Energy management strategy via dual fuzzy control based on Pareto multi-objective optimization for fuel cell hybrid electric vehicles with three power sources

Abstract

Energy management is the key technology for power distribution and driveability of fuel cell hybrid electric vehicles. To maximize the economic potential and prolong the power source lifetime of hydrogen fuel cell/battery/supercapacitor-based hybrid electric vehicles, this paper proposes an energy management strategy (EMS) based on dual fuzzy control with Pareto multi-objective optimization. Firstly, the dual fuzzy control strategy is developed to satisfy the vehicle dynamics, wherein the main-fuzzy controller determines the power output of the fuel cell, and the sub-fuzzy controller regulates the power output of the Li-ion battery and supercapacitor or recovers the braking energy of the vehicle. Secondly, the improved non-dominated sorting genetic algorithm (NSGA-II) is used to solve the multi-objective problem, wherein both the equivalent energy consumption and the equivalent power source performance degradation are incorporated in the cost function. And then, to obtain an optimized EMS, the membership functions of the dual fuzzy controllers are optimized by using the obtained Pareto non-inferiority solution set. Finally, the joint simulation model is built using MATLAB and ADVISOR, and nine Pareto non-inferior solutions are selected to verify the effectiveness and superiority of the proposed strategy. The results show that the proposed strategy is able to select different optimized control schemes according to the different situations of the amount of hydrogen stored in the fuel cell, ensuring that the equivalent energy consumption value and the equivalent power source performance degradation value reach the desired effect. Taking the fuel cell storing a moderate amount of hydrogen as an example, compared with the power following control strategy and the unoptimized double fuzzy control strategy, the proposed strategy can reduce the equivalent energy consumption by 3.1% and 2.1%, and the equivalent power source performance degradation by 88.8% and 86.4%, respectively, and it effectively reduces fluctuations of the FC output power.