 and 4 are both effective addition areas.

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(a) Sound pressure level cloud diagram of

(b) Sound pressure level cloud diagram of

sound field at 583Hz after optimization

sound field at 1583Hz after optimization

Noise SPL RMS/dB

Fig. 5.164 Radiated noise cloud diagram of transmission after optimization with solution 2

Fig. 5.165 Noise comparison before and after optimization

5.4.6.5

Brief Summary

In this section, the forced vibration response is calculated on the finite element meshes of the two-speed automatic transmission case to obtain the vibration response information of the case surface, which is used as the boundary condition for the calculation of case radiated noise. The acoustic boundary element model of case is established by using the acoustic boundary element method, the vibration information on the case structured mesh is transferred to the boundary element model, and the mapping results of gear meshing frequency within 100–4000 Hz are briefly analyzed. Based on the vibration information of the case surface, the radiated noise of the case is calculated, and the SPL of six rectangular sound field points of the transmission is calculated under the gear meshing frequency within 100–4000 Hz and its doubling frequency. The results show that the SPL is larger at the front field point

Bibliography

381

of the transmission. The front field is selected as the target field for radiated noise optimization, and the acoustic transfer vector and modal acoustic contribution are combined to accurately locate the area that vibrates violently in the transmission rear case. After the optimization solution is determined, the modal frequency and modal shape, vibration response and sound field response before and after case optimization are compared and analyzed. The results show that solution 1 can achieve better optimization effect of the transmission radiated noise.

Bibliography China Automotive Technology & Research Center (2016) Technical specification for reduction gearbox of battery electric passenger cars: QC/T1022–2015[S]. China Plan Press, Beijing Kaleli T, Gur CH (2020) Determination of surface residual stresses in carburised AISI 8620 steel by the magnetic Barkhausen noise method. Insight-Non-Destructive Testing Condition Monitoring 6:416–421 Lang G, Wentao Z, Xin Z (2020) The optimization design on noise reduction of engine cooling fan. Automob Appl Technol 14:40–42 Lei Z, Xuhui W (2012) Radial electromagnetic vibration model characteristics of PMSMs for electric vehicles. Electric Machin Control 5:33–39 Liang W, Wang J, Luk P et al (2014)Analytical modeling of current harmonic components in PMSM drive with voltage-source inverter by SVP-WM technique. IEEE Trans Energy Convers 29(3):673–680 Liang W, Luk P, Fei W (2016) Analytical investigation of sideband electromagnetic vibration in integral-slot PMSM drive with SVPWM technique. IEEE Trans Power Electron (6):4795 Lingbo L, Lutao S (2016) CFD Simulation analysis and noise control of automotive HVAC box[C]. China Soc Automot Eng SAE-China Congress Proc 2016:1146–1149 Liu H, Hu J, Tang Y (2017) Discussion on vibration and noise test of automobile transmission. Shandong Ind Technol 09:266 Liu X, Zhu ZQ, Hasegawa M et al (2020) Investigation of PWMs on vibration and noise in SRM with sinusoidal bipolar excitation. In: IEEE international symposium on industrial electronics. IEEE 674–679 Park C, Kim GD, Yim GT et al (2020) A validation study of the model test method for propeller cavitation noise prediction. Ocean Eng 213:107655 Qiu Z, Chen Y, Liu H et al (2019) Analysis of sideband noise mechanism of permanent magnet synchronous motor based on multi-physics field desorption/China society of automotive engineers. In: SAE-China congress proceedings, pp 48–54 Qiuz Z, Kang Y, Chen Y et al. Analysis of the sideband current harmonics and vibro-acoustics in the PMSM with SVPWM. ET Power Electron 019(6):033–1040 Tang R, Song Z, Yu S et al (2010) Study on source of vibration and acoustic noise of permanent magnet machines by inverter. Electric Machin Control 14(03):12–17 Wang X, Lu J, Nian M (2015) Application and experimentation of vibration absorber in automotive vibration noise control. Sci Technol Eng 15(08):233–237 Wang H, Wang H, Li J (2019) The invention relates to an automobile rolling noise test system and a noise test method. China Rubber/Plast Technol Equipm 45(11):62 Zhang Y, Cui J, Liu K (2016) A method for locating abnormal noise source of steering system based on test equipment. Society of Automotive Engineers of Henan. Proceedings of the 13th Henan Automotive Engineering Science and Technology Symposium, 2016:421–423.

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Zhuang Y, Quan W, Du H (2014) Research on vibration and noise analysis of hybrid electric car based on structural component improvement. Shanghai Auto (06):43–45 Zu Z, Wang J, Gao L et al (2016) Optimization and NVH performance test for mounting system of extended range electric vehicle. J North Univ China (Nat Sci Edn) 37(03):238–244

Chapter 6

Vehicle Powertrain Reliability Test Technology

6.1 NEV Powertrain Reliability Test Technology 6.1.1 Overview of Test Equipment 6.1.1.1

Two-Motor Power Cycle Fatigue Test Bench

The power cycle fatigue test bench is used to test the high-speed gear performance and transmission performance of electric vehicles, which can realize the accurate evaluation of high-speed gear life and performance of electric vehicles. The twomotor power cycle fatigue test bench is shown in Fig. 6.1, which can be used for high-speed gear life test, reverse drag test, efficiency test, burn test, failure test, high-speed test, high-speed low-torque test and other test items of the high-speed gear.

6.1.1.2

Three-Motor Power Transmission Comprehensive Performance Test Bench

The three-motor power transmission comprehensive performance test bench is built for the development of automobile front/rear drive mechanical transmission. The high-performance dynamic dynamometer is used to simulate the load of the vehicle, and the input motor is used to simulate the power source input, which can realize the accurate test and evaluation of the life and performance of the front/rear drive transmission. The three-motor power transmission comprehensive performance test bench, as shown in Fig. 6.2, can be used for the life test, efficiency test, shift performance test, differential test, high-speed test and high-speed low-torque test, reverse drag test, burn test and other test items of the automobile front/rear drive mechanical transmission. © Huazhong University of Science and Technology Press and Springer Nature Singapore Pte Ltd. 2023 Y. Chen, New Energy Vehicle Powertrain Technologies and Applications, Key Technologies on New Energy Vehicles, https://doi.org/10.1007/978-981-19-9566-8_6

383

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6 Vehicle Powertrain Reliability Test Technology

Fig. 6.1 Two-motor power cycle fatigue test bench

Fig. 6.2 Three-motor power transmission comprehensive performance test bench

6.1.1.3

Three-Motor Powertrain Semi-Anechoic Chamber

The three-motor powertrain semi-anechoic chamber is mainly built for the vibration and noise performance test of automobile transmission. With the seamless connection technology of wedge structure, high sound insulation muffler, high-speed and lowinertia carbon fiber shaft, and the bench and vibration and noise test system, the

6.1 NEV Powertrain Reliability Test Technology

385

Fig. 6.3 Three-motor powertrain semi-anechoic chamber

semi-anechoic chamber can achieve low background noise and meet the NVH test requirements of automobile transmission in various driving cycles and is suitable for the front/rear drive transmission or assembly of electric vehicles. The three-motor powertrain semi-anechoic chamber, as shown in Fig. 6.3, can be used for steadystate NVH test, acceleration and deceleration NVH test, noise source identification, noise contribution, sound power, sound pressure level test, three-dimensional sound field analysis, sound quality evaluation, gear rattle, whine, noise pickup and fault diagnosis.

6.1.2 Reliability Test of Key Components Reliability test of key components of the NEV powertrain mainly includes fatigue life test, transmission efficiency test, differential reliability test, high-speed performance test, NVH test and other test items.

6.1.2.1

Fatigue Life Test

Test procedures: (1) Install the transmission on the test bench. (2) The test oil temperature is (80 ± 5) °C. (3) The test conditions are as specified in Table 6.1.

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Table 6.1 Fatigue life test indexes Life index (output end revolutions/cycle time)

Test conditions

Forward rotation and forward drive High torque condition

High speed condition

Input speed/(r/min)

Maximum power ≥ 80 × 105 point speed × (1 ± 5‰)

Input torque/(N · m)

Maximum input torque ± 5

Input speed/(r/min)

(Maximum power point speed ÷ reduction ratio) × (1 ± 5%)

Input torque/(N · m)

(Maximum input torque x reduction ratio) ± 5

Input speed/(r/min)

Maximum input ≥ 40 × 105 speed × (1 ± 5‰)

Input torque/(N · m)

Maximum power point torque ± 5

–

Reverse rotation and forward drive

Forward rotation and reverse drive

–

≥2h

≥ 10 × 105

–

–

–

Note The maximum power point speed in the high torque condition refers to the speed under the maximum power at the maximum input torque, while the maximum power point torque in the high speed condition refers to the torque under the maximum power at the maximum input speed

(4) The test time is determined according to the requirements in Table 6.1. (5) The test is carried out in the order of forward rotation first and then reverse rotation, and the whole test can be completed in 10 cycles. Processing of test results: If the main parts are not damaged (such as fracture, severe pitting of tooth surface (pitting area over 4 mm2 or depth over 0.5 mm), peeling, bearing stuck, etc.) after the test is completed according to the fatigue life test indexes specified in Table 6.1, the transmission fatigue life test is passed.

6.1.2.2

Transmission Efficiency Test

Test procedures: (1) Running-in. (2) Fill lubricating oil as required. (3) Test speed: Take 5 speeds uniformly from 500 r/min to the designed maximum input speed range, including the designed maximum input speed.

6.1 NEV Powertrain Reliability Test Technology

387

(4) Test torque: The input torque is 50% and 100% of the maximum input torque designed for the reducer. (5) The oil temperature is controlled in the range of (80 ± 5)°C. (6) The test only measures the forward direction, combined with speed, torque and oil temperature combination in turn. Processing of test results: According to the measured results, the transmission efficiency-speed and transmission efficiency-torque curves are drawn at the test temperature. The comprehensive transmission efficiency of transmission is the average value of all detected transmission efficiencies, and is calculated and evaluated according to Eq. (6.1). 2 η=

2

k=1

5

m=1

20

n=1

ηmnk

(6.1)

where η is the average value of transmission efficiency measured at 5 test speeds, 2 torques and 2 gears, namely, the comprehensive transmission efficiency of transmission, which shall not be less than 95%.

6.1.2.3

Differential Reliability Test

Test procedures: (1) Running-in: Either output end is fixed and cannot rotate, and the other output end can rotate freely; at the oil temperature of 95–105 °C, the input speed is (2000 ± 10)r/min for no less than 30 min to complete no-load forward rotation. Replace the lubricating oil after running-in. (2) Install the transmission on the test bench and fill lubricating oil as required. (3) The test oil temperature is controlled in 90–110 °C. (4) High-speed low-torque: Perform forward rotation at high gear, keep 50–55% of the maximum input speed and 25–35% of the maximum input torque. Either output end is fixed and cannot rotate, and the other output end can rotate freely for no less than 30 min (after 15 min, the fixed end and rotating end can be switched). (5) Low-speed high-torque: Perform forward rotation at low gear, keep (20% ± 10 of the maximum input speed)r/min and the slip speed of 12–15% for not more than 3 min; increase the input torque from 0 to (75% ± 5 of the designed maximum input torque)N · m, and keep at (75% ± 5 of the designed maximum input torque)N · m for no less than 1 min; then decrease from (75% ± 5 of the maximum design input torque)N · m to 0, thus forming a cycle. The total number of cycles is not less than 200. Processing of test results: After completing high-speed low-torque and low-speed high-torque test, the transmission rotation is flexible without clamping stagnation or abnormal sound, indicating that the differential reliability test is passed.

388

6.1.2.4

6 Vehicle Powertrain Reliability Test Technology

High Speed Performance Test

Test procedures: (1) Install the transmission on the test bench. (2) Fill lubricating oil as required and control the test oil temperature at 90–110 °C. (3) Run the specified time according to the rotation direction, input speed and torque specified in Table 6.2. Processing of test results: During the test, there is no oil leakage phenomenon, the bearing, gear, oil seal and other parts are not burned or damaged, and the transmission is running normally, indicating that the transmission passes the high speed performance test.

6.1.2.5

NVH Test

NVH test is divided into steady-state and transient condition tests. The background noise shall be measured before formal steady-state measurement of transmission noise. Test speed: Take multiple speeds uniformly from 500 r/min to the designed maximum input speed range, including the designed maximum input speed. Test torque: Take multiple torques uniformly from 10 N · m to the designed maximum input torque range, including the designed maximum input torque. At the same time, the test point shall not exceed the maximum power carried by the transmission. Measure and record vibration and noise values. NVH test procedure under transient condition: (1) Install the transmission on the test bench and fill lubricating oil as required. (2) The transmission operates at a speed change rate of 200 r/s. Taking a two-speed transmission as an example, test the acceleration and coasting modes of gear 1, gear 2 and reverse gear according to Table 6.3. Processing of test results: (1) Use the sound pressure A weighted network. (2) For the noise detection instrument, if the value fluctuation is less than 3 dB, the average value of the upper and lower reading limits shall be taken; if the value fluctuation is greater than 3 dB, the RMS value of the upper and lower reading limits shall be taken. (3) When the difference between the noise value measured at each measuring point of the transmission under test and the background noise value at the point is less than 3 dB, the measurement value is invalid. If the difference is equal to 3–10 dB, it shall be corrected according to Table 6.4. (4) The corrected value with the maximum reading in the measuring points is taken as the noise value. Perform high and low gear loading/coasting noise tests for no less than 30 s according to the noise test conditions specified in Table 6.3. The transmission noise

Rated power point torque ± 5

50% of the maximum input speed × (1 ± 5‰)

Negative rotation

Input torque/(N · m) Rated power point torque ± 5

Maximum input speed × (1 ± 5‰)

Input speed/(r/min)

Positive rotation

Rotation direction

Table 6.2 High speed performance indexes

≥ 0.17

≥5

Duration/h

6.1 NEV Powertrain Reliability Test Technology 389

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6 Vehicle Powertrain Reliability Test Technology

Table 6.3 Transient condition test points Gear

Torque/(N · m)

Acceleration mode/(r/min)

Coasting mode/(r/min)

Gear 1

10

50–5000

5000–50

60

50–4000

4000–50

90

50–3000

3000–50

120

50–2000

2000–50

10

50–7000

7000–50

60

50–4000

4000–50

90

50 ~ 3000

3000–50

10

− 50 to − 2000

− 2000 to − 50

60

− 50 to − 2000

− 2000 to − 50

120

− 50 to − 1000

− 1000 to − 50

Gear 2

Reverse gear

Table 6.4 Transmission noise corrected value Range/dB

3

4

5

Corrected value/dB

−3

−2

−1

6

7

8

9

10 0

shall not be greater than 83 dB(A), the transmission coasting noise value shall not be greater than the loading noise value, and there is no abnormal sound, indicating that the test is passed.

