Yongliang Li, Changlu Zhao, Ying Huang, Xu Wang, Fen Guo, Long Yang
{"title":"增程电动汽车再生制动控制策略研究","authors":"Yongliang Li, Changlu Zhao, Ying Huang, Xu Wang, Fen Guo, Long Yang","doi":"10.1109/VPPC49601.2020.9330885","DOIUrl":null,"url":null,"abstract":"Aiming at the problem of regenerative braking energy recovery control for extended range electric vehicles, a front-rear braking force distribution strategy that maximizes braking energy recovery is proposed on the premise of ensuring vehicle braking stability and safety in this paper; then a regenerative braking energy recovery strategy based on fuzzy control is designed. In addition, the membership function of the fuzzy controller is optimized by particle swarm optimization with taking the braking energy recovery rate as the target. Finally, a quasi-static model of the whole vehicle simulation is established on the Simulink-Cruise joint simulation platform, and the simulation is performed under the NEDC, FTP72 and Ja1015 operating conditions. The simulation results show that the designed regenerative braking energy recovery control strategy has an energy recovery rate of 53.5%, 43.9% and 56.1% in the above three operating conditions, and the battery charging power does not exceed the maximum charging power in the extended range mode, proving a good control performance.","PeriodicalId":6851,"journal":{"name":"2020 IEEE Vehicle Power and Propulsion Conference (VPPC)","volume":"8 1","pages":"1-6"},"PeriodicalIF":0.0000,"publicationDate":"2020-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Study on Regenerative Braking Control Strategy for Extended Range Electric Vehicles\",\"authors\":\"Yongliang Li, Changlu Zhao, Ying Huang, Xu Wang, Fen Guo, Long Yang\",\"doi\":\"10.1109/VPPC49601.2020.9330885\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Aiming at the problem of regenerative braking energy recovery control for extended range electric vehicles, a front-rear braking force distribution strategy that maximizes braking energy recovery is proposed on the premise of ensuring vehicle braking stability and safety in this paper; then a regenerative braking energy recovery strategy based on fuzzy control is designed. In addition, the membership function of the fuzzy controller is optimized by particle swarm optimization with taking the braking energy recovery rate as the target. Finally, a quasi-static model of the whole vehicle simulation is established on the Simulink-Cruise joint simulation platform, and the simulation is performed under the NEDC, FTP72 and Ja1015 operating conditions. The simulation results show that the designed regenerative braking energy recovery control strategy has an energy recovery rate of 53.5%, 43.9% and 56.1% in the above three operating conditions, and the battery charging power does not exceed the maximum charging power in the extended range mode, proving a good control performance.\",\"PeriodicalId\":6851,\"journal\":{\"name\":\"2020 IEEE Vehicle Power and Propulsion Conference (VPPC)\",\"volume\":\"8 1\",\"pages\":\"1-6\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 IEEE Vehicle Power and Propulsion Conference (VPPC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/VPPC49601.2020.9330885\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE Vehicle Power and Propulsion Conference (VPPC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/VPPC49601.2020.9330885","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Study on Regenerative Braking Control Strategy for Extended Range Electric Vehicles
Aiming at the problem of regenerative braking energy recovery control for extended range electric vehicles, a front-rear braking force distribution strategy that maximizes braking energy recovery is proposed on the premise of ensuring vehicle braking stability and safety in this paper; then a regenerative braking energy recovery strategy based on fuzzy control is designed. In addition, the membership function of the fuzzy controller is optimized by particle swarm optimization with taking the braking energy recovery rate as the target. Finally, a quasi-static model of the whole vehicle simulation is established on the Simulink-Cruise joint simulation platform, and the simulation is performed under the NEDC, FTP72 and Ja1015 operating conditions. The simulation results show that the designed regenerative braking energy recovery control strategy has an energy recovery rate of 53.5%, 43.9% and 56.1% in the above three operating conditions, and the battery charging power does not exceed the maximum charging power in the extended range mode, proving a good control performance.