Optimization of hybrid electric vehicle energy management strategy based on dynamic programming

Junyan Fan; