{"title":"Research on energy management and optimization for PHEV","authors":"Zhumu Fu, Junya Xiao, A. Gao","doi":"10.1109/ICAL.2012.6308144","DOIUrl":null,"url":null,"abstract":"In order to reduce the fuel consumption and emissions of automobiles, the powertrain structure of Parallel Hybrid Electric Vehicle (PHEV) and the models of main components were firstly established. Then, on the basis of the models, the fuzzy control energy management system (EMS) was designed for PHEV. The fuzzy control energy management strategy was embedded in soft of Advisor for simulation. Finally, the parameters of the powertrain were optimized. Simulation results show that the fuzzy control strategies with parameters optimization not only have improved the fuel economy, but also reduced the emissions of HC, CO and so on, compared with the before parameters optimization.","PeriodicalId":373152,"journal":{"name":"2012 IEEE International Conference on Automation and Logistics","volume":"8 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 IEEE International Conference on Automation and Logistics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICAL.2012.6308144","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6
Abstract
In order to reduce the fuel consumption and emissions of automobiles, the powertrain structure of Parallel Hybrid Electric Vehicle (PHEV) and the models of main components were firstly established. Then, on the basis of the models, the fuzzy control energy management system (EMS) was designed for PHEV. The fuzzy control energy management strategy was embedded in soft of Advisor for simulation. Finally, the parameters of the powertrain were optimized. Simulation results show that the fuzzy control strategies with parameters optimization not only have improved the fuel economy, but also reduced the emissions of HC, CO and so on, compared with the before parameters optimization.