Improving fuel economy and robustness of an improved ECMS method

Hybrid electric vehicles have shown significant improvement for both fuel efficiency and emission reduction, and attracted many researchers. Paramount for the fuel efficiency of HEVs is the energy management control strategies. ECMS (equivalent consumption minimization strategy) is one of the well-known real time power management strategies and has been used extensively in different works; however, its intrinsic difficulty is to find the optimal equivalent factor, which in theory is determined by the a priori knowledge of the complete driving cycle. Different methods have been proposed to solve this issue, but each one has its own pros. and cons. Especially, the applicability of each method for different cycles as well as the computation overhead are two main concerns in the methods presented so far. In this paper, a new method is presented for calculating equivalent factor in the ECMS method. The method does not rely on any prediction nor the a priori knowledge of driving cycles. Its robustness is demonstrated through different driving cycles with distinct characteristics. Our new method will improve the effectiveness and robustness of the ECMS method.