6.1.3 Shift Performance Test Test procedures: (1) Fill lubricating oil as required. After 300 times running in each gear, the transmission is driven from the output end. (2) Alternate shift between two adjacent gears, and ensure that the input speed is (6000 ± 10) r/min when hanging in high gear, and (4000 ± 10) r/min when hanging in low gear. (3) Adjust the shift force to the design specified value, the oil temperature to 60– 90 °C, and the control accuracy to ± 5 °C. (4) Measure and record the synchronization time and force of each gear, measure and record the synchronization torque of each gear, and test at the frequency of 10–16 times /min. Figures 6.4 and 6.5 show the structure diagram and 3D layout of the shift performance test bench of a two-speed transmission respectively. Processing of test results:

6.1 NEV Powertrain Reliability Test Technology

Speed sensor

391

Dyn amo met er

Flywheel

Axle shaft

Signal communication Electrical connection

Axle shaft Tire

Tire

Enco der Ethernet

Motor

Console

Shift motor Battery pack BMS MeCa measurement and calibration software CAN bus

Ethernet

dSPACE vehicle model

Fig. 6.4 Shift performance test bench structure diagram

Fig. 6.5 3D layout of shift performance test bench. 1—Flywheel; 2—dynamometer; 3—drive motor; 4—transmission; 5—half shaft; 6—tire

(1) Evaluate the performance of the transmission shift system with the synchronous impulse as the index, which is not more than 100 N · s. (2) Evaluate the performance of the transmission shift system with the impact degree as the index, which is J=

d 2u 1 i g i f ηt dTR = 2 d t δm rw dt

(6.2)

where u is the vehicle driving speed (km/h), δ is the conversion factor of vehicle gyrating mass, δ > 1; m is vehicle mass (kg); ig and if are the speed ratio and final

392

6 Vehicle Powertrain Reliability Test Technology

ratio of the transmission respectively; ηt transmission efficiency; r w is the rolling radius of tire; T R is the transmission output torque; t is time. There are different standards for shift impact in different countries: J ≤ 17.64 m/s3 in Chinese standards and J ≤ 10 m/s3 in German standards.

6.2 Test Technology for Powertrain Components 6.2.1 Gear Fatigue Test Technology 6.2.1.1

Gear Bending Fatigue Strength Test

1. Test method To determine the gear bending fatigue strength, the gear bench running test (referred to as test method A) or the gear teeth pulsating loading test (referred to as test method B) should be used. In case of difference between the results of test method A and test method B, the result of test method A shall prevail. Test method A is to install the test gear pair on a gear tester for load running test until the gear teeth show bending fatigue failure or the number of root stress cycles reaches the specified cycle base N. In case of no failure (hereinafter referred to as “overrunning”), the test is terminated and a lifetime data of the tooth under test stress is obtained. When the test gear and test process are normal, the data is usually referred to as the test point. Test method B is to use a special fixture in a pulsating fatigue tester to carry out pulsating loading on the gear teeth of the test gear until the gear teeth show bending fatigue failure or overrunning. Then the test is terminated and a lifetime data of the gear teeth under the test stress is obtained. In the test, the pulsating load is only applied to the teeth of the test gear, and the test gear does not engage. The selected test gear teeth shall be at least one gear tooth apart from the loaded gear teeth (including the supporting teeth). Several test points can be obtained for each test gear. After the test points are obtained by different test methods, the bending fatigue characteristic curve and ultimate bending fatigue stress of the test gear are measured by the following combinations of different test points. The conventional grouping method is used to determine the reliability stress-life curve of the test gear (i.e. R–S–N curve), and to obtain the ultimate bending fatigue stress of the test gear. 4–5 stress levels are taken during the test, with at least 5 test points (excluding the overrunning point) at each stress level. The number of bending stress cycles at all test points in the highest stress level is not less than 0.5 × 105 . The stress interval between the highest stress level and the next highest stress level is 40–50% of the total test stress range, and gradually decreases with the stress. At least one test point in the lowest stress level is overrunning. The few-test-point combination method is usually used to measure S–N curve or only the ultimate stress, and the total number of test points is 7–16. 4–10 stress levels

6.2 Test Technology for Powertrain Components

393

are taken to measure S–N curve, with 1–4 test points at each stress level. The lifting method can be used to determine the ultimate stress. Each factor shall have at least 3 test points when using the orthogonal method. 2. Test conditions and test gears The gear bending fatigue strength test shall be carried out in accordance with the test conditions and test gears specified below (except for the subjects of comparative tests), from which the ultimate bending stress of test gears can be determined as σ Film . (1) Test conditions When the test method A is used to determine the gear bending fatigue strength, a tester of power flow closed structure shall be used. The calibration of the tester is shown in Appendix A of GB/T14230-2021 Test Method of Tooth Bending Strength for Gear Load Capacity (Appendixes A to E mentioned in Sect. 6.2.1 refer to the corresponding appendixes in this Standard). The center distance of the tester is generally 90–150 mm and the linear speed of the test gear is 8–16 m/s. The accuracy of the tester shall not be less than the accuracy required by the test gear, and shall have the following basic functions: (a) Automatic stop when a tooth is broken; (b) A circulating fuel injection system to ensure good gear lubrication; (c) With a lubricating oil temperature control device, it shall control the return oil temperature below 60 °C; (d) With a cycle number recording device with the recording error not more than ± 0.1%. When the test method B is used to determine the gear bending fatigue strength, a pulsating fatigue tester shall be used, and the fixture shall be designed according to the test requirements and test gear parameters. The main technical performance and measurement of the tester are shown in Appendix B, and the design and technical requirements of the fixture are shown in Appendix C. The lubricating oil is selected and maintained according to JB/ T8831-2001. In general, the lubricating oil shall be sampled for inspection after continuous operation of the tester for three months. (2) Test gear Test gear modulus m = 3–5 mm, helical angle β = 0°, tooth width b = 10–50 mm, pressure correction coefficient Y ST = 2.0, root fillet parameter qs = 2.5, root fillet roughness Rs ≤ 10 µm, and accuracy of level 4–7 specified in GB/T10095.1-2008. The tooth profile and the root arc line must be smoothly transitioned. Check the test gear accuracy and record the measured value, test the surface hardness and base pitch deviation of all test gears and eliminate unqualified test gear. The same group of test gears must have the same processing equipment and processing technology.

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6 Vehicle Powertrain Reliability Test Technology

The test gear materials must be provided with a formal technical document, including material trademark, smelting method, chemical composition, heat treatment state, grain size, mechanical properties, metallographic structure and nonmetallic inclusions. All indexes shall comply with the provisions of routine inspection in GB/T3480.5-2008. Non-destructive testing shall be carried out for test gear materials when possible. The gear bending fatigue strength test can also be carried out under the condition that the test conditions and test gear parameters are consistent or similar to those of the product gear. 3. Bending fatigue failure criteria Any of the following conditions in the test shall be judged as bending fatigue failure: (1) Fatigue cracks observed at the root of the gear teeth. (2) Load or frequency drop by 5–10%; (3) Broken tooth along the root. 4. Test procedures (1) Preparation before the test (a) When the specified test conditions are met, the performance of the gear tester shall be checked according to Appendix A or Appendix B. (b) After cleaning the test gear, visually inspect the transition arc of the tooth root without machining tool marks or other forms of damage, and number the test gear and gear teeth. (c) The test gear shall be installed according to the tester requirements or the fixture design requirements. (2) Preliminary test The preliminary test is to determine the stress level of the test. Generally, the load range and ultimate stress in the fatigue area can be estimated by measuring an S–N curve, and the stress level can be determined according to the relevant requirements. (3) Test process monitoring Carry out the loading test point by point according to the desired stress level. During the test, check the test equipment frequently, and exclude any abnormalities in time. Accurately record the failure cycle life of the test site and make a complete test record for each test site. See Appendix E for the record sheet. Keep the test gear and broken teeth for failure analysis. (4) Supplementary test point The test points of the same stress level shall be tested for distribution (see Appendix D). If the linear correlation coefficient of the distribution function cannot meet the minimum requirement, the test points shall be supplemented.

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395

5. Test gear root stress calculation (1) Test method A The root stress of the test gear in test method A is calculated according to Eq. (6.3): σF =

Ft K A K V K Fβ K Fα Y F Y S Yβ bnY ST Yδr elT Y Rr elT Y X

(6.3)

See GB/T3480.5-2021 for the meaning and value of each letter code in the equation. (2) Test method B First, determine the exact position of load application point E by the method shown in Appendix C. The root stress of the test gear shall be calculated according to the determined position of point E according to Eq. (6.4): σ F =

Ft Y E F Y S E bnY ST Yδr elT Y Rr elT Y X

(6.4)

where Y FE is the form factor when the load is applied to point E; Y SE is the stress correction factor when the load is applied to point E. The meanings and values of other letter codes are shown in GB/T3480.5-2021. Y FE and Y SE are calculated according to the equation given by GB/T3480, where, αe , γe , α Fe and h Fe are respectively substituted by αe , γe , α Fe h Fe . Note: The root stress calculated by Eqs. (6.3) and (6.4) has transformed the test conditions and test gear into the standard state required by GB/T 3480.5-2021. When calculating the bending static strength of gear teeth, the root stress is still calculated according to Eq. (6.3) or Eq. (6.4), but Y Rr elT j = 1.0 and Y X j = 1.0 shall be taken at this time; Yδr elT j can be calculated by the equation listed in Table 24 in GB/T 3480.5-2021 or obtained by actual measurement. For constructional steel, quenched and tempered steel, ductile cast iron and pearlitic malleable cast iron, when NL ≤ 104 (NL ≤ 103 for other materials), the stress can be regarded as static stress. Due to the tester limitations, the cyclic characteristic coefficient of test method B is r F = Fmin /Fmax = 0 and the actual gear stress σ F shall be converted into the pulsating cyclic tooth root stress σ F at r F = 0, the unit is N/mm2 , and the conversion formula is σF =

(1 − r F )σ F σ

F 1 − r F σb +350

(6.5)

where σb is the tensile strength, N/mm2 . The cyclic characteristic coefficient rF is constant during the test and r F ≤ 0.05.

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6 Vehicle Powertrain Reliability Test Technology

6. Statistical processing of test data At the stress level with the total number of test points as n without overrunning point, the lifetime values are ranked in Eq. (6.6): N L1 ≤ N L2 ≤ · · · N L(n−1) ≤ N Ln

(6.6)

At the stress level with the total number of test points as n with overrunning point and with the number of failed test points as r, the lifetime values are ranked as N L1 ≤ N L2 ≤ · · · N L(r −1) ≤ N Lr For a certain lifetime value NLi , its lifetime empirical distribution function value is F(N Li ) =

i n+1

(6.7)

Or i − 0.3 n + 0.4

F(N Li ) =

where n is the total number of test points; i is the serial number of the test points in order of life value from small to large, i = 1, n in the absence of overrunning point and i = 1, r in case of overrunning point. In test method B, if double tooth loading is adopted, the failure sequence is calculated by the average order method. When P pairs of teeth are loaded and r teeth fail (r ≤ P), n = 2P, then the empirical distribution function value of lifetime can be calculated as Ai n+1

(6.8)

Ai − 0.3 n + 0.4

(6.9)

F(N Li ) = Or F(N Li ) =

where n is the total number of test gear teeth: n = 2P; Ai is the average order of the test sites according to the lifetime value from small to large, and Ai = Ai−1 +

n + 1 − Ai−1 n + 3 − 2i

(6.10)

where i is the separate order of failed test points, i = 1, r . When the life distribution function of the test gear is unknown, the normal distribution, lognormal distribution or two-parameter Weibull distribution is generally

6.2 Test Technology for Powertrain Components

397

used for distribution test to determine the distribution type. The three distribution functions are as follows:   N L − μNL (6.11) F(N L ) = φ σNL   ln N L − μln N L (6.12) F(N L ) = φ σln N L   NL k (6.13) F(N L ) = 1 − exp − b where NL is the number of root stress cycles; µvL is the population mean of normal distribution function; σ N L is the population standard deviation of the normal distribution function; μInN L is the population logarithmic mean of the lognormal distribution function; σInN L is the population logarithmic standard deviation of the lognormal distribution function; b is the scale parameter of Weibull distribution function; k is the shape parameter of Weibull distribution function. The fitting of the distribution function curve and the confirmation of the parameters of the R–S–N curve are shown in Appendix D. 7. Test Report The test report shall include: (1) (2) (3) (4) (5) (6) (7)

Test purpose and requirements; Test method; Test conditions and test gear; Original test data; Processing results of test data; Damage analysis; Test unit, reporter, reviewer and date.

