Improved fuzzy energy management strategy for fuel cell vehicles based on IPIO

In the energy management of fuel cell vehicles (FCEV), the traditional fuzzy logic strategy has the problems of strong subjectivity and average vehicle economy. This paper proposes a composite fuzzy energy management strategy with the goal of improving the life of the auxiliary energy source power battery, using an improved pigeon swarm optimization algorithm (IPIO) to update the fuzzy membership function, while ensuring that the power battery works in a suitable range for a long time and reducing equivalent hydrogen consumption quantity. This paper conducts secondary development on the existing ADVISOR model to establish a simulation model of the FCEV hybrid system, and conducts simulation experiments under NEDC and CLTC-P operating conditions. The results show that IPIO's improved energy management strategy can charge more than twice as fast as the power following strategy when the initial SOC is low, and can reach the appropriate SOC range faster, which can extend the life of the power battery; when the initial SOC is high, the charging speed is more than twice that of the power following strategy. In this case, the equivalent hydrogen consumption of IPIO's improved composite fuzzy energy management strategy was reduced by 9.09% and 9.09% respectively in the two working conditions compared with the before improvement 11.8%, which significantly reduced the hydrogen consumption and improved the economy of hydrogen fuel cell vehicles.