Zhiyuan Peng, Honglu Si, Haibing Wang, Chaodong Zhou, Guoli Chen, Tao Deng, Yuchun Shu, Yi Wang, Zengyue Liu, LianZuo Yin
{"title":"电动汽车用感应电动机的高精度转矩估计与安全控制","authors":"Zhiyuan Peng, Honglu Si, Haibing Wang, Chaodong Zhou, Guoli Chen, Tao Deng, Yuchun Shu, Yi Wang, Zengyue Liu, LianZuo Yin","doi":"10.1177/16878132231199345","DOIUrl":null,"url":null,"abstract":"As a power output unit, Induction Motor (IM) is widely used in Electric Vehicles (EV) due to its unique advantages of higher power density and better torque ability. With more complicated motor controller system, there are some hardware and software failures which bring some risks including EV unexpected acceleration or deceleration, therefore it is necessary to build high-accuracy torque estimation and safety control strategy. Firstly, hazard and safety concept are analyzed to make sure function safety goals and levels for IM system. Secondly, a novel method of high-accuracy torque estimation is proposed based on a rotor dynamic and composite flux linkage observer. Then, fault diagnosis and handling mechanisms of motor torque are designed to avoid hazards when it is a significant difference between motor estimation torque and vehicle requested torque. Finally, power test and Hardware in Loop (HIL) bench are configured to verify torque estimation accuracy and fault protection mechanisms rationality by comparing test results and injecting related faults. Experiment result shows that motor torque accuracy is within ±5 Nm and fault protection mechanisms can bring motor to safety state promptly.","PeriodicalId":49110,"journal":{"name":"Advances in Mechanical Engineering","volume":null,"pages":null},"PeriodicalIF":1.9000,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"High-accuracy torque estimation and safety control for induction motor used in electric vehicles\",\"authors\":\"Zhiyuan Peng, Honglu Si, Haibing Wang, Chaodong Zhou, Guoli Chen, Tao Deng, Yuchun Shu, Yi Wang, Zengyue Liu, LianZuo Yin\",\"doi\":\"10.1177/16878132231199345\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"As a power output unit, Induction Motor (IM) is widely used in Electric Vehicles (EV) due to its unique advantages of higher power density and better torque ability. With more complicated motor controller system, there are some hardware and software failures which bring some risks including EV unexpected acceleration or deceleration, therefore it is necessary to build high-accuracy torque estimation and safety control strategy. Firstly, hazard and safety concept are analyzed to make sure function safety goals and levels for IM system. Secondly, a novel method of high-accuracy torque estimation is proposed based on a rotor dynamic and composite flux linkage observer. Then, fault diagnosis and handling mechanisms of motor torque are designed to avoid hazards when it is a significant difference between motor estimation torque and vehicle requested torque. Finally, power test and Hardware in Loop (HIL) bench are configured to verify torque estimation accuracy and fault protection mechanisms rationality by comparing test results and injecting related faults. Experiment result shows that motor torque accuracy is within ±5 Nm and fault protection mechanisms can bring motor to safety state promptly.\",\"PeriodicalId\":49110,\"journal\":{\"name\":\"Advances in Mechanical Engineering\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.9000,\"publicationDate\":\"2023-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Advances in Mechanical Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1177/16878132231199345\",\"RegionNum\":4,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ENGINEERING, MECHANICAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Advances in Mechanical Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1177/16878132231199345","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, MECHANICAL","Score":null,"Total":0}
High-accuracy torque estimation and safety control for induction motor used in electric vehicles
As a power output unit, Induction Motor (IM) is widely used in Electric Vehicles (EV) due to its unique advantages of higher power density and better torque ability. With more complicated motor controller system, there are some hardware and software failures which bring some risks including EV unexpected acceleration or deceleration, therefore it is necessary to build high-accuracy torque estimation and safety control strategy. Firstly, hazard and safety concept are analyzed to make sure function safety goals and levels for IM system. Secondly, a novel method of high-accuracy torque estimation is proposed based on a rotor dynamic and composite flux linkage observer. Then, fault diagnosis and handling mechanisms of motor torque are designed to avoid hazards when it is a significant difference between motor estimation torque and vehicle requested torque. Finally, power test and Hardware in Loop (HIL) bench are configured to verify torque estimation accuracy and fault protection mechanisms rationality by comparing test results and injecting related faults. Experiment result shows that motor torque accuracy is within ±5 Nm and fault protection mechanisms can bring motor to safety state promptly.
期刊介绍:
Advances in Mechanical Engineering (AIME) is a JCR Ranked, peer-reviewed, open access journal which publishes a wide range of original research and review articles. The journal Editorial Board welcomes manuscripts in both fundamental and applied research areas, and encourages submissions which contribute novel and innovative insights to the field of mechanical engineering