6.2.1.2

Gear Contact Fatigue Strength Test

1. Test method To determine the gear contact fatigue strength, a load running test of test gear shall be carried out on a gear tester. When the tooth surface shows contact fatigue failure or the number of stress cycles of the tooth surface reaches the specified cycle base N0 without failure (overrunning), the test is terminated and a lifetime data of the tooth surface under the test stress is obtained. When the test gear and test process are normal, the data point obtained is the test point. According to different test purposes, the following different combinations of test points are selected, and the contact fatigue characteristic curve and ultimate contact fatigue stress of test gear are determined by statistical processing of test data.

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6 Vehicle Powertrain Reliability Test Technology

(1) Conventional grouping method The conventional grouping method is used to measure the R–S–N curve of the test gear and to obtain the ultimate contact fatigue stress of the test gear. 4–5 stress levels are taken during the test, with at least 5 test points (excluding the overrunning point) at each stress level. The number of bending stress cycles at all test points in the highest stress level is not less than 0.5 × 106 . The stress interval between the highest stress level and the next highest stress level is 40–50% of the total test stress range, and gradually decreases with the stress. At least one test point in the lowest stress level is overrunning. (2) Few-test-point combination method The few-test-point combination method is usually used to measure S–N curve or only the ultimate stress, and the total number of test points is 7–16. 4–10 stress levels are taken to measure S–N curve, with 1–4 test points at each stress level. The lifting method can be used to determine the ultimate stress. Each factor shall have at least 3 test points when using the orthogonal method. 2. Test conditions and test gears The gear contact fatigue strength test shall be carried out in accordance with the test conditions and test gears specified below (except for the subjects of comparative tests), from which the ultimate contact stress of test gears can be determined as σ Hlim . (1) Test conditions A tester of power flow closed structure shall be used for the test whose calibration is shown in Appendix A. The center distance of the tester is generally 90–150 mm and the linear speed of the test gear is 8–16 m/s. The accuracy of the tester shall not be less than the accuracy required by the test gear, and shall have the following basic functions: (1) Automatic stop when a tooth is broken; (2) A circulating fuel injection system to ensure good gear lubrication; (3) With a lubricating oil temperature control device, it shall control the return oil temperature below 60 °C; (4) With a cycle number recording device with the recording error not more than ± 0.1%. The lubricating oil is selected and maintained according to JB/ T8831-2001. In general, the lubricating oil shall be sampled for inspection after continuous operation of the tester for three months. (2) Test gear Test gear modulus m = 3–8 mm, helical angle β = 0°, tooth width b = 10–50 mm, gear ratio u = 1.2–1.5 (pinion as drive wheel), identical test gear pair materials, working tooth width b > 0.05a (a is the center distance, unit mm), surface roughness Rz = 2–5 µm, accuracy class 4–6 in GB/T10095.1-2008, and the basic tooth profile conforming to the provisions of GB/T1356-2001.

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The material, heat treatment and machining inspection of the test gear are shown in Appendix B. The gear contact fatigue strength test can also be carried out under the condition that the test conditions and test gear parameters are consistent or similar to those of the product gear. 3. Contact fatigue failure criteria The pitting damage degree on tooth surface is used as the criterion of contact fatigue failure in the gear contact fatigue strength test. There are two methods to calculate the tooth surface pitting damage as follows: (1) Single-tooth pitting area ratio, with the formula of Rs = A S /Asw

(6.14a)

where RS is the pitting area ratio of single tooth, %; AS is the sum of pitting area on a single tooth surface of the test gear, mm2 ; ASW is the working surface area of a single tooth surface of the test gear, mm2 . (2) Gear pair pitting area ratio, with the formula of RT = A1T / A1T w + A2T /A2T w

(6.14b)

where RT is pitting area ratio of gear pair, %; A1T is the sum of all pitting area of the drive wheel of the test gear pair, mm2 ; A2T is the sum of all pitting area of the driven wheel of the test gear pair, mm2 ; A1Tw is the sum of the working area of all teeth of the drive wheel of the test gear pair, mm2 ; A2Tw is the sum of the working area of all teeth of the driven wheel of the test gear pair, mm2 . Failure discrimination criteria based on pitting area rate are as follows: (1) For non-surface hardened gears, the pitting generally occurs on all tooth surfaces. When the hardness of test gear pairs is equal or similar, their pitting damage limit is RT = 2%. (2) For surface hardened gears, including carburized, nitrided, carbonitrided and flame or induction quenched gears, the pitting generally occurs on a small number of tooth surfaces. Their pitting damage limit is RT = 0.5%. When the test gear pitting area ratio reaches the pitting damage limit above, the tooth surface is judged to fail. However, for the practical application of automobile transmission gears, the surface peened gear can be used for millions of cycles even if the damage area reaches 10%, up to 30% complete pitting. (3) Non-surface hardened test gear cycle base N0 = 5 × 107 , surface hardened test gear cycle base N0 ≥ 5 × 107 . When the number of stress cycles on the tooth surface reaches the cycle base N0 , and the degree of tooth surface pitting damage does not reach the pitting damage limit, the test is stopped and the test point is judged to overrun.

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4. Test Procedures (1) Preparation before test (a) When the specified test conditions are met, the performance of the gear tester shall be calibrated according to relevant provisions. (b) After cleaning the test gear, visually inspect the tooth surface without corrosion, rust or other forms of damage, and number the test gear and gear teeth. (c) Check the tooth surface contact after the installation of the test gear. When the tester is loaded to the test load, the contact spot area of the tooth surface along the working tooth width direction shall account for not less than 90%, and the contact spot area along the tooth height direction shall account for not less than 80%. (2) Preliminary test The preliminary test is to determine the stress level of the test. Generally, the stress range and ultimate stress in the fatigue area can be estimated by measuring an S–N curve, and the stress level can be determined according to relevant requirements. (3) Test process monitoring (a) Often check the operation of the tester and control the oil temperature during the test. For the tester with static loading, determine the reloading time interval according to the unloading situation, and make detailed records. (b) Determine the tooth surface inspection time interval according to the test gear contact stress size. At the beginning of the test, observe the tooth surface with a 10X magnifying glass. After the pitting damage is found, the inspection time interval shall be shortened according to the damage morphology and expansion trend in time, so as to accurately record the number of cycles when the pitting damage limit of the tooth surface is reached. If the pitting area rate exceeds the pitting damage limit when the tooth surface is checked, half of this interval is taken as the time when the interval reaches the tooth surface failure. (c) Track and check the morphology of pitting damage, the position on the tooth surface, the tooth number and stress cycle times of the tooth surface, and make description and record, and perform film mulching or photography if necessary. (d) In case of damage other than the tooth surface pitting during the test, such as abnormal wear and tear, gluing, etc., carefully record their changes, and improve the lubrication conditions and operating conditions. Non-contact fatigue failure shall be judged in case of moderate wear, moderate gluing or tooth breakage and this data cannot be used as a test point.

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(4) Supplementary test point The test points of the same stress level shall be tested for distribution. If the linear correlation coefficient of the distribution function cannot meet the minimum requirement, the test points shall be supplemented. 5. Calculation of test gear contact stress Calculate the test gear contact stress according to the following equation: √ Z H Z E Zα Zβ σH = ZV ZL Z R ZW Z X

Ft (u ± 1)K A YV Y H α Y Hβ d1 bu

(6.15)

See GB/T3480.2-2021 for the meaning and value of each letter code in the equation. Note: The contact stress calculated in Eq. (6.15) has transformed the test conditions and test gear into the standard state required by GB/T 3480.2-2021. 6. Statistical processing of test data At the stress level with the total number of test points as n without overrunning point, the lifetime values are ranked as N L1 ≤ N L2 ≤ · · · N L(n−1) ≤ N Ln

(6.16)

At the stress level with the total number of test points as n with overrunning point and with the number of failed test points as r, the lifetime values are ranked as N L1 ≤ N L2 ≤ · · · N L(r −1) ≤ N Lr

(6.17)

For a certain lifetime value N Li , its lifetime empirical distribution function value is F(N Li ) =

i n+1

(6.18)

i − 0.3 n + 0.4

(6.19)

Or F(N Li ) =

where n is the total number of test points; i is the serial number of the test points in order of life value from small to large, i = 1, n in the absence of overrunning point and i = 1, r in case of overrunning point. When the life distribution function of the test gear is unknown, the two-parameter Weibull distribution, lognormal distribution or normal distribution is generally used for distribution test to determine the distribution type. The three distribution functions are as follows:

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  NL k F(N L ) = 1 − exp − b   ln N L − μln N L F(N L ) = φ σln N L   N L − μNL F(N L ) = φ σNL

(6.20) (6.21) (6.22)

where N L is the number of root stress cycles; b is the scale parameter of Weibull distribution function; k is the shape parameter of Weibull distribution function; μln N L is the population logarithmic mean of the lognormal distribution function; σln N L is the population logarithmic standard deviation of the lognormal distribution function; μ N L is the population mean of normal distribution function; σ N L is the population standard deviation of the normal distribution function. The fitting of the distribution function curve and the confirmation of the parameters of the R–S–N curve are shown in Appendix C. 7. Test report The test report shall include: (1) (2) (3) (4) (5) (6) (7)

Test purpose and requirements; Test method. Test conditions and test gear; Original test data; Processing results of test data; Damage analysis; Test unit, reporter, reviewer and date.

6.2.2 Bearing Fatigue Test Technology 6.2.2.1

Test Conditions

1. Tester The bearing tester must be in line with the relevant standards and pass the identification. The same batch of test samples shall be tested on the testers of the same structural performance under the same test conditions. 2. Bearing selection (1) Fit the bearing to the shaft and case as specified in Table 6.5. (2) For the test conditions with large radial load, under the condition of ensuring the working clearance of the bearing, the interference fit tolerance between the bearing and the shaft shall be appropriately increased to prevent the relative

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Table 6.5 Type of fitted bearing of the bearing to shaft and case Fitted location

Bearing type

Bearing diameter series

Fit

Fit of bearing and shaft

Ball bearing

8, 9, 0.1

k5

2, 3, 4

m5, m6

8, 9, 0.1

m5

2, 3, 4

n6, p6

Thrust bearing (unidirectional)

All series

p6

Radial bearing

All series

H7

Thrust bearing

All series

H8

Roller bearing

Fit of bearing and case

Note During the fitting, the limit deviation of shaft and case holes shall comply with the provisions of Appendix A in GB/T275-2015; the fit in the table is determined on the basis that the inner ring of the bearing bears cyclic (rotational) load and the outer ring bears local load

sliding between the inner ring of the bearing and the shaft in the process of operation. 3. Bearing outer ring temperature Not allowed to exceed 80 °C during grease lubrication; and not allowed to exceed 95 °C during oil lubrication. 4. Bearing rotating speed The speed of the inner ring is generally not more than 60% of the bearing limit speed. The specific value of the speed shall be selected according to the speed data of the tester. 5. Bearing lubrication (1) L-FC type 32 oil that meets SH0017-1990 standard shall be used for circulating oil lubrication. Check the oil viscosity and impurities regularly. (2) The diameter of dust and mechanical impurities in the oil shall not be more than 3um. A special oil filter device shall be used to reduce the content of impurities in the oil. (3) The circulating oil supply shall meet the requirements listed in Table 6.6. Table 6.6 Circulating oil supply Nominal inner diameter of bearing d/mm

Circulating oil supply/(L/h)

10–30

≥ 100

> 30–60

≥ 200

> 60–120

≥ 300

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6.2.2.2

Test Preparation

1. Sample preparation (1) Sampling. In the product batch that has been accepted, the products with the same process and specifications are randomly selected to inspect according to the provisions of the relevant standards. (2) Sample size: Generally, 10–20 sets of samples are taken. The sample size can be upper limit in case of short test cycle. (3) Numbering. Generally, the number shall be marked on the non-datum surface of the ring. Bearings with inner diameter d ≤ 20 mm can be numbered on the outer cylinder surface or other parts. Both the inner and outer rings of the separable bearing shall be numbered. 2. Test head assembly The test head consists of the test spindle, load body, left and right flanges, left and right bushings, disassembly ring, isolating ring, left and right lock nuts at the shaft end, and load bearing. Each part of the test head shall conform to the drawing requirements. The assembled test head shall meet the requirements of the assembly drawing. After the test head is assembled with the tester body, all systems (load transmission, lubrication, drive, etc.) shall be checked to ensure their normal function. 3. Tester debugging (1) The tester shall be applied a load with the error controlled within the range of ± 2%. The pressure gauge of class 1.5 shall be used for hydraulic loading. The precision pressure gauge of class 0.4 shall be calibrated in advance and regularly. (2) The circulating oil circuit shall be kept smooth, and the oil supply pressure shall be no less than 0.25 MPa. (3) The speed error shall be controlled within the range of ± 2%, and the tachometer shall be calibrated regularly. (4) The combination of the lower plane of the loading piston head and the concave surface of the load body shall be checked by the imprint method. The contact shall be smooth and normal, and the piston shall move flexibly. (5) After installation, drag the belt by hand. There shall be no obstruction or abnormality. (6) The electrical system shall be safe and reliable. 6.2.2.3

Test Procedure

1. Failure criteria (1) Fatigue failure: A certain depth and area of matrix metal spalling on the working surface of the rolling body or ring of the test bearing, with the ball

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bearing spalling area not less than 0.5 mm2 , the roller bearing spalling area not less than 1 mm2 , and the depth not less than 0.05 mm. (2) Other failure: Any part of the test bearing is damaged, so that it cannot operate normally, such as cage fracture, loose sleeve, sealing element deformation, and cannot play the role of sealing, etc. 2. Tester start, stop and loading procedures (1) Grease lubrication. After start the tester, operate it for 0.5 h without load first, and then gradually load to the specified value during the 3 h operation and closely observe the temperature rise. (2) Oil lubrication. When the test bearing has no axial load, start the oil pump motor first, then start the main motor, and finally slowly increase the load to the specified value; when stopping, unload first, stop the main motor, and finally stop the oil pump. When the test bearing bears axial load and combined load, start the oil pump motor first, then apply a small amount of axial load (1/3–1/2 of the specified value), start the main motor, apply the axial load to the specified value, and finally apply the radial load to the specified value; when stopping, proceed in reverse order. 3. Test detection The load, speed, oil pressure, vibration, noise and temperature rise shall be monitored and controlled at any time during continuous operation of the tester. According to the relevant standards and requirements, the temperature shall be recorded every 2 h, as the basis of the test pass time. When the time is less than 2 h, it shall be recorded directly on the corresponding table.

