An Adaptive Energy Management Control Strategy for Plug-in Hybrid Electric Vehicles During Car-Following Process

Abstract

An adaptive energy management control strategy is proposed for a commuter plug-in hybrid electrical vehicle (PHEV) during car-following process in this paper. The proposed energy management strategy (EMS) is an instantaneous optimization control strategy integrating car-following behavior performance index into adaptive equivalent consumption minimization strategy (A-ECMS). In order to achieve better fuel economy and safety performance under different car-following scenarios, the equivalent factor (EF) of ECMS and the weight factor of car-following performance in the instantaneous optimization cost function are designed as adaptive forms of Map tables about battery state of charge (SOC) and travel distance. The Mapping tables are established offline by utilizing historical traffic data of the commute road and particle swarm optimization (PSO) method. The effectiveness and practicality of the designed EMS are verified through the co-simulation of MATLAB/Simulink and GT-Suite simulator.