{"title":"An Intelligent Control Strategy in a Parallel Hybrid Vehicle","authors":"A. Abdollahi","doi":"10.1109/ICEHV.2006.352272","DOIUrl":null,"url":null,"abstract":"This paper presents a design procedure for an adaptive power management control strategy based on a driving cycle recognition algorithm. The design goal of the control strategy is to minimize fuel consumption and engine-out NOx, HC and CD emissions on a set of diversified driving schedules. Seven facility-specific drive cycles are considered to represent different driving scenarios. For each facility-specific drive cycle, the fuel economy and emission are optimized and obtained proper split between the two energy sources (engine and electric motor). A driving pattern recognition algorithm is subsequently developed and used to classify the current driving cycle in to one of the facility-specific drive cycles; thus, the most appropriate control algorithm is adaptively selected. This control scheme was tested on a typical driving cycle and was found to work satisfactorily.","PeriodicalId":129674,"journal":{"name":"2006 IEEE Conference on Electric and Hybrid Vehicles","volume":"101 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2006 IEEE Conference on Electric and Hybrid Vehicles","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICEHV.2006.352272","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 9
Abstract
This paper presents a design procedure for an adaptive power management control strategy based on a driving cycle recognition algorithm. The design goal of the control strategy is to minimize fuel consumption and engine-out NOx, HC and CD emissions on a set of diversified driving schedules. Seven facility-specific drive cycles are considered to represent different driving scenarios. For each facility-specific drive cycle, the fuel economy and emission are optimized and obtained proper split between the two energy sources (engine and electric motor). A driving pattern recognition algorithm is subsequently developed and used to classify the current driving cycle in to one of the facility-specific drive cycles; thus, the most appropriate control algorithm is adaptively selected. This control scheme was tested on a typical driving cycle and was found to work satisfactorily.