6.2.2.4

Test Result Analysis and Test Report

(1) Failed products caused by improper test load, abnormal rotation speed, lack of oil supply and burn jam shall not be included in the normal failure data. (2) Failure analysis may be made on typical failed products according to relevant regulations if required. (3) It is advisable to keep three significant digits when recording the original test data (the total time the test passed). (4) Process the test data according to relevant standards and issue an inspection report. If necessary, attach a diagram of the estimated results, indicating the corresponding values of the distribution parameters.

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6.2.3 Tribological Test Characteristics of Parts and Components Tribology is a discipline that studies the basic theory and practice (including design and calculation, lubricating materials and lubrication methods, friction materials and surface states, friction fault diagnosis, monitoring and prediction) of friction, lubrication and wear between interacting surfaces in relative motion. One third to one half of the energy used in the world is consumed by friction. Tribology studies a wide range of objects, mainly including ➀ Dynamic and static friction pairs, such as sliding bearing, gear drive, threaded connection, electrical contact and tape-recording heads ➁ Working medium friction or collision and impact on the parts surface, such as plowshare and turbine runner; ➂ Tribological problems in mechanical manufacturing processes, such as metal forming, cutting and superfinishing; ➃ Elastomer friction pair, such as friction between the auto tyre and the road surface, the dynamic leakage of the elastomer seal; ➄ Tribological problems under special driving cycles in mechanical engineering. In addition, there are a lot of tribological problems in music, sports and people’s daily lives. Tribology involves many disciplines. For the oil-lubricated metal friction pair, the bearing oil film of the sliding bearing in the state of complete fluid lubrication can be basically solved by using the theory of fluid mechanics. However, for point and line contact friction pairs such as gear drive and rolling bearing, the impact of contact deformation and the lubricating oil viscosity changes under high pressure shall also be considered in calculation of the bearing oil film in hydrodynamic lubrication; in the calculation of frictional resistance, it is necessary to seriously consider the rheological properties of oil (the physical properties of material deformation and flow in terms of stress, strain, temperature and time), and even consider the effect of instantaneous change process, rather than reducing it to a Newtonian fluid. In this way, only in terms of oil-lubricated metal friction pairs, it is necessary to study lubrication mechanics, elastic and plastic contact, rheological properties of lubricants, surface morphology, heat transfer and thermodynamics, tribochemistry and metal physics, involving physics, chemistry, materials, mechanical engineering and lubrication engineering. With the development of science and technology, the theory and application of tribology will be transformed from macro to micro, from static to dynamic, from qualitative to quantitative, and become a field of systematic and comprehensive research. The main components considered here are the gears and bearings in the transmission. If the power loss of friction is reduced as much as possible during the highspeed operation of the transmission, the efficiency of the transmission will be greatly improved. Therefore, it is of great significance to study the friction characteristics of gear and bearing.

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Introduction to Test Instruments

1. Four-Ball tester As shown in Fig. 6.6, the four-ball tester uses sliding friction to evaluate the bearing capacity of the lubricant under extremely high point contact pressure, including the maximum non-seizure load PB, sintering load PD, and comprehensive wear value ZMZ. (1) Maximum non-seizure load PB (represents oil film strength): Maximum load at which the seizure does not occur between the upper and lower balls under specified test conditions. (2) Sintering load PD: The lowest load level to make the ball sintered, which represents the ultimate working capacity of lubricant. (3) Comprehensive wear value ZMZ: also known as comprehensive wear index, average Hertz load, load-wear index, etc., it is an index to characterize the extreme pressure resistance of lubricants. It is equal to the digital average of several calibration loads. The greater the ZMZ value, the better the wear resistance of the lubricant is. It has a strong ability to distinguish extreme pressure additives. 2. UMT-2 universal micro-tri-botester As shown in Fig. 6.7, the UMT-2 universal micro-tri-botester is widely applied in friction wear and material research. It can be used to carry out standard test (four-ball test), a variety of conventional tribological tests (ball disk test, pin disk test, diskdisk test) to simultaneously get the friction force, load, torque, friction coefficient, horizontal displacement, vertical displacement, high-frequency acoustic signal and other measurement data.

Performance indexes Axial test force:40N~10kN (stepless adjustable) Loading control mode: manual loading (hydraulic) Spindle speed range: 200~2000r/min Sample heating range: room temperature ~75℃ Friction measuring range: 1~300N Precision of steel ball for test: G10 Diameter of steel ball for test: 12.7mm

Fig. 6.6 Four-ball tester

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Leading indexes Loading range: 0.1mN(0.01g)~120N(12kg) Pairing mode: four-ball type, reciprocating, ball disk type, pin disk type, disk-disk type Spindle speed: 0.001~5000r/min

Fig. 6.7 UMT-2 universal micro-tri-botester

3. High-Speed loop block tribotester As shown in Fig. 6.8, the high-speed loop block tribotester (MR-H5 II tester) is mainly used for evaluating the lubrication performance of all kinds of lubricating oils and greases, especially for evaluating the abrasion resistance of middle and highgrade automobile gear oils, as well as for evaluating the lubrication performance of solid lubricating materials, testing the wear performance of all kinds of metal and non-metal materials, and measuring the friction force and friction coefficient of all kinds of materials. 4. UMT-3 controlled environmental tribotester As shown in Fig. 6.9, the UMT-3 controlled environmental tribotester can be effectively used to test the friction properties of metals, plastics, ceramics, paper products,

Main technical specifications and parameters Maximum test force: 5000N Spindle speed range: 10~3500r/min infinitely variable (Maximum linear speed in the contact area: 9m/s) Maximum friction force 1000N Heater temperature range: room temperature~100 ℃ (Accuracy: ±0.2℃) Test force accuracy: The relative error of the indicated value is not more than ±1% Repeatability error not more than ±1%; Reference standard: China GB/T12444-2006; US ASTM G77-1998

Fig. 6.8 High-speed loop block tribotester

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Manufacturer:CETR (Center of tribology), US Loading range: 1 mN~1000N Vertical positioning: maximum stroke 150mm and position resolution 1μm Lateral displacement: maximum stroke 75mm and position resolution 2μm Spindle speed: 0.001~5000r/min Pairing mode: four-ball type, reciprocating, ball disk type, pin disk type, disk-disk type Add-on modules: The humidity and temperature control module is installed to adjust the test environment, and the maximum heating temperature can reach 1000℃. The electrochemical module is also installed to obtain the polarization curve during the friction process.

Fig. 6.9 Controlled environmental tribotester

composites and coatings, as well as solid lubricants, lubricants, lubricating oils and greases. 5. Optimal SRV-4 high temperature tribotester As shown in Fig. 6.10, the optimal SRV-4 high temperature tribotester is a tribotester used widely and a device that evaluates the performance of lubricating oils and additives. It is mainly used for testing the friction and wear performance of the materials at room temperature or high temperature, lubrication or dry friction. It can also be used to evaluate the bearing capacity and the high temperature anti-friction performance of the lubricating medium. 6. Universal tribotester (Plint TE92) As shown in Fig. 6.11, TE92 microprocessor controlled rotary universal tribotester is a floor type friction tester that consists of the servo controlled low inertia pneumatic loading system with force sensor feedback, vector controlled speed motor with code feedback, electromagnetic clutch quick start system, control and data acquisition software with SUPERSLIM series interface. The TE92 tester can simulate different friction forms and be used at a variety of temperatures, speeds and pressures. Its test results are well correlated to the real driving cycles. The TE92 tester is a universal test instrument for research and development of new materials and lubricants. With collinear rotation and loading shaft, the tester provides an open test platform for many types of tribological tests, many of which comply with relevant international standards. 7. Surface morphology measurement system (Talysurf PGI 1230) As shown in Fig. 6.12, the surface morphology measurement system is an instrument used to measure the surface morphology of objects. It can measure more than 90

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Technical indexes of SRV-4 Friction forms: oscillating friction and rolling friction Load: 1~2000N and 0.5~200N Frequency: 1~511Hz and 0.01~511Hz Stroke: 0.01~5mm Temperature: Standard range: room temperature ~350℃ High temperature range: room temperature ~1000℃ Time: 1min~999h Speed: 0~2000r/min Rotational test radius: 0~42mm Measurable data: friction coefficient, load, stroke, temperature, torque and speed Contact mode: point, line, surface, needle and disk, disk and disk, ball and disk, block and disk

Fig. 6.10 SRV-4 high temperature tribotester

Load range: 20~10000N Rotational speed: 30~3000r/min Torque 7N·m(3000r/min)~21N·m(30~1500r/min) Motor: 2.2kW AC (1500r/min), 50% overload up to 30s Heating block power: 550W Temperature sensor: K-type thermocouple Vibration sensor: piezoelectric ceramic type, adjustable threshold sensitivity and cut-off time

Fig. 6.11 Universal tribotester

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Performance indexes Minimum vertical resolution: 0.8nm Basic error: 5% Dynamic measurement range: 12.5mm Probe stroke: 200mm (horizontal direction)

Fig. 6.12 Surface morphology measurement system

parameters of two-dimensional and three-dimensional surface morphology, such as surface roughness and waviness, and can be expanded at any time according to user requirements. 8. Knoop/Vickers Automated Hardness Tester As shown in Fig. 6.13, the micro hardness tester is mainly used for small and thin, crisp and hard specimens. With various attachments or various structure updates, it can be widely used in various kinds of metal (ferrous metal, nonferrous metal, casting, metal materials, etc.), metal structures, metal surface processed layers, electroplated layers, hardened layers (oxide layer, all kinds of diffusion layers, coatings), heat treated specimens, carbonized specimens, quenched specimens, a tiny fraction of the phase inclusion points, glass, agate, artificial stones, ceramics and other crisp and hard non-metallic materials, and can be used for multi-point measurement of precision positioning in small parts, deep indentation test and analysis, composite alloying layer test and analysis, hardness gradient test, metallographic structure observation and research, coating thickness measurement and analysis, etc.

6.2.3.2

Application of Tribology in Gears

The research results of tribology have achieved great economic and social benefits in improving the operation reliability of mechanical equipment, prolonging the service life, reducing accidents and saving energy and raw materials. According to the estimation in Britain, the total annual savings to the British civil economy are more than 500 million pounds depending on the improvement measures in tribology research. The American Society of Mechanical Engineers estimates that the United States

412

6 Vehicle Powertrain Reliability Test Technology Main parameters Sample table size: 180mm×180mm Maximum test height: 83mm(3.1in) Hardness scale: Knoop/Vickers Load range: 10gf~1kgf Force precision: ±1.5%(200g) Test force loading: Automatic closed-loop sensor Hold time: 1~999s Meet standards: ASTME384, ASTME92, ISO6507, ISO9385, ISO4546

Fig. 6.13 Knoop/Vickers automated hardness tester

spent 24 million dollars on tribology research and development in 1976 and saved about 11% of energy throughout the year, about 16 billion dollars. The “industrial gear oil application technology research” project completed by China in the mid1980s is estimated to save 1.3 billion yuan per year if the research results are widely applied. The gear drive is an important part widely used in mechanical equipment. With the rapid development of industrial production today, the volume of industrial gear device is getting smaller and smaller, the power is getting larger and larger, the driving cycle is getting more and more harsh, so the gear lubrication has become one of the key technologies of gear drive. The advanced industrial countries in the world attach great importance to the research and application of tribology and fully realize the importance of gear lubrication. Specific industrial applications of gear tribology include gear friction, wear and lubrication. 1. Theoretical research on gear tribology The theoretical research of gear tribology focuses on gear elastohydrodynamic lubrication (EHL), gear surface morphology and micro-tribology. Tsinghua University, Shanghai Jiao Tong University, Wuhan Institute of Technology, Harbin Institute of Technology and so on have completed the study on EHL elastic flow numerical solution and oil film thickness test. Tsinghua University carried out “Research on Film Lubrication Theory”. Chongqing Logistics Engineering University carried out

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“Experimental Research on Tribological Surface Treatment”. Wuhan Research Institute of Materials Protection carried out the “Tribological Test and Friction Surface Analysis of Steel-steel Friction Pair under Self-compensating Oil Lubrication”. Lanzhou Institute of Chemical Physics, Chinese Academy of Sciences carried out the “Experimental Study on Synergistic Effect of Extreme Pressure Anti-wear and Antifriction Additives in Lubricating Oil”. Beijing Academy of Machinery Science and Technology carried out “Experimental Study on Linear Contact Elastohydrodynamic Film Thickness with Moderate Elastic Modulus”. 2. Research methods and gear test technology Since the 1980s, Sinopec and the Ministry of Machine-Building Industry have jointly organized the relevant units to successfully develop gear oil and worm gear oil bench evaluation device and test methods. Zhengzhou Research Institute of Mechanical Engineering has successively completed “Experimental Research on the Gluing Bearing Capacity of Hardened Face Gear and Medium Hardened Face Gear”, “Study on the Influence of High-speed Lubricating oil Additives on the Bearing Capacity, Vibration and Noise” and “Study on the Influence of Lubricating Oil and Additives on the Gear Bearing Capacity, Worm Gear Pair Bearing Capacity and Transmission Efficiency”. Tsinghua University has carried out the “Experimental Research on Friction and Wear Characteristics of Copper Steel Friction Pairs”. Dalian Railway University has carried out “Experimental Study on the Gear Gluing Strength Optimization Design Calculation, Optional Parameter Path and Gluing Critical Temperature Reliability”. East China University of Science and Technology, Tsinghua University and China University of Mining and Technology have studied the “Effect of Lubrication Mode on Wear Performance of Low-speed and Heavy-duty Gears”. 3. Research on gear tribology design method The gear with appropriate strength, adequate wear resistance and gluing resistance must be used for design. For this reason, designers shall consider the gear tribology design in terms of three elements of performance: material surface, ambient conditions and lubricants. The gear drive shall be considered as a complete system in the design. Both the influence of individual factors, the mutual influence between the factors and the influence on the whole system shall also be considered. Chongqing University has carried out the “Theory and Application Research on Tribological Design of Large Worm Reducer”. Zhengzhou Research Institute of Mechanical Engineering has preliminarily studied the tribology design elements, design criteria and design methods of the gear drive. 4. Development trend of gear tribology technology in China (1) Nanotribology Nanotribology is to study friction, wear and lubrication at the atomic and molecular scales. Nanotribology technology is especially needed in micromechanics.

