Velocity Prediction and Energy Management Strategy of Plug-In Hybrid Electric Vehicle

WEI Liqing; WAN Xing

doi:10.3969/j.issn.1001-2222.2022.03.010

Vehicle Engine ›› 2022, Vol. 0 ›› Issue (3) : 69-75. DOI: 10.3969/j.issn.1001-2222.2022.03.010

Velocity Prediction and Energy Management Strategy of Plug-In Hybrid Electric Vehicle

WEI Liqing，WAN Xing

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Abstract

In order to further improve the fuel economy of plug-in hybrid electric vehicle (PHEV), the vehicle velocity prediction method was proposed based on combined prediction model. Back propagation (BP) neural network vehicle velocity prediction models with different mapping capabilities were established to predict the vehicle velocity respectively, and then the weighted summation was conducted to obtain the vehicle velocity prediction results of combined prediction model. The energy management strategy was established to obtain the optimal fuel economy based on model predictive control, and the time-domain power output of prediction was optimized by using the idea of predictive control. The simulation results show that the combined vehicle velocity prediction model has a higher vehicle velocity prediction accuracy than that of single BP neural network. Compared with the rule-based strategy, the fuel economy for the predictive control strategy improves by 9%.

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PHEV / vehicle velocity / prediction / control strategy / energy management

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WEI Liqing，WAN Xing. Velocity Prediction and Energy Management Strategy of Plug-In Hybrid Electric Vehicle[J]. Vehicle Engine. 2022, 0(3): 69-75 https://doi.org/10.3969/j.issn.1001-2222.2022.03.010