{"title":"混合动力汽车能量管理预测控制:实验结果","authors":"S. Kermani1, S. Delprat, T. Guerra, R. Trigui","doi":"10.1109/VPPC.2009.5289827","DOIUrl":null,"url":null,"abstract":"The control strategies of hybrid electric vehicles (HEV) consist of determining an optimal power split between different energy sources. The objective is to improve fuel economy and reduce pollutant emissions of the vehicle. In this paper a global optimization algorithm based on Lagrange formalism is recalled. This algorithm is then embedded within a Predictive Model Control scheme. Experimental results are presented.","PeriodicalId":191216,"journal":{"name":"2009 IEEE Vehicle Power and Propulsion Conference","volume":"36 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"39","resultStr":"{\"title\":\"Predictive control for HEV energy management: experimental results\",\"authors\":\"S. Kermani1, S. Delprat, T. Guerra, R. Trigui\",\"doi\":\"10.1109/VPPC.2009.5289827\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The control strategies of hybrid electric vehicles (HEV) consist of determining an optimal power split between different energy sources. The objective is to improve fuel economy and reduce pollutant emissions of the vehicle. In this paper a global optimization algorithm based on Lagrange formalism is recalled. This algorithm is then embedded within a Predictive Model Control scheme. Experimental results are presented.\",\"PeriodicalId\":191216,\"journal\":{\"name\":\"2009 IEEE Vehicle Power and Propulsion Conference\",\"volume\":\"36 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-10-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"39\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 IEEE Vehicle Power and Propulsion Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/VPPC.2009.5289827\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 IEEE Vehicle Power and Propulsion Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/VPPC.2009.5289827","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Predictive control for HEV energy management: experimental results
The control strategies of hybrid electric vehicles (HEV) consist of determining an optimal power split between different energy sources. The objective is to improve fuel economy and reduce pollutant emissions of the vehicle. In this paper a global optimization algorithm based on Lagrange formalism is recalled. This algorithm is then embedded within a Predictive Model Control scheme. Experimental results are presented.