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(2) Development trend of gear lubricants The development trend of vehicle gear oil is to develop lubricating oil with the same life as lubricating parts and to develop high-temperature and high-load lubricating oil and multistage lubricating oil. The industrial gear oil develops towards the energy saving gear oil, synthetic gear oil and environmental protection. With the increase of the additive level, appropriate reduction of oil viscosity is also the goal of industrial gear oil application under the premise of ensuring effective and reliable lubrication. The modern design method of gear tribology is the development direction of gearbox design, and the establishment of a systematic and complete tribology database is the premise of establishing the modern design method. Strengthening the promotion and application of gear drive oil monitoring technology and fault diagnosis technology will achieve the economic and social benefits brought by the safe, reliable and efficient operation of mechanical equipment and the full use of lubricating oil potential. (3) Suggestions on the development of gear tribology application technology in China Carry out research on gear tribology and improve our gear lubrication technology level. The industrial gear drive often plays a vital role in the production line, or single key equipment. The modern gearbox has increased transmitted power, decreased volume and harsh working environment, so higher requirements are put forward for the gear drive performance. In order to design and manufacture high-parameter and high-performance gearbox, it is necessary to adopt advanced design and manufacture technology as much as possible. The calculation of friction force in elastohydrodynamic contact area under lubricant condition and the simulation of gluing under mixed lubrication condition have been studied abroad. We should give full play to the advantages of universities and institutes to carry out the research on the common basic technology of gear tribology, especially pay attention to the industry cooperation with the relevant departments of petrochemical industry, promote the further improvement of the performance of gear oil, and combine with engineering application to transform scientific research achievements into productivity. Carrying out research on gear tribology, making use of the technology achievements of emerging interdisciplines, and integrating with other aspects of gear technology will greatly improve the independent development ability of the lubricants of the gear products in China, and enhance the ability to participate in the international market competition.

6.2.3.3

Application of Tribology in Rolling Bearings

Friction and wear is an extremely complex behavior occurring on the contact interface, which is affected by many factors such as working parameters, environmental conditions, friction pair material and lubrication technology. There are complex coupling and interaction among the factors, and the friction and wear process is irreversible and dissipative. Therefore, tribology is characterized by complexity, systematicness and discipline synthesis.

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At present, the tribology research can be divided into seven directions: material friction and wear, lubrication theory and application, biological and bionic tribology, micro-nano tribology, surface engineering tribology, industrial tribology and design tribology. As an important basic part, the rolling bearing is closely related to the above tribology sectors, such as bearing design (design tribology), friction and wear of bearing materials, bearing lubrication, bearing ring surface treatment (surface engineering tribology) and bearing application (industrial tribology). It can be seen that the development of rolling bearings is inseparable from tribology. As an important basic part, the rolling bearing is widely used in various industrial fields. There are more friction pairs in rolling bearings, such as the friction between the rolling body and the inner and outer ring raceway surface, the friction between the rolling body and the cage pocket, the friction between the lubricant and the rolling body, the friction between the lubricant and the inner and outer ring raceway surface, and even the friction on the seal ring. According to the mechanism of friction, the rolling bearing friction can be divided into pure rolling friction, sliding friction (differential motion on the rolling contact surface, spin and other sliding friction, sliding friction in the sliding contact part, including sliding friction between rolling body and cage pocket, sliding friction between roller end face and ring guard, sliding friction between the seal and ring in the sealed bearing, etc.), and viscous block friction of lubricants. Compared with the current tribology research, the application of the tribology in rolling bearing is discussed in 4 aspects: friction and wear of rolling bearing materials (corresponding to the direction of material friction and wear), rolling bearing design (corresponding to the design tribology direction), rolling bearing surface treatment (corresponding to the surface engineering ribology direction) and rolling bearing lubrication (corresponding to lubrication theory and application). 1. Friction and wear of materials The life of rolling bearings is largely affected by the performance of bearing materials, especially in harsh environments. However, because of many friction pairs of rolling bearings, friction will produce wear, and the bearing will fail when wearing to a certain extent. Wear failure is one of the main forms of rolling bearing failure. Domestic scholars have studied the wear properties of Cr4Mo4V, and believed that the surface cracks will be caused by the adhesive wear and fatigue wear pits; some scholars have made tribological analysis on white corrosion crack (WEC) failure of rolling bearings, and believed that WEC failure is the product of microbalance among the friction material, friction machinery and tribochemistry. Therefore, it is one of the methods to effectively extend the life of rolling bearings to study the friction and wear of bearing materials, explore the wear mechanism of bearing materials, and seek to reduce the wear of rolling bearings from the perspective of materials. 2. Structural design The wide application of rolling bearings, especially under harsh conditions, puts forward higher requirements for the design of rolling bearings. Rolling bearings are designed to meet the requirements of application conditions, such as high-speed

416

6 Vehicle Powertrain Reliability Test Technology

High tightness

Low friction coefficient

Optimal design of sealed end in contact with the

Reduce the applied force on the

inner ring

sealed end and inner ring

Fig. 6.14 NSK new bearing seal structure

angular contact ball bearings developed by SKF. In order to meet the requirements of high speed (d m × n = 1.05 × 106 mm · r/min), the bearing design is changed as follows: Change the profile of the raceway surface, the contact angle and the cage pocket morphology and finally reduce the sliding between the ball and the raceway surface, the cage pocket force, and the friction between the cage and the ball and develop the high-performance bearing that meets the requirements. The highperformance and low-friction seal structure developed by NSK Company through bearing seal design is shown in Fig. 6.14. The design of rolling bearings minimizes the friction effect of the friction pairs while meeting customer requirements. Thus, the application of tribology is helpful to improve the design of rolling bearings. 3. Surface treatment The in-depth statistical analysis of rolling bearing failure shows that the failure often occurs on the surface and subsurface of the ring or rolling body. In the context of saving energy and reducing pollution worldwide, the surface treatment technology of rolling bearings develops rapidly, which is the future development trend. No matter the traditional surface treatment technology, such as carburizing, nitriding, PVD and CVD, or the emerging surface treatment technology, such as ion implantation, laser surface modification, ultrasonic surface modification, etc., all need performance evaluation, namely wear resistance test, which must be achieved by friction tests. N ion implantation has an important effect on the surface wear of 9Cr18, and metal ion implantation has an important effect on the wear performance of Cr4Mo4V. The comparison results of surface friction coefficients of 9Cr18 under different N ion treatments are shown in Fig. 6.15. The surface treatment with natural antioxidants significantly reduces the wear extent of the bearing surface, as shown in Fig. 6.16. The tribological characteristics of the surface treated layer can be studied to master the performance and damage mechanism of the modified layer, so as to improve the surface treatment technology and improve the bearing performance and life. Therefore, tribology is widely used in surface treatment technology of rolling bearings.

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417

No surface treatment Friction coefficient

Treatment for 1h Treatment for 4h Treatment for 8h

Test time/min

Wear extent (×10-11m³)

Fig. 6.15 Comparison of surface friction coefficients of 9Cr18 under different N ion treatments

G1: 9% soap base, v=100mm2/s G2: 12% soap base,v=124mm²/s G3: 8.7% soap base,v=531mm²/s, added EP B01:v=100 mm2/s B02:v=124 mm2/s B03:v=531 mm2/s

Number of cycles (×106)

Fig. 6.16 Comparison of bearing surface wear extent after treatment with different natural antioxidants

4. Lubrication The excellent performance of rolling bearings is inseparable from lubrication. Rolling bearing failure is largely caused by the lubrication failure, that is, the change of lubrication state (lubricant contamination and change of lubricating oil film thickness). Generally speaking, the rolling bearing is well lubricated, and the lubricating film can completely isolate the rolling body from the ring, so that it is in the elastohydrodynamic lubrication state; However, in the actual operation process of the bearing, the rolling bearing is often in a mixed lubrication state, and is even in a dry friction state when the lubrication fails, which is related to the change of the oil film thickness in the lubrication theory of the rolling bearing.

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6 Vehicle Powertrain Reliability Test Technology

In addition, the application environment of rolling bearings is diverse, and no specific lubricant can satisfy the lubrication state of all rolling bearings. Therefore, the rolling bearing lubrication also includes lubricant development and application. NTN adds inhibitors to the lubricant to form an oxide film to inhibit H from entering the steel substrate, which increases the bearing life by about 4 times. The study on the influence of oil chemical composition on the rolling contact fatigue shows that increasing the content of soap in the thickening agent can increase the oil film thickness and reduce the contact wear. It can be seen that the lubrication theory in tribology is closely related to the rolling bearing lubrication, and tribology is helpful to select appropriate lubricants for actual driving cycles.

6.2.3.4

Prospects of Application of Tribology in Rolling Bearings

The world-famous bearing enterprises pay more attention to the application of tribology in rolling bearings and carry out related research extensively. In 2012, SKF invested 180 million Euros in research and development, and many important innovations are the result of tribology, such as SKF energy efficient bearings, permanent wear-proof coatings, ceramic bearings, copper and polymer cages, ultra-clean bearings for special applications, surface crazing, grease and lubricant specifications and low friction seals. Schaeffler has always attached great importance to tribology and has developed tribology standards for bearings. NSK takes tribology knowledge as one of the four core technologies (tribology technology, analytical technology, material technology and mechatronics technology). NTN takes tribology as the basis of all its technologies and extends the application accordingly. Its technology tree is shown in Fig. 6.17. JTEKT innovates through material development and processing technology based on tribology. NMB, which produces the world’s smallest ball bearing (OD 1.5 mm only), believes that the friction (lubrication) technology is essential to reduce friction and wear. Nearly half a century of accumulated lubrication technology ensures that the lubrication design is based on the product application. It can be seen that the famous bearing enterprises pay more attention to tribology and its application in rolling bearings. Domestic bearing enterprises pay less attention to the application of tribology in rolling bearings. Most domestic tribology researchers are not engaged in bearing related work, while few bearing practitioners have a systematic understanding of tribology knowledge. This situation is completely opposite to the development of tribology in foreign countries. In terms of the application of tribology in rolling bearings, there is a big gap between Chinese bearing enterprises and foreign bearing enterprises, which may be one of the reasons why the quality of Chinese high-end bearing products is not as good as that of foreign bearing enterprises. Therefore, how to effectively apply tribology to rolling bearings, improve the friction loss of rolling bearings (low friction, low energy consumption) and improve the performance and life of rolling bearings, is one of the directions of bearing development in the future.

6.2 Test Technology for Powertrain Components

419

Create new energy protection technologies for the future global environment Wind turbine

All cars

Space rocket and artificial satellite

Long life (high

Very high

reliability)

speed

Building machinery

Electric vehicle

Automobile

Aircraft

Medical equipment Lighter and

Low friction

more

(low torque)

Provide customers with strong support through basic technology, design and development, product technology, assembly technology and intellectual property rights

Precision assembly

Machine tool

Tribology

Fig. 6.17 NTN technology tree

At present, the development of rolling bearings tends to high reliability, long life, energy consumption and reduction of environmental pollution. The use of tribology knowledge can reduce the friction of the rolling bearing friction pairs, improve the rolling bearing material, rolling bearing design and bearing surface treatment technology, improve the lubrication state of rolling bearings, improve the bearing performance, and then extend the rolling bearing life. Therefore, the following suggestions are put forward on the application of tribology in rolling bearings: (1) Antifriction and wear resistance design of rolling bearings. Use the tribology knowledge to optimize bearing design and improve the friction state of friction pairs in rolling bearings. (2) Research and development of rolling bearing lubricants and research on lubrication theory. There are many types of rolling bearings and different application environments. Based on the basic research of lubrication theory, the optimal lubrication mode of corresponding bearings is explored and lubricants with excellent performance are developed, so as to improve bearing performance and improve bearing life. (3) Research and development of self-lubricating bearing materials. The development of rolling bearings is inseparable from the development of bearing materials. However, in harsh environments (such as aerospace), the traditional lubrication method is no longer suitable, and novel lubrication methods (such as self-lubrication) are more important. At present, the self-lubrication of bearings is mainly realized by solid lubrication on the bearing surface or cage immersion

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Table 6.7 Motor driving cycles Condition 1 (640 cycles in total) Settings

Operating voltage: rated voltage (336 V) Operating speed: ns = 1.1 × rated speed Run time: 320 h Driving cycle: Cycle as shown in Fig. 6.18

2 (80 cycles in total)

3 (80 cycles in total)

4 (continuous operation for 2 h)

Operating voltage: maximum voltage (410 V) Operating speed: ns = 1.1 × rated speed Run time: 40 h Driving cycle: Cycle as shown in Fig. 6.18

Operating voltage: minimum voltage (240 V) Operating speed: ns = (minimum voltage/rated voltage) × rated speed Run time: 40 h Driving cycle: Cycle as shown in Fig. 6.18

Operating voltage: rated voltage (336 V) Operating speed: ns = maximum speed Run time:2 h Driving cycle: continuous operation

in the oil. It is one of the effective ways to develop self-lubricating materials for bearings with superior performance. (4) Research on surface engineering technology of rolling bearings. At present, bearing surface engineering technology is one of the hot spots of bearing life extension. The systematic research on the rolling bearing surface engineering technology, such as ion implantation, surface modification (spraying, ultrasonic machining), can expand the application range of rolling bearings in harsh environment and improve the rolling bearing life.

