ECMS-MPC Energy Management Strategy for Plug-In Hybrid Electric Buses Considering Motor Temperature Rise Effect

Abstract

Due to working in urban conditions, the plug-in hybrid electric bus (PHEB) has a high vehicle load rate during peak hours and when climbing long slopes. Therefore, the motor of PHEB is prone to overload and overheating, which affects the power performance and fuel economy of the PHEB. Thus, designing an energy management strategy (EMS) for PHEB that considers motor temperature is a crucial research topic. In this article, a strategy combining the equivalent consumption minimization strategy (ECMS) with the model predictive control (MPC) is proposed for PHEB to solve the problem of satisfying the fuel economy while preventing the motor temperature from being too high. First, the components of PHEB are analyzed and modeled. Second, ECMS is applied to the MPC framework, and the motor temperature is added to the cost function as an important optimization term. Third, the gray wolf optimization algorithm (GWOA) is selected to solve the minimum value of objective function offline. Finally, the accuracy of the model and the effectiveness of the proposed strategy in saving fuel are verified by MATLAB/Simulink and the hardware-in-the-loop tests. The result shows that compared with rule-based EMS, the fuel consumption of the proposed strategy is reduced by 15.81% and 15.45% under the urban dynamometer driving schedule and new combined driving cycle, respectively. Moreover, the proposed strategy can well restrain the motor temperature from being too high and keep it within a safe range.