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

作     者：Yang Zhao Yanguang Cai Qiwen Song Yang Zhao;Yanguang Cai;Qiwen Song

作者机构：Department of Mechanical and Electrical EngineeringGuangdong University of Science and TechnologyDongguan 523083China School of AutomationGuangdong University of TechnologyGuangzhou 510006China Transport Infrastructure Investment CompanyGuangzhou 510620China 

出 版 物：《IEEE/CAA Journal of Automatica Sinica》 (自动化学报（英文版）)

年 卷 期：2021年第8卷第12期

页      面：1948-1955页

核心收录：

学科分类：082304[工学-载运工具运用工程] 08[工学] 080204[工学-车辆工程] 0835[工学-软件工程] 0802[工学-机械工程] 080201[工学-机械制造及其自动化] 0823[工学-交通运输工程] 

主　　题：Energy management model predictive control(MPC) optimal control plug-in hybrid electric vehicle(PHEV) 

摘      要：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 ***,dynamic programming combined with equivalent con-sumption minimization strategy is used to compute an optimalsolution for real-time energy *** solution is thereference for PHEV energy management control along the *** 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 *** 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.