Energy Management Strategy of Combining Dynamic
Programming and XGBoost Algorithm for Hybrid Electric Vehicle

doi:10.3969/j.issn.1001-2222.2025.02.012

Vehicle Engine ›› 2025, Vol. 0 ›› Issue (2) : 80. DOI: 10.3969/j.issn.1001-2222.2025.02.012

Energy Management Strategy of Combining Dynamic Programming and XGBoost Algorithm for Hybrid Electric Vehicle

TIAN Ke¹，MA Xiao²

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Abstract

The real-time and accuracy problems of power distribution exist in plug-in hybrid electric vehicle energy management. The existing off-line power prediction model fails to fully consider the influence of multi-objective changes in dynamic performance of hybrid electric vehicle battery such as SOH and power fluctuation on the prediction results, and the existing machine learning algorithm has insufficient performance in power distribution calculation and prediction of hybrid electric vehicles. In order to solve these problems, the off-line dynamic programming and online XGBoost algorithm was used to model the power distribution of hybrid electric vehicles and realize the power distribution prediction. Firstly, the power system model of plug-in hybrid electric vehicle was built, and the typical mixed driving conditions of vehicle were obtained by cluster analysis method. Secondly, the optimal distribution ratio of engine power and lithium battery under the working condition was calculated off-line by dynamic programming algorithm. Finally, XGBoost algorithm was used as training data to verify the model. The calculation results show that the considered multi-objective optimization in the off-line dynamic planning makes the model training in the online stage have sufficient data support. Compared to the random forest algorithm, the XGBoost algorithm reduces the maximum error by 28% and increases the computational speed by 62%, which enables accurate estimation of the power distribution of plug-in hybrid vehicles.

Key words

hybrid electric vehicle / energy management strategy / dynamic programming / machine learning

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TIAN Ke, MA Xiao. Energy Management Strategy of Combining Dynamic Programming and XGBoost Algorithm for Hybrid Electric Vehicle[J]. Vehicle Engine. 2025, 0(2): 80 https://doi.org/10.3969/j.issn.1001-2222.2025.02.012