Energy Management Strategy Optimization for a Novel Electric‐hydraulic Power Coupling Vehicle Considering the Influence of Multiple Driving Cycles

Abstract

Hydraulic hybrid technology can further improve the economy of electric vehicles (EV). In this article, a novel electric‐hydraulic power coupling vehicle (EHPCV), which is endowed with multiple drive modes and energy regenerative braking modes, is investigated. The electric‐hydraulic power coupler (EHPC) is an innovative device for realizing power coupling and conversion. The design and optimization of the energy management strategy (EMS) are key to ensuring the efficient and stable operation of the hybrid electric vehicle. Based on the analysis of energy flow, a rule‐based EMS (RB‐EMS) is built. To achieve more reasonable energy management of the EHPCV in random driving environments, the article proposes an optimization framework for the EMS based on multiple driving cycles. More precisely, a multiobjective optimization mathematical model is established with the goal of maximizing the battery state of charge and minimizing velocity error. Moreover, the optimal Latin hypercube design is used to select the design variables that have a significant impact on the optimization objective. Definitively, the nondominated sorting genetic algorithm II algorithm combines with RB‐EMS to optimize the control parameters. The verification results show that the optimized EMS enables the EHPCV to have superior economic advantages.