Study on the fuel economy of fuel cell electric vehicle based on rule-based energy management strategies

This paper designed a fuel cell power system statically to meet the dynamic requirement, with the fuel cell's model and the vehicle model built by GT-Suite. The influence mechanism of different rule-based energy management strategies on the fuel economy was studied. The results revealed that fuel cell worked more efficiently with fuzzy logic control strategy than with power-follower strategy, given an average efficiency increase of 13.27%. Compared with the on/off control strategy, the heat dissipation was reduced by 79.67% with the fuzzy control strategy. Considering the feasibility of real-time implementation, robustness, and low computational burden, the on/off control strategy was optimised by a non-dominated sorting genetic algorithm (NSGA-II), based on ModeFRONTIER (MF). Compared with the original strategy, the fuel consumption was reduced by 17.9%.