A modified model-free-adaptive-control-based real-time energy management strategy for plug-in hybrid electric vehicle

Abstract

To further improve the energy-saving potential and robustness of the energy management strategy (EMS) for plug-in hybrid electric vehicles (PHEVs) in a real-time application, this paper proposes a modified model-free-adaptive-control-based (MFAC-based) EMS to overcome the disadvantages in our previous MFAC-based EMS. First, the influence of external disturbance on MFAC-based EMS is discussed, and the results show that both the vehicle velocity and load change have a significant impact on its performance. Second, a modified MFAC-based real-time EMS is designed based on history driving data obtained from a repeated route in which a state-of-charge (SOC)-constraint-based reference SOC planning method is firstly proposed to simultaneously consider the vehicle velocity and changing load. Then, global SOC constraints are incorporated in Pontryagin's minimum principle (PMP) to enhance the adaptive capability of the proposed method. Finally, the optimal solution of PMP (i.e., optimal constant) is deployed as a benchmark, and the performance of the modified MFAC-based EMS (namely MFAC-II and MFAC-III) is in contrast to the previous one (MFAC for short) under various real-world driving cycles. The results demonstrate that the MFAC-III has a remarkable improvement in both economic performance and robustness. Particularly, the energy-saving effectiveness is close to the global optimum one in some driving conditions.