6.3 Motor Reliability and Endurance Test Specification 6.3.1 Reliability Test Specification The motor reliability test is carried out in accordance with GB/T 29,307–2012. The driving cycles and number of cycles of the motor are summarized in Tables 6.7, 6.8 and Fig. 6.18.

6.3.2 Endurance Test Specification Before the high temperature endurance test of the drive motor, run the drive motor first to make the winding temperature reach (150 ± 5) °C under a certain driving cycle. During the test, the coolant temperature is the maximum allowable temperature of the system, and the flow rate and coolant composition meet the vehicle requirements.

6.3 Motor Reliability and Endurance Test Specification

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Table 6.8 Cycle run time of motor reliability test No.

Load torque

Run time/min

1

Continuous torque TN (t1 )

22

2

TN in transition to TPP (t2 )

0.5

3

Peak torque TPP (t3 )

0.5

4

Tpp in transition to −TN (t4 )

1

5

Continuous feedback torque −TN (t5 )

5

6

−TN in transition to TN (t6 )

1

Cumulative time of a single cycle

30

Revolving speed

Torque

Peak torque Rated torque

Rated feedback torque

Time/min

Fig. 6.18 Schematic diagram of motor reliability test cycle conditions

The drive motor shall be operated in cycle shown in Fig. 6.19, and the total run time is 750 h. During the test, the winding temperature of the drive motor shall be maintained at (150 ± 5) °C. The motor can be maintained at the required temperature by adjusting the driving cycle. During the test, it is allowed to stop every 100 h to maintain the test bench, but the maintenance start and stop time and maintenance content shall be recorded. In the high-speed endurance test of the drive motor, the drive motor changes by a certain multiple based on the rated torque and rated speed data. For specific driving cycles, refer to Fig. 6.20. The drive motor runs 350 h in a cycle. The coolant temperature of the drive motor is the maximum allowable temperature, and the flow rate and coolant composition meet the vehicle requirements. During the test, it is allowed to stop every 100 h to maintain the test bench, but the maintenance start and stop time and maintenance content shall be recorded.

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6 Vehicle Powertrain Reliability Test Technology Instruction speed

Motor torque/(N•m)

Motor speed/(r/min)

Instruction torque

Fig. 6.19 High temperature endurance test cycle conditions

Torque multiple Torque multiple

Speed multiple

Speed multiple

Time/min Fig. 6.20 High speed endurance test cycle condition

Bibliography Abersek B, Flasker J (1998) Experimental analysis of propagation of fatigue crack on gears. Experimental Mechan 38(3) China Automotive Technology & Research Center (2016) Technical specification for reduction gearbox of battery electric passenger cars: QC/T1022–2015. China Plan Press, Beijing Chongqing Tsingshan Industry Co., Ltd., Chongqing Changan Automobile Co., Ltd., China Automotive Technology & Research Center, etc (2019) Specification & bench test methods for manual transmission assembly: QC/T568--2019. Beijing Science and Technology Publishing Co., Ltd., Beijing Guo Y, Wei B, Li Z et al (2020) Bending fatigue life simulation and acceleration test of a spiral bevel gear. J Henan Univ Sci Technol (Nat Sci) 41(5):13–17,25 Hu S, Bai Q, Zheng W et al (2019) Development and test of an energy saving gear oil for drive axle. Auto Sci-Tech 04:10–14 Li M, Xie LY, Ding LJ (2017) Load sharing analysis and reliability prediction for planetary gear train of helicopter. Mech Mach Theory 115 Li W, Deng S, Liu BS (2020) Experimental study on the influence of different carburized layer depth on gear contact fatigue strength. Eng Failure Analy 107 Liu G, Bian W, Huang F et al (2019) Loader transmission overrun clutch reliability test bench. Constr Machin Mainten 5:32–33

Bibliography

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Tian Y, Ruan J, Zhang N et al (2018) Modelling and control of a novel two-speed transmission for electric vehicles. Mechan Machine Theory 127:13–32 Wang ML, Liu XT, Wang YS et al (2016a) Research on assembly tolerance allocation and quality control based on fuzzy reliability. Proc Instit Mech Eng Part C: J Mechan Eng Sci 230(20):3755– 3766 Wang XL, Liu XB, Wang YS et al (2016b) Reliability analysis on the drive system of a gear-type oil pump with variable displacement. Adv Mech Eng 8(3) Yang QJ (1996) Fatigue test and reliability design of gears. Int J Fatigue 18(3) Yu Z (2009) Automobile theory, 5 edn. China Machine Press, Beijing Zhang X (2018) Research on reliability test system for gearbox of high-speed train based on vibration excitation. Jilin University, Changchun Zhao R, Du B, Zhang P (2020) Research on fault analysis method of high pressure oil pump reliability test based on deep learning. Internal Combust Engines (1):17–21, 26 Zhou Q, Guo P, Li N et al (2018) Research on reliability test method and failure analysis for automobile drive axle. Automobile Parts 06:80–82 Zhu M, Zhaojy, Wang QM (2017) Reliability evaluation of key hydraulic components for actuators of FAST based on small sample test. Int J Precis Eng Manuf 18 (11)

Chapter 7

New Energy Vehicle Hardware-In-The-Loop Test Technology

Following the V-mode development process, the hardware-in-the-loop (HiL) test is indispensable for the development and verification of control policy software. The HiL test helps identify and solve problems early in development because it combines safety, feasibility and cost rationality. Therefore, it has long been a very important part of the ECU development process. In the development of hybrid electric vehicle control units, the HiL test mainly includes the test and verification of the three core electric control systems—hybrid control unit (HCU), battery management system (BMS) and motor control unit (MCU). The rational use of HiL test can not only make up for the low credibility and reliability of pure simulation verification, but also reduce the number of real vehicle road tests, so as to shorten the development time, reduce the cost and improve the software quality of the control algorithm.

7.1 HiL Test Platform Architecture of Extended-Range Electric Logistics Vehicle HCU Figure 7.1 shows the HiL test platform architecture built for the control algorithm software verification of extended-range electric logistics vehicle HCU. The platform is mainly composed of a vehicle HCU and NI real-time simulator. The vehicle HCU uses D2P development control unit in which the control algorithm code has been written, and is connected to NI real-time simulator through CAN channel. The driver model is written into the driver operating platform and displayed on the upper computer, and the driver’s operation control signal is input through the external actual simulator and I/O interface. The vehicle dynamical model runs in NI realtime simulator, and the I/O interface between the upper computer driver operating platform and NI real-time simulator is set up in the model, which can realize system communication and coordinated operation. Aiming at the problem that the platform is difficult to diagnose faults, a real-time data detection platform is developed based on © Huazhong University of Science and Technology Press and Springer Nature Singapore Pte Ltd. 2023 Y. Chen, New Energy Vehicle Powertrain Technologies and Applications, Key Technologies on New Energy Vehicles, https://doi.org/10.1007/978-981-19-9566-8_7

425

426

7 New Energy Vehicle Hardware-In-The-Loop Test Technology GUI scenario building interface (analog radar)

Optical camera obscura: scenario model + real camera

Upper computer

Driving simulator

Pedal and steering wheel angle signal

CAN or Ethernet

Camera collects scenario information

CAN or

CAN or

Ethernet

Ethernet

Distance, velocity, RCS, etc.

CAN or Ethernet

Vehicle dynamic model Object under test: ADAS control Real-time system

Fig. 7.1 Schematic diagram of HiL test bench architecture

CAN communication, which realizes the fault handling policy of the vehicle for the motor, control unit, battery and auxiliary system, is conducive to timely finding and improving the problems in the test and improving the efficiency of control policy development, and improves the HiL test platform for the HCU control algorithm verification of the whole vehicle.

7.1.1 HiL Test Hardware Platform Building The HiL test hardware platform for extended-range electric logistics vehicle HCU control policy verification mainly includes NI real-time simulator and vehicle HCU D2P control unit. The real-time simulator used to carry the vehicle dynamical model adopts NI real-time simulator, as shown in Fig. 7.2. The NI real-time simulator consists of the real-time processor card PXIe-8135RT, CAN communication board PXI 8513/2, analog output board PXI 6723, multifunctional RIO board PXI 7853R, fault injection board PXI 5210 and analog resistance board PXI 2722. The whole vehicle HCU adopts D2PECM-5554-112-0904-XD (DEV) development control unit. The control unit downloads the compiled program code of vehicle control and energy management optimization strategy through CAN1 channel. The analog input signal of the control unit is sent by the vehicle model through the analog output board PXI6723 in the NI real-time simulator. In addition, the control unit is connected to the CAN communication board PXI8512-1-CAN2 of the NI real-time

7.1 HiL Test Platform Architecture of Extended-Range Electric Logistics …

427

Fig. 7.2 Physical picture of NI real-time simulator

simulator through the CAN3 channel and sends and receives signals with the vehicle model in the real-time simulation process.

7.1.2 HiL Test Software Platform Building The HiL test software platform for HCU control policy verification mainly includes human–computer interaction display platform, dynamic model and communication system. The human–computer interaction display platform adopts NIVeriStand operating environment to establish a user virtual instrument, as shown in Fig. 7.3. Driver control signals can be input and relevant variables and parameters can be monitored in real time. The above compiled model can run only after generating the project file (.dll), importing the NIVeriStand operating environment, adding and configuring the hardware equipment and completing the signal pairing. During the test, the IP address of the host computer and the IP address of the real-time simulator work in the same network segment to achieve communication.

7.1.3 CAN Communication Diagnostic System Model Based on LabVIEW In the actual test process after building the HiL test platform, it is found that, due to the complexity of the vehicle system, it usually takes a lot of time to troubleshoot the abnormal test results if any. Therefore, a CAN communication diagnostic system

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7 New Energy Vehicle Hardware-In-The-Loop Test Technology

Fig. 7.3 HiL test human–computer interaction display platform interface

model based on LabVIEW is developed on the HiL test platform. The model can be used to locate and analyze the system faults in time, further improve the development platform, improve the development and test efficiency of the HiL test platform of the vehicle HCU, and reduce the development cost. According to ISO15765 and ISO14229 standards, a complete diagnostic system is designed and implemented by LabVIEW software for USB high-speed CAN hardware development tools. Figure 7.4 shows the overall schematic diagram of the diagnostic system. The whole vehicle HCU will monitor whether the working process of its controlled system is normal during the normal operation of the vehicle. The diagnostic system realizes the data exchange with the help of NI USB 8473 s CAN card, and builds the functional algorithm of data analysis by NI LabVIEW software at the application

(a) FPS resolution

(b) DTC resolution

Fig. 7.4 Overall schematic diagram of diagnostic system

(c) DTC details

7.2 Energy Management HiL and MiL Test

429

layer. The diagnostic system is designed with a favorable human–computer interaction interface: Fig. 7.4a shows the parsing process of diagnostic trouble code (DTC), and the detailed list of the DTC in the controller is arranged in the window on the left; Fig. 7.4b shows the resolution process of the DTC of the diagnosis error type; Fig. 7.4c shows the details of the DTC of the diagnosis error type and the cause of the DTC fault.

7.2 Energy Management HiL and MiL Test 7.2.1 Selection of Driving Cycles Vehicles are powered by chemical energy from internal combustion engines, which are mechanically inefficient and produce harmful emissions. Large amounts of exhaust gas produced by the increased use of vehicles exacerbate the harm to people’s health. In the 1970s, California first adopted the emission regulation to push the auto industry to develop engines with higher combustion efficiency and lower emissions. The regulation requires a test procedure that can compare performance difference between different engines, which is called driving cycle (also known as operating cycle). The United States pioneered the driving cycle and promoted the research and development of the driving cycle in various countries, forming different research objectives, different research objects and different uses of driving cycles. With the deepening and improvement of the driving cycle research, the driving cycle has typical actual road driving characteristics, which can reflect the real driving cycle of the vehicle, and can be used in the vehicle research, certification and inspection/maintenance. The increase of vehicle population changes the actual driving cycles of vehicles, which need to be corrected by continuous evaluation of real road conditions. It is significant to understand and grasp the driving cycle research motivations, objects and forms, as well as the differences and development among the main driving cycles to develop driving cycles in China.

7.2.2 Types of Driving Cycles The driving cycles for vehicle emission tests worldwide can be divided into three groups: US driving cycle (USDC), New European driving cycle (NEDC) and Japanese driving cycle (JDC). Transient cycles (FTP72) represented by FTP (Federal Test Procedure) and modal driving cycles (NEDC) represented by ECE (Economic Commission of Europe) have also been adopted worldwide. In terms of use, the driving cycles can be divided into the cycles in research, certification and in-use vehicle. There are various types and uses of USDC, including three major systems for certification (FTP system), research (WVU system) and short driving cycle (I/M

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7 New Energy Vehicle Hardware-In-The-Loop Test Technology

system). Widely known driving cycles include FTP75, LA92 and load simulation condition (IM240).

