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Research on Energy Management Strategy of PHEV Considering Battery Life Based on Driving Cycle Recognition

Aiming at the problems of deterioration of the use conditions of the power battery and increase of the life cycle cost of the vehicle caused by complicated driving conditions, the battery life is proactively extended from the perspective of energy management optimization. The optimization goal is to minimize the comprehensive fuel consumption and battery life attenuation. DP algorithm is used to achieve the global optimization. Based on the global optimization results of three representative driving routes composed of urban driving cycle, suburban driving cycle and high-speed driving cycle, the training is applied to the NN controller, a real-time optimization strategy for energy management under the corresponding routes is developed, and a random forest model is trained to identify the driving cycle. The simulation results show that the comprehensive fuel consumption obtained by simulation with the operating condition recognition strategy is only increased by 1.4%, the effective Ah-throughput flowing through the battery is increased by 1.3%, the ODCV is increased by 1.3%, and the simulation calculation time is reduced by more than 95% compared with the global optimization results. The developed energy management strategy based on operating condition recognition achieves good control effect and optimizes the overall performance of PHEV.