{"title":"插电式混合动力汽车在不同驾驶场景下的油耗与性能权衡优化","authors":"S. Buerger, W. Huebner","doi":"10.1109/IEVC.2012.6183262","DOIUrl":null,"url":null,"abstract":"In [1] a new concept was developed for the design of hybrid electric powertrains that includes optimization of the component sizes as well as control strategies. In contrast to most existing publications, the approach explicitly considers the conflicting goals of low fuel consumption and high vehicle longitudinal dynamics and the trade-off is quantified. This is achieved by formulating two multiobjective optimization problems using the Pareto-concepts and solving it by using a Genetic Algorithm. Whereas results have already been shown for the New European Driving Cycle (NEDC) [1], this paper focuses on future driving scenarios that represent the markets USA, China and Germany. It is shown, how the control strategy and the component sizes of the electrical machine, the battery-pack and the final drive have to be adapted when considering driving cycles with different typical characteristics.","PeriodicalId":134818,"journal":{"name":"2012 IEEE International Electric Vehicle Conference","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Optimization of the trade-off between fuel consumption and performance of PHEVs in different driving scenarios\",\"authors\":\"S. Buerger, W. Huebner\",\"doi\":\"10.1109/IEVC.2012.6183262\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In [1] a new concept was developed for the design of hybrid electric powertrains that includes optimization of the component sizes as well as control strategies. In contrast to most existing publications, the approach explicitly considers the conflicting goals of low fuel consumption and high vehicle longitudinal dynamics and the trade-off is quantified. This is achieved by formulating two multiobjective optimization problems using the Pareto-concepts and solving it by using a Genetic Algorithm. Whereas results have already been shown for the New European Driving Cycle (NEDC) [1], this paper focuses on future driving scenarios that represent the markets USA, China and Germany. It is shown, how the control strategy and the component sizes of the electrical machine, the battery-pack and the final drive have to be adapted when considering driving cycles with different typical characteristics.\",\"PeriodicalId\":134818,\"journal\":{\"name\":\"2012 IEEE International Electric Vehicle Conference\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-03-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 IEEE International Electric Vehicle Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IEVC.2012.6183262\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 IEEE International Electric Vehicle Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IEVC.2012.6183262","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Optimization of the trade-off between fuel consumption and performance of PHEVs in different driving scenarios
In [1] a new concept was developed for the design of hybrid electric powertrains that includes optimization of the component sizes as well as control strategies. In contrast to most existing publications, the approach explicitly considers the conflicting goals of low fuel consumption and high vehicle longitudinal dynamics and the trade-off is quantified. This is achieved by formulating two multiobjective optimization problems using the Pareto-concepts and solving it by using a Genetic Algorithm. Whereas results have already been shown for the New European Driving Cycle (NEDC) [1], this paper focuses on future driving scenarios that represent the markets USA, China and Germany. It is shown, how the control strategy and the component sizes of the electrical machine, the battery-pack and the final drive have to be adapted when considering driving cycles with different typical characteristics.