On Adaptive-ECMS strategies for hybrid electric vehicles

The problem of adapting the equivalence factor of the Equivalent Consumption Minimization Strategy (ECMS) to achieve a real time implementable sub-optimal solution of the problem of energy management in hybrid electric vehicle (HEV) has been the object of extensive research over the last decade. Contributions in the open literature range from methods based on prediction of driving cycle to driving pattern recognition to feedback from state of charge. In this paper, we first propose a classification of the methods that have been proposed to design an Adaptive-ECMS (A-ECMS) controller and then we carry out a comparative analysis in simulation of three adaptation laws falling into the class of algorithms of adaptation through feedback of SOC. Simulation results are performed on a parallel hybrid vehicle and show the performances of the three adaptation laws as compared to the optimal ECMS (a suitable proxi for the global optimal solution given by the dynamic programming algorithm).