R. Dang, C. He, Zhang Qiang, Keqiang Li, Yusheng Li
{"title":"ACC of electric vehicles with coordination control of fuel economy and tracking safety","authors":"R. Dang, C. He, Zhang Qiang, Keqiang Li, Yusheng Li","doi":"10.1109/IVS.2012.6232121","DOIUrl":null,"url":null,"abstract":"An adaptive cruise control system of electric vehicles is proposed, considering both fuel economy and tracking safety with model predictive control theory. Firstly, the mathematical relationship between fuel cost and longitudinal acceleration is analyzed through a simulation model. Secondly the 2-norm number is adopted to indicate the integrated cost function, which integrates economy performance and tracking performance together. Finally the proposed optimization problem is solved by model predictive control theory, and a contrast controller is built with linear quadratic algorithm. Both simulation and real vehicle test results show that the MPC controller can reduce fuel cost by above 5% than LQ controller in the range of safe tracking, and it successfully coordinates fuel economy and tracking safety.","PeriodicalId":402389,"journal":{"name":"2012 IEEE Intelligent Vehicles Symposium","volume":"225 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 IEEE Intelligent Vehicles Symposium","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IVS.2012.6232121","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 10
Abstract
An adaptive cruise control system of electric vehicles is proposed, considering both fuel economy and tracking safety with model predictive control theory. Firstly, the mathematical relationship between fuel cost and longitudinal acceleration is analyzed through a simulation model. Secondly the 2-norm number is adopted to indicate the integrated cost function, which integrates economy performance and tracking performance together. Finally the proposed optimization problem is solved by model predictive control theory, and a contrast controller is built with linear quadratic algorithm. Both simulation and real vehicle test results show that the MPC controller can reduce fuel cost by above 5% than LQ controller in the range of safe tracking, and it successfully coordinates fuel economy and tracking safety.