Fuzzy energy management strategy for electric vehicle combining driving cycle construction and air-conditioning load identification

Energy management strategy is developed by considering the random and air conditioning load fluctuation, which greatly affected torque control of electric motor in vehicle. Firstly, vehicle power consumption model established, based on influencing factors energy consumption: load. Therefore, driving conditions with characteristics representing actual are constructed. According to clustered characteristic parameters, were classified as different modes. Secondly, mode predicted condition was taken a variable evaluate logic threshold fuzzy influence considered. Finally, under New European Driving Cycle (NEDC), proposed simulated software environment, hardware in-loop (HIL) test performed verify strategy. The simulation HIL results show that can increase range fluctuation conditioning. Furthermore, combining prediction alleviate decline rate SOC. And has better adaptability complex lower battery rate.