{"title":"优化电动汽车运动,实现高效节能","authors":"Qin Yan, Bei Zhang, M. Kezunovic","doi":"10.1109/NAPS.2014.6965467","DOIUrl":null,"url":null,"abstract":"This paper focuses on the development of computational optimization algorithm to provide energy-based driving guidance for electric vehicle (EV) drivers to use the limited resource efficiently. The proposed efficiency improving strategy that minimizes total energy consumption according to various driving scenarios is demonstrated and analyzed. Several factors such as regenerative energy coefficient, stop-and-go frequency, inclination of ground, wind speed, etc. have been taken into consideration in the case studies.","PeriodicalId":421766,"journal":{"name":"2014 North American Power Symposium (NAPS)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"27","resultStr":"{\"title\":\"Optimization of electric vehicle movement for efficient energy consumption\",\"authors\":\"Qin Yan, Bei Zhang, M. Kezunovic\",\"doi\":\"10.1109/NAPS.2014.6965467\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper focuses on the development of computational optimization algorithm to provide energy-based driving guidance for electric vehicle (EV) drivers to use the limited resource efficiently. The proposed efficiency improving strategy that minimizes total energy consumption according to various driving scenarios is demonstrated and analyzed. Several factors such as regenerative energy coefficient, stop-and-go frequency, inclination of ground, wind speed, etc. have been taken into consideration in the case studies.\",\"PeriodicalId\":421766,\"journal\":{\"name\":\"2014 North American Power Symposium (NAPS)\",\"volume\":\"9 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-11-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"27\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 North American Power Symposium (NAPS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/NAPS.2014.6965467\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 North American Power Symposium (NAPS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NAPS.2014.6965467","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Optimization of electric vehicle movement for efficient energy consumption
This paper focuses on the development of computational optimization algorithm to provide energy-based driving guidance for electric vehicle (EV) drivers to use the limited resource efficiently. The proposed efficiency improving strategy that minimizes total energy consumption according to various driving scenarios is demonstrated and analyzed. Several factors such as regenerative energy coefficient, stop-and-go frequency, inclination of ground, wind speed, etc. have been taken into consideration in the case studies.