Haoxuan Dong, Weichao Zhuang, Yan Wang, Haonan Ding, Guo-dong Yin
{"title":"互联电动汽车能量最优制动速度规划","authors":"Haoxuan Dong, Weichao Zhuang, Yan Wang, Haonan Ding, Guo-dong Yin","doi":"10.1109/CVCI51460.2020.9338472","DOIUrl":null,"url":null,"abstract":"To improve the regeneration energy of electric vehicle, an energy-optimal braking strategy is developed. First, the vehicle braking intention is accessed by using vehicle-to-everything communication, i.e., braking distance and terminal velocity. Then, an optimal control problem with consideration of braking intention is formulated for maximizing regeneration energy. The control problem is solved by distance-based dynamic programming algorithm to plan the energy-optimal braking velocity. Finally, the effectiveness of proposed strategy is evaluated by simulation. The results show the regeneration energy efficiency of proposed strategy achieves improvement is over 10% compared with the constant speed strategy. Furtherly, the energy-optimal braking suggestions is investigated based on several traffic scenarios, i.e., a larger braking force in a high-velocity range can reduce vehicle resistance and make full use of motor generation power; the braking force was adjusted in moderated-velocity range for reducing friction braking, and a larger braking force should be used for parking quickly.","PeriodicalId":119721,"journal":{"name":"2020 4th CAA International Conference on Vehicular Control and Intelligence (CVCI)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2020-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Energy-optimal Braking Velocity Planning of Connected Electric Vehicle\",\"authors\":\"Haoxuan Dong, Weichao Zhuang, Yan Wang, Haonan Ding, Guo-dong Yin\",\"doi\":\"10.1109/CVCI51460.2020.9338472\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"To improve the regeneration energy of electric vehicle, an energy-optimal braking strategy is developed. First, the vehicle braking intention is accessed by using vehicle-to-everything communication, i.e., braking distance and terminal velocity. Then, an optimal control problem with consideration of braking intention is formulated for maximizing regeneration energy. The control problem is solved by distance-based dynamic programming algorithm to plan the energy-optimal braking velocity. Finally, the effectiveness of proposed strategy is evaluated by simulation. The results show the regeneration energy efficiency of proposed strategy achieves improvement is over 10% compared with the constant speed strategy. Furtherly, the energy-optimal braking suggestions is investigated based on several traffic scenarios, i.e., a larger braking force in a high-velocity range can reduce vehicle resistance and make full use of motor generation power; the braking force was adjusted in moderated-velocity range for reducing friction braking, and a larger braking force should be used for parking quickly.\",\"PeriodicalId\":119721,\"journal\":{\"name\":\"2020 4th CAA International Conference on Vehicular Control and Intelligence (CVCI)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-12-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 4th CAA International Conference on Vehicular Control and Intelligence (CVCI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CVCI51460.2020.9338472\",\"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 4th CAA International Conference on Vehicular Control and Intelligence (CVCI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CVCI51460.2020.9338472","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Energy-optimal Braking Velocity Planning of Connected Electric Vehicle
To improve the regeneration energy of electric vehicle, an energy-optimal braking strategy is developed. First, the vehicle braking intention is accessed by using vehicle-to-everything communication, i.e., braking distance and terminal velocity. Then, an optimal control problem with consideration of braking intention is formulated for maximizing regeneration energy. The control problem is solved by distance-based dynamic programming algorithm to plan the energy-optimal braking velocity. Finally, the effectiveness of proposed strategy is evaluated by simulation. The results show the regeneration energy efficiency of proposed strategy achieves improvement is over 10% compared with the constant speed strategy. Furtherly, the energy-optimal braking suggestions is investigated based on several traffic scenarios, i.e., a larger braking force in a high-velocity range can reduce vehicle resistance and make full use of motor generation power; the braking force was adjusted in moderated-velocity range for reducing friction braking, and a larger braking force should be used for parking quickly.