Power management strategy based on adaptive neuro-fuzzy inference system for fuel cell-battery hybrid vehicle

Abstract

A power management strategy based on an adaptive neuro-fuzzy inference system is proposed to enhance the fuel economy of fuel cell-battery hybrid vehicle and increase the mileage of continuation of journey. The model of hybrid vehicle for fuel cell-battery structure is developed by electric vehicle simulation software advisor. The simulation results demonstrate that the proposed strategy can satisfy the power requirement of four standard drive cycles and achieve the power distribution between fuel cell system and battery. The comprehensive comparisons with a power tracking control strategy which is widely adopted in advisor verify that the proposed strategy has better validity in terms of fuel economy in four standard drive cycles. Hence, the proposed strategy will take important effect for designing advanced power management system of hybrid vehicle.