Energy Control of Plug-In Hybrid Electric Vehicles Using Model Predictive Control With Route Preview

Yang Zhao; Yanguang Cai; Qiwen Song

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Energy Control of Plug-In Hybrid Electric Vehicles Using Model Predictive Control With Route Preview

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The paper proposes an adoption of slope,elevation,speed and route distance preview to achieve optimal energymanagement of plug-in hybrid electric vehicles(PHEVs).Theapproach is to identify route features from historical and real-time traffic data,in which information fusion model and trafficprediction model are used to improve the information accuracy.Then,dynamic programming combined with equivalent con-sumption minimization strategy is used to compute an optimalsolution for real-time energy management.The solution is thereference for PHEV energy management control along the route.To improve the system''s ability of handling changing situation,the study further explores predictive control model in the real-time control of the energy.A simulation is performed to modelPHEV under above energy control strategy with route preview.The results show that the average fuel consumption of PHEValong the previewed route with model predictive control(MPC)strategy can be reduced compared with optimal strategy andbase control strategy.

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《自动化学报：英文版》 |2021年第12期|P.1948-1955|共8页
作者
Yang Zhao; Yanguang Cai; Qiwen Song;
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作者单位

Department of Mechanical and Electrical Engineering Guangdong University of Science and Technology Dongguan 523083 China;

School of Automation Guangdong University of Technology Guangzhou 510006 China;

Transport Infrastructure Investment Company Guangzhou 510620 China;

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原文格式 PDF
正文语种 chi
中图分类汽车工程;
关键词
Energy management; model predictive control(MPC); optimal control; plug-in hybrid electric vehicle(PHEV);

Energy Control of Plug-In Hybrid Electric Vehicles Using Model Predictive Control With Route Preview

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