Energy management strategy for plug-in hybrid electric vehicle integrated with vehicle-environment cooperation control

Energy management strategies have been proven to be instrumental in fully realizing the potential of plug-in hybrid electric vehicles (PHEVs). This paper proposes an improved adaptive equivalent consumption minimization strategy (IA-ECMS). In an IA-ECMS, the equivalence factor (EF) can be tuned in real time due to integration with the results of the vehicle-environment cooperative control. This study's main contributions are twofold. First, a novel A-ECMS is developed, in which the EF tuning method is carefully designed based on the results of a correlation study. The study results reveal that EF is determined by the future driving behaviour and the current component status. To ascertain the future driving behaviour, a method based on participatory sensing data (PSD) is used to implement the vehicleenvironment cooperative control. Second, a comparative study of the IA-ECMS and the energy management strategy based on the existing model of predictive control (MPC) is performed. The comparison results show that the application process of the IA-ECMS is similar to that of the MPC-based method except for two main differences. The simulation results demonstrate that the presented IA-ECMS approach could outperform in fuel economy the conventional A-ECMS (CA-ECMS) method. (C) 2020 Published by Elsevier Ltd.