7.2.2.1

Driving Cycles for Passenger Vehicles and Light Trucks

In the 1960s, exhaust from commuter cars created smoggy air in Los Angeles, USA. To improve this situation, it is necessary to reduce the vehicle exhaust emissions. After research, the speed-time curve of vehicles analyzed from a representative commuter car route was used by the US Environmental Protection Agency (EPA) in 1972 as a test procedure for certified vehicle emissions (FTP72, also known as UDS). Controlling the reduction in vehicle emissions under this procedure is considered to take into account the most stringent scenarios. FTP72 is composed of cold-state transient condition (0–505 s) and steady-state condition (506–1370 s). In 1975, 600 s hot immersion and hot-state transient condition (repeated cold-state transient condition) were added on the basis of FTP72 to form FTP75, with a duration of 2475 s, which can be used for the inspection of vehicle hot start emission. Due to the development of traffic network, many trunk lines and expressways have appeared, the high-speed run time of vehicles accounts for an increasing proportion of the travel time, and the emission characteristics of the three main pollutants of the engine have changed, so the EPA has released a revised version of FTP. Researchers have developed many cycles that can reflect the real traffic conditions more accurately, such as US06 considering road changes, SC03 operating at full load with air conditioning, etc., as supplementary conditions of FTP to form SFTP (SFTP) and applied to the emission test of models produced after 2001. In order to solve the effect of road slope on vehicle fuel consumption, HWFETMTN cycle with variable slope has been developed. In addition to the above driving cycles, there are several research results as follows. (1) LA92: Higher maximum and average speeds, less idle running time and stops/mile, and higher maximum acceleration. (2) ARB02: A study condition developed by CARB (California Air Resources Board) based on vehicle tracking, including cold start and end of the trip, to test the vehicle’s actual operation. The study results exceed FTP72 emission reductions. (3) HL07: An engine cycle developed by the EPA in collaboration with automobile manufacturers to test a range of accelerations beyond a certain speed range; most vehicles must be fully throttled under such accelerations. It is used to develop and modify existing US cycles at various speed levels. (4) Aiming at the vehicle driving cycles that are not described and covered by FTP cycle, some cycles are developed, such as REP05 (beyond RepFTP), which represents the driving cycle. REM01 (Remainder), which is developed based on the startup conditions, targets speed and acceleration and focuses on more detailed transient change effects.

7.2 Energy Management HiL and MiL Test

7.2.2.2

431

Driving Cycles for Heavy Vehicles

In recent years, the research on heavy vehicles has tended to focus on transient conditions. BAC is recommended as the operating procedure for testing the fuel economy of heavy vehicles (SAEJ1376). CBD14 is the Commercial Center Area Vehicle test cycle and part of the BAC composite test cycle, which uses 14 identical cycles to simulate the bus stop-and-run driving mode. CBD14 approximates the CBDBUS cycle, but with variable time steps. Others include the CBDTRUCK cycle for trucks and the COM-MUTER cycle for suburban commuter round-trip test. Also well known is the Urban Dynamometer Test Cycle (UDDSHDV), which simulates the operation of a heavy duty gasoline engine in an urban area with the run time of 1060 s, the idle speed of 33% and the average speed of 30.4 km/h, and is used to test the fuel evaporation emissions. New York City Cycle (NYCC) represents the running conditions of large vehicles on the city’s regional roads. They are widely used as FTP standard conditions. In order to evaluate the emission effect of buses, the West Virginia university (WVU) has developed a group of cycles containing 10 short strokes, with the idle time of 19 s, by investigating the operation and condition of hybrid electric and conventional buses on several different and admittedly busy routes in Manhattan, New York; to meet sufficient energy consumption tests, the number of short strokes was increased to 20 as NewYorkBus condition for conventional power transporters (trucks and buses). In addition, WVU also studied CSHVR, a composite driving cycle representing the road test data of heavy vehicles, typical urban composite driving cycles (urban WVUCITY, suburban WVUSUB and intercontinental WVUINTER) composed of various micro-strokes, as well as NYC-COMP and NYCTRUCK. For heavy vehicles, in addition to the conditions used for the chassis dynamometer, there are representative conditions used on the engine bench, which are described by vehicle characteristics calculated from engine speed and torque. The test cycle consists of a set of stable “transient” cycles indicated by engine speed and torque, or by both instantaneous engine speed and torque (US rules).

7.2.2.3

EDC

To study the cycle suitable for European traffic conditions, the researchers have systematically compared various existing emission test procedures (European, Japanese and American) and technologies (sampling and analysis equipment, etc.) for measurement and control, and studied the vehicle driving cycles through a variety of vehicles. The study classifies different road areas, such as urban, suburban and expressways, as well as multiple hierarchical categories of average speed and acceleration, according to the degree of road congestion or volume of traffic, and artificially develops and cascades into stable speed and acceleration segments. The EDC used to certify light vehicle emissions on the chassis dynamometer, also known as MVEG-A in Europe, has been developed as the New EDC (NEDC). In this cycle, the local cycle speed is constant, which is a steady-state condition, including urban

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7 New Energy Vehicle Hardware-In-The-Loop Test Technology

(ECE15), suburban (EUDC) or suburban low-power vehicles (EUDCL). The ECE15 is an UrbanDC consisting of four representative urban driving cycles, featuring low speed, low load and low exhaust temperature. Due to the increasing proportion of vehicles running in suburban areas, EUDC and EUDCLOW segments representing high-speed driving cycles were developed in 1992. The ECE15 added an EUDC or EUDCLOW constitutes the familiar ECE + EUDC. In the practical application of European II emission regulation before 2000, 0–40 s running was not measured in the driving cycle. In contrast, European III/IV emission regulations are stricter in controlling vehicle emissions (testing the engine cold start emissions). The emission sampling is synchronized with the operating cycle, and a complete operating cycle is adopted, which is called the New European Driving Cycle (NEDC). The cycle lasts 1220 s, with the average speed of 32.12 km/h, and the maximum acceleration of 1.06 m/S2 . The modal cycle is used for energy consumption (or emissions), and different gear shifting strategies may cause some slight difference in test results. The operating cycle adopted in the European ECER15.04 takes this difference into account for manual and automatic vehicles: The driving distance and average speed are 4.06 km and 18.7 km/h, 3.98 km and 18.4 km/h, respectively. From the analysis of the speed-time curve, it is found that the EDC has too high proportion of steady speed, uneven distribution of various driving cycles, such as short duration of the average driving cycle and long duration of urban driving cycle, and lower average acceleration value than the real value; the ECE cycle only approximates the urban center conditions in the past. In short, there are considerable limitations to this cycle. The researchers confirmed that the FTP72 cycle simulated the average traffic conditions in European cities relatively well when the EDC was deemed not to meet the requirements. NEDC is a modal cycle and does not represent the real driving cycle. Due to the need for developing new hybrid vehicles, Europe developed a set of practical driving cycles called HYZEM based on the BRITE-EURAMHYZEM project, belonging to the instantaneous cycle. HYZEM includes the urban cycle, suburban cycle and high-speed cycle. The cycle is developed based on a database of recorded real driving patterns of 89 vehicles across European urban roads and is therefore more representative of driving conditions than the standard EDC. Compared with the modal cycle, its steady speed part is much less, with the average speed of 40.4 km/h, the number of stops of 0.69 times/km, the average acceleration of 0.71 m/s2 , and the maximum acceleration of 1.3 m/s2 .

7.2.2.4

JDC

Similar to the EDC, the JDC is also modal. Before 1976, Japan had been using 10mode to simulate the city driving cycles, repeating 6 cycles and sampling the last 5 cycles, called hot start. For the models produced after 1976, 11mode was adopted, that is, repeating 4 cycles from cold start and sampling the whole process, with the driving distance and average speed of 4.08 km and 30.6 km/h, respectively. In

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November 1991, J10.15 was adopted in Japan, which consisted of 4 10modes and 1 15mode. Although J10.15 has not become an international driving cycle, it has been continuously and deeply studied in Japan. Japan insists on using its own driving cycle, mainly because its driving cycle is well correlated with the certified driving cycles in Europe and the US.

7.2.2.5

Characteristics of Driving Cycles

The driving cycles of vehicles on the road can be reflected by the motion characteristics such as acceleration, deceleration, constant speed and idle speed. Through the investigation and analysis of these motion characteristics, the driving cycles which can represent the motion state can be developed. Whether expressed by modal or transient, the driving cycle is ultimately expressed as the speed-time curve, with the time step of usually 1 s. Through the acceleration and speed at the corresponding time point, the formula can be used to determine the mechanical energy required for vehicle motion. No matter what kind of power the vehicle uses, when this driving cycle recurs in the test vehicle on the chassis dynamometer under a common environment such as temperature, wind speed and rolling coefficient that can be controlled, the constant volume sampling (CVS) system and data analysis system can be used to comparatively judge the vehicle power performance, economy and emission performance indexes. Due to the diversity of actual road conditions and test purposes, various driving cycles have different characteristics, different proportion distribution of idle speed, constant speed, acceleration and deceleration and different acceleration distribution. If the speed and acceleration distribution is the same, the test results are likely to be the same. Some simulation software can also be used to evaluate the differences between different driving cycles on the same vehicle. The test results of different driving cycles are different, and the adaptive performance of the vehicle can be evaluated by using different driving cycles. In general, the countries and cities have different road characteristics and traffic flow, many types of driving cycles, and different distribution of characteristics. However, from the development of the forms and characteristics of driving cycles, the following conclusions can still be drawn. (1) Due to certain stability and similarity of the characteristics of driving cycles in a fixed region, it is of great significance to study the actual driving cycles according to different uses and purposes. At the same time, the driving cycles shall be improved constantly according to the development and change of vehicle technology and traffic conditions. (2) There may be a difference between the certified and researched driving cycles. The former has a wider speed range than the latter and the latter should take into account various extreme scenarios. Due to the improvement of vehicle technology and the importance of vehicle emission control, there is an increasing requirement for the correlation between short driving cycle used for I/M and

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certified driving cycle such as FTP, so the development of short driving cycle is becoming more and more important. (3) In terms of the simulated energy consumption level results, modal and transient conditions do not have much effect; but from a specific power point of view, the transient condition may be better and can provide different accelerations because the acceleration variation comes from real operation. In terms of control policy, the transient condition is definitely more appropriate. In Europe and Japan, more and more transient conditions have been developed and studied. (4) Beijing passenger vehicle cycle is also a condition with a variety of accelerations. According to the research results, the characteristic values of the cycle are basically between the transient driving cycle in the US and the steady driving cycle in Europe. The cycle is also distinguished among the urban, suburban and comprehensive roads, which is suitable for research and application.

7.2.3 HiL Simulation Test Taking a single-axle parallel hybrid electric vehicle as the test object, as shown in Fig. 7.5, the engine and the motor are connected to a drive shaft through an electronically controlled clutch. By controlling the clutch engagement and disengagement, the engine can be decoupled from the rest of the power chain. The ECU and the MCU, as the actuators in the total system, control the torque output and control mode of the engine and motor respectively. The main function of the BMS is to detect the status of the battery and control the connection switch between the battery and the MCU to ensure high voltage safety. The TCU controls the gears of the clutch and transmission respectively. The HCU obtains the signals of the engine, motor and battery through CAN bus communication, as well as the driver’s driving demand through communication interface, so as to control the power system and the electrically controlled clutch respectively. The running state of the actual vehicle can be simulated by running the mathematical model simulator, but the model built in the test process is limited by the accuracy and run time. A simple model is mainly composed of table lookup function and logic function. The online simulation design has the advantages of short run time and development time and small data demand. Although this model works normally, it has limited precision. However, a high-precision model needs to consume a lot of computing resources, so it is difficult to ensure the real-time operation of the simulator. Generally, offline simulation is used, such as SimPowerSystems tool used for high-voltage system analysis and GT-POWER used for high-precision engine. Therefore, a compromise should be made between the model computation time and simulation precision in modeling. In order to facilitate the comparison of the results of MiL and HiL, the control policy in the VCU is directly converted into C code. Therefore, the control policy of the HCU in the offline simulation is exactly the same as that downloaded to the

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Fig. 7.5 Control structure of hybrid electric vehicle

VCU, and the vehicle model of the software is exactly the same as that in the HiL system. The specific model is as follows. 1. Diver model The driver model takes the reference speed trajectory as the external input, and PI controller is used as the virtual driver to follow the moving trajectory of the reference vehicle. Based on the PI controller, the torque output of the driver model at the setting point is T ' dem , and the vehicle required torque is provided by the hybrid system. The torque T dem required by the vehicle is limited by the output torque of the power system, as shown in Eq. (7.1):  '  Tdem = min Tdem , Tdem, max (ω)

(7.1)

where Tdem.max (ω) Is the maximum torque that the power chain can transmit at the current motor speed ω. The dynamic response of the power chain takes Tdem.max (ω) as the maximum boundary value. 2. Engine model The engine, as the main power source of the hybrid electric vehicle, determines whether the whole power system can run normally. The engine model is built by table lookup method, and the table lookup function is based on the data of speed, torque, fuel consumption rate and emission in the test. Unlike conventional vehicles, the ECU of the hybrid vehicle is controlled by the HCU, not connected to the throttle. For easy control of the engine in the power chain, the improved ECU features the control mode of torque, speed and throttle. The input variables of the ECU are throttle requirement, speed requirement, torque requirement and control mode, as well as related state parameters such as engine

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speed and temperature. The torque control is designed to achieve better coupling between the output torque of the engine and the motor. The ECU receives a percentage of the torque requirement as input to the engine power requirement and converts this percentage into the actual torque requirement through a steady-state lookup table. The torque calculated by the ECU shall be modified according to the transmission control system and idle speed controller. The engine required torque (Tice,rep ) is calculated by the percentage (Tice,per ) function of torque requirement, which involves engine speed (ωice,idle ) and powertrain command control torque (Tice,tr ), as shown in Eq. (7.2).   Tice, req = f ice, trq ωice, idle , Tice, per + Tice, idle + Tice, tr

(7.2)

where fice.trp is a 2D lookup table function used by the ECU to convert the torque percentage into actual torque requirement; Tice,idle is the engine torque at idle. The idle speed controller is simulated with a PI controller and a feedback compensated engine resistance. The engine friction torque in the model is a quadratic function of engine speed designed on engine test data, as shown in Eq. (7.3). 2 Tice, fr = bice, 2 ωice + bice, 1 ωice + bice, 0

