Research on Multi-objective Parameter Dynamic Optimization Design of HEV Considering Mode Transition

Abstract

The parameter optimization of hybrid electric vehicle is very complex and has always been the focus of research, due to the highly intertwined relationship between powertrain configurations and EMS. In addition, automated powertrain is typical cyber-physics system that contains discrete states, such as modes and gears. Transition between discrete states is a contributing factor that causes discomfort. Therefore, in order to solve the above problems, this paper proposes a multi-objective dynamic optimization algorithm considering mode transition. The algorithm consists of two layers. The first layer optimizes fuel economy and dynamic performance, the second layer optimizes ride comfort and smoothness performance, and the results of the second layer are returned to the first layer for re-optimization in real time. The mode transition frequency is used as the comfort objective function, and the threshold value of the engine high efficiency working area is added to the optimization parameter selection. The results show that the optimization method proposed in this paper realizes the parameter decoupling, and the optimization results achieve the global optimization. Effectively improves the vehicle performance and reduces engine start-stop frequently.