Optimization of fuzzy control energy management strategy for fuel cell vehicle power system using a multi-islandgenetic algorithm

Abstract

Energy storage system can be used to increase the fuel economy of fuel cell system (FCS). In this study, a new method was introduced for optimizing the energy management strategy (EMS) for fuel cell vehicle (FCV) to reduce fuel consumption. The membership function (MF) in fuzzy control is subjective; thus, 12 design variables in the input-output MFs were selected using sensitivity analysis, and elliptical basis function neural network method was used to establish a high-precision approximate model of FCV. Multi-island genetic algorithm was used to optimize the MFs. The effectiveness of the optimized fuzzy control EMS and the proposed optimization method were demonstrated in simulations of two EMSs under four driving cycles. The simulation results confirmed that the optimized fuzzy control EMS provided smoother and more stable output power from FCS reducing hydrogen consumption by 8.4%, 1.1%, 5.1%, and 7.6%, respectively, compared to the original fuzzy control EMS; and hydrogen saved by the optimized EMS provided extra range of 9.15, 1.10, 5.37, and 8.25 km per 100 km in the four driving cycles, respectively. The optimized EMS can reduce hydrogen consumption to increase fuel economy and extend the life span of the fuel cell.