Abstract:

For the fuel economy of a series-parallel plug-in hybrid electric vehicle (PHEV) as the research target, in order to improve the control effect of the instantaneous equivalent fuel consumption minimization strategy (ECMS), allowed for the relationship of the battery state of charge (SOC), equivalent factor and equivalent fuel consumption, the global optimization model of the equivalent factor is built. The equivalent factorS is offline optimized by genetic algorithm (GA) to obtain the MAP of the optimization equivalent factor between the different ranges and the battery SOC value. The energy management strategy based on the optimization equivalent factor of ECMS is proposed. And considering the efficiency of the battery motor and other components, the power distribution of the engine, ISG and drive motor is gained based on the best equivalent factor of ECMS. Conducted with hardware in the loop simulation experiment, the simulation results show that compared with the equivalent factor which is not optimized, the vehicle fuel economy increases by 20.82%. And the results between hardware in loop experiment and simulation are basically identical. It’s indicated the feasibility and effectiveness of the proposed energy management strategy. Also it provides theoretical basis on solving the power allocation strategy of the different ranges of PHEV.

Key words: control strategy, discrete optimization of the equivalent factor, genetic algorithm global optimization, plug-in hybrid electric vehicle