{"title":"Real-time power management strategy in power-split hybrid electric vehicle","authors":"G. Gruosso, F. M. Ramacciotti","doi":"10.1109/IEVC.2014.7056125","DOIUrl":null,"url":null,"abstract":"This paper presents the implementation of a realtime predictive power management strategy in a light commercial power-split hybrid electric vehicle (HEV). The control outline was designed in a more intuitive way, avoiding rigorous mathematical description for predictive strategies, with a practical receding horizon insight. Therefore, a priori knowledge of the driving cycle is not required and the strategy aims actual implementation in real Electronic Control Units (ECUs). The cost function minimizes fuel consumption by setting different weighting factors to the manipulated variables at different drive conditions. Also it tries to sustain the State of Charge (SOC) of the battery. Moreover, a novel feature of the algorithm takes into account whether the vehicle is in urban zone or not, adapting the power distribution accordingly. The controller was validated in MATLAB. Results showed that the algorithm is very sensitive to changes in weighting factor. Furthermore, the insightful approach should be integrated with other communication systems in order to explore its full potential.","PeriodicalId":223794,"journal":{"name":"2014 IEEE International Electric Vehicle Conference (IEVC)","volume":"552 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 IEEE International Electric Vehicle Conference (IEVC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IEVC.2014.7056125","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
This paper presents the implementation of a realtime predictive power management strategy in a light commercial power-split hybrid electric vehicle (HEV). The control outline was designed in a more intuitive way, avoiding rigorous mathematical description for predictive strategies, with a practical receding horizon insight. Therefore, a priori knowledge of the driving cycle is not required and the strategy aims actual implementation in real Electronic Control Units (ECUs). The cost function minimizes fuel consumption by setting different weighting factors to the manipulated variables at different drive conditions. Also it tries to sustain the State of Charge (SOC) of the battery. Moreover, a novel feature of the algorithm takes into account whether the vehicle is in urban zone or not, adapting the power distribution accordingly. The controller was validated in MATLAB. Results showed that the algorithm is very sensitive to changes in weighting factor. Furthermore, the insightful approach should be integrated with other communication systems in order to explore its full potential.