(7.3)

where T ice.fr is the engine friction torque; bice,i (i = 0, 1, 2) is the friction coefficient of the engine. All accessory loads are also centrally calculated as engine friction. 3. Motor model The motor is mainly used to perform the conversion between electric and mechanical energy, and its model is also used as a quasi-static table lookup of electric power with required torque and speed functions. Unlike the engine, the running ability of the motor is related to the SOC, so the SOC should be taken into account in the model of the motor. When the battery SOC is low, the battery cannot support the motor torque output due to low battery. In addition, according to the operating characteristics of the motor, the normal operation of the motor is affected by multiple factors: (1) Considering the inverter and winding temperature, when the temperature is higher than a certain value, the output torque of the motor is cleared to zero. (2) High and low voltage limits for motor. Considering the voltage range of the capacitor and inverter, torque limitation is required when the voltage exceeds the boundary. (3) Current limit effect. Excess current will cause damage to motor components, so the motor current shall also be considered in the motor model. In the HiL systems, the simulator is directly connected to the real controller. The software inside the simulator, RT-LAB, converts the vehicle model into code based on Simulink RTW software toolkit. The real-time system has the functions such as

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real-time model calculation, electrical interface input and output control, and realtime data interaction of the object under test. In the offline simulation, the simulation system can take one minute to simulate 1 h operation of the real system. However, in real-time simulation, the simulation time is strictly synchronized with the actual time, and the calculation of each simulation time step must correspond to the real time. The task execution time of the real-time system is the transient state of the real-time code running in the real-time system, and the time step is t n and t n+1 . The complete step size requires real-time simulation of the whole process from the beginning of t n to the end of t n+1 . The whole process consists of three parts: computation time, signal sampling and output time, and intermittent time. The task execution time is the computation time of the model. The real-time code obtained from Simulink obtains the run time of the system state for the next time step through efficient system solving equations. The signal sampling and output time refers to the instantaneous time between system computations, which is reflected at the real-time node or the I/O interface of the real-time system. The intermittent time is the idle time of the processor until the next time step. The asynchrony between offline simulation and real-time simulation is mainly because of the absence of intermittent time in offline simulation. The execution time of the time coding over time limit in the real-time system will exceed the selected real-time simulation step size. If the tolerance limit is exceeded, the simulation can only be classified as the software real-time simulation. This offlimit situation can be eliminated by increasing the simulation step size, but it will reduce the operation accuracy of the hybrid vehicle model. In order to ensure the real timeliness of the simulator simulation during operation of a complex model, the real-time system can be divided into one or more nodes according to the complexity of the model, and the model can be divided into vehicle powertrain model and other subsystem models accordingly. The parallel computation of multiple nodes in the simulator can ensure the real-time operation of the complex model without exceeding the calculated load. The simulation of the whole system is shown in Fig. 7.6. The system consists of two real-time systems (RTS), named RTS1 and RTS2 respectively. In the real-time simulation of the hybrid electric vehicle, RTS1 simulates the main parts such as engine, motor and transmission, while RTS2 is used to run the dynamic model and other models (such as vehicle accessory models, etc.) of the hybrid electric vehicle. Figure 7.7 shows the hardware layout of the real-time simulator. The code generated in the control model is downloaded into the RTS and run in real time. LINUX is installed on the RTS to ensure real-time tasks for the real-time controller. The RTS is connected to the real-time controller via CAN or I/O and is implemented using PCI board on the hardware. The I/O board, with a resolution of 10 ms, ensures that the system can output signals with sufficient precision. Since the control model is complex and requires a large amount of computation, RTS only runs part of the whole model. The two real-time systems are connected by a PCI-e high-speed board, and each real-time system downloads the real-time code from the upper computer through the local network (LAN line).

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Real-time system

Engine

Vehicle

Accelerator pedal Brake pedal

dynamics Motor

and other models

Transmission PCI-e communication Fig. 7.6 Application of real-time system

CAN bus

CAN card (PCI card)

CPU (run the real-time execution

High-speed FPGA (PCI-e) OPAL-RT)

Analog I/O I/O interface Digital I/O

PCI-e communication

Other RT nodes

Ethernet

Fig. 7.7 Hardware layout of real-time simulator

In order to meet the computation speed and real-time requirements of the simulation, the simulator uses OP5600 as the real-time target machine, with built-in Inteli7 hexa-core processor of 3.46 GHz basic frequency, one FPGA board and Ethernet interface; the CPU is internally installed with REDHATLINUX real-time operating system and I/O card driver. For HCU interface, one analog output board OP5330, analog input board OP5340, digital output board OP5354 and digital input board OP5353 are used.

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Engine Road driving cycle Diver model

VCU

Transmiss ion

Main reducer and

Motor and its control unit Brake force distributor

Braking torque True vehicle speed Engine and motor torque Vehicle longitudinal dynamics

Fig. 7.8 Vehicle Simulink simulation model

The Simulink simulation model of the hybrid electric vehicle is shown in Fig. 7.8. The basic data of the model is the configuration data of components of a 12 m bus. The engine has a peak power of 135 kW; the motor has a peak power of 100 kW, the battery capacity of 40 Ah and the nominal voltage of 324 V. The CCBC is used to simulate the model, and the step length is set as 1 ms in HiL simulation. The model running result is shown in Fig. 7.9, where, the red is the MiL running result (offline simulation result) based on MATLAB platform, and the blue is the HiL running result (online simulation result). In the simulation, the reference trajectory is followed based on the driver model, and the control command is sent to the control unit to control the whole powertrain. It can be seen from the simulation results that the vehicle speed, SOC and fuel consumption have similar trajectories in offline and online simulation. The results show that under the two different simulation modes, the global operation is relatively close, and the battery and fuel consumption trajectories are also very close, indicating that the system can produce similar control results by using the same energy management algorithm. However, the offline and online simulation results of transient operation characteristics are different. Taking the speed change trajectory during clutch engagement as an example, as shown in Fig. 7.10, the results of the two simulation cases show a great difference. In the offline simulation, the clutch engagement leads to small speed fluctuation, with the amplitude of only 20 r/min through the closed-loop control of the clutch stroke. However, in the online simulation, a large speed fluctuation occurs through the closed-loop control, with the speed rising sharply at 220 r/min, followed by the speed fluctuation caused by the torque impact. The transient speed change is mainly caused by torque impact. During the transition from pure motor drive to hybrid drive, the engine output torque is coupled with the whole power output torque, and the clutch stroke and motor torque shall be controlled in the whole process. As shown in Fig. 7.11, the torque of the motor and engine is coordinated on the main drive shaft according to the engagement process of the clutch. The torque rises gently, so that the pure motor drive is seamlessly

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Fig. 7.9 Comparison of offline calculation and HiL simulation results

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Fig. 7.10 Offline simulation results

connected to the hybrid drive. In the HiL simulation, the closed-loop control system is unstable based on the same policy due to the influence of the communication cycle, as shown in Fig. 7.12. The torque impact occurs during clutch engagement. This is mainly due to the time delay caused by the control through the closed loop during the clutch engagement process, which causes the estimated torque of the clutch operation to be inconsistent with the actual torque. According to the above simulation results, the differences between HiL and offline simulation of hardware are attributed to the following aspects: (1) A/D and D/A conversion In the control of MiL, the A/D and D/A are not converted for the system, so there is no deviation of simulation results caused by delay. In the execution of HiL

Fig. 7.11 Simulation results of engine and motor torque coupling

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Fig. 7.12 HiL simulation results

simulation, the SCM and the simulator need to take time to convert the voltage signal of the sensor and the digital signal in the SCM. Especially in signal sampling, the transient single fluctuation will cause the instability of the digital signal, which needs to be filtered, resulting in sampling delay. (2) I/O delay When the model runs offline, there is no signal conversion, so the run cycle of the controller in MiL simulation is the same as that of the model. On the premise that the model has a high degree of imitation, the run cycle of the system is only 1 ms. However, in the HiL system, it takes 4 ms to realize the controller sampling and output command, which is different from the result of 1 ms in MiL simulation. (3) CAN communication delay In the controller, the CAN communication delay of the power system is generally 10 ms or 2 ms, and the time needed to transmit from one node to another is different. These communication delays exist in the HIL test, but not in the MiL test. In MiL and HiL controls, although the same control policy is adopted, the operation effect of the vehicle will be affected due to the delay of sampling and command in the HiL system. As shown in Fig. 7.9, there is only a small difference between MiL and HiL when the vehicle is operating in steady state. However, in the case of transient vehicle changes, especially in the process of torque coupling, multiple control signals are coordinated for control, and there is a communication delay, resulting in a time control deviation of up to 40 times between the feedback signal and the command signal issued according to the feedback signal. This deviation can make the control response of the transient system out of sync as expected. Figures 7.10 and 7.12 show the engagement process of the clutch in the MiL and HiL tests, respectively. The MiL test achieves a better control result due to the absence of hardware delay. However, the closed-loop control of sampling in the HiL test makes the torque transfer unsmooth due to the time delay, resulting in the fluctuation of the vehicle

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speed. The HiL test is a comprehensive test of software and hardware, so it can better reflect the actual control effect of the controller.

7.2.4 MiL Simulation Test The key to realize MiL simulation is that the core control algorithm can be called by both MATLAB simulation model and DSP control software, so the control software is implemented by modular programming, and each module and its sub-modules exist in the form of functions. The control software includes such modules as system initialization and core control algorithm, in which the core control algorithm is run once per sampling period and invoked in interrupt or fast task. The MiL simulation system established based on Simulink environment is shown in Fig. 7.13. The data exchange between simulation software and control algorithm is realized by S-function in C language format. The S-function obtains the feedback signal from the main circuit model established by the Simulink simulation software and passes it to the control algorithm. After the operation, the control algorithm returns the PWM duty cycle and enable signal to the PWM module in the Simulink simulation software in the format of S-function. The S-function contains a set of callbacks to perform the necessary tasks at each simulation stage. The callbacks contained in the S-function, which acts as the data interface between the control algorithm and Simulink, are shown in Fig. 7.14, including initialization and simulation cycle. (1) The initialization section contains three callback functions: mdlInitializeSizes, mdlInitializeSampleTimes and mdl-Start, all of which are executed only once at the start of simulation. The quantity and dimension of the input and output ports are set in mdlInitializeSizes; the sampling time of S-function is set as a sampling

Fig. 7.13 MiL simulation system established in Simulink environment

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Fig. 7.14 Callback functions contained in S-function

period in mdlInitializeSampleTimes; the core control algorithm initialization is completed in mdlStart. (2) The mdlOutputs in the simulation cycle section is executed once only in each sampling period. In mdlout-puts, the core control algorithm is called. In order to verify the feasibility of the solution, an MiL simulation system is built by taking the single-phase PWM inverter as an example. Figure 7.15 shows the main circuit model of the inverter, which is built by Simulink simulation software. The power supply of the inverter is a single-phase AC power supply with adjustable amplitude. The front end is a single-phase uncontrolled rectifier, and the back end is a full-bridge inverter circuit with passive filter. The inverter adopts double loop PI control of voltage and current to control the inverter output voltage and inductive current respectively. The MiL simulation system is used for simulation. The simulation parameters are set as follows: the power supply of the inverter is single-phase 15 V, 50 Hz AC, and the switching frequency is 10 kHz; the passive filter is set to have 1.2 mH inductance, 4.7 μF capacitance, 30 Ω and 60 Ω load and 15 V reference voltage amplitude. Figure 7.16a, b show the output voltage of the inverter when the load is 30 Ω and 60 Ω respectively. The calculated output voltage is 14.5 V and 15.4 V, and the total harmonic distortion (THD) is 2.77% and 1.99%, respectively. Figure 7.16c, d show the dynamic response of the inverter output voltage when the load is 30 Ω and 60 Ω and the reference voltage changes from 5 to 15 V suddenly. According to the calculation, the adjustment time of output voltage is less than 5 ms, and the first peak value after sudden change is 11.9 V and 13.9 V respectively.

Fig. 7.15 Main circuit model of PWM inverter

445

u0/(5V/grid)

u0/(5V/grid)

7.2 Energy Management HiL and MiL Test

t/(5ms/grid)

t/(5ms/grid) (b) 60Ω load

u0/(5V/grid)

u0/(5V/grid)

(a) 30Ω load

t/(5ms/grid)

t/(5ms/grid)

(c) At the time of reference voltage

(d) At the time of reference voltage

sudden change at 30Ω load

sudden change at 60Ω load

Fig. 7.16 Test waveform

The experimental verification is carried out on the basis of simulation. The power supply, switching frequency, device, PI control and other parameters in the test are set to be consistent with those in the simulation. The test results are as follows. When the load is 30 Ω and 60 Ω, the amplitude of the output voltage of the inverter is 14.4 V and 15.2 V, respectively. When the load is 30 Ω and 60 Ω and the reference voltage changes from 5 to 15 V suddenly, the adjustment time of the inverter output voltage is less than 5 ms, and the first peak value after sudden change is 12 V and 13.6 V, respectively. The MiL simulation results and the test results are shown in Table 7.1. By comparison, it is found that they are consistent in both steady state and dynamic characteristics. This shows that the MiL simulation system can simulate the actual control effect of DSP control software, verifying the correctness of DSP control software developed by the MiL simulation system. A complete MiL simulation system is established, of which, the main circuit model is built by Simulink simulation software, the DSP control algorithm is written in C language in CCS environment, and the data interface between Simulink and

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Table 7.1 MiL simulation results and test results Load

Steady state output voltage/V

Dynamic response adjustment time/ms

First peak in dynamic response/V

Simulation

Simulation

Simulation

Tests

Tests

Tests

30 Ω

14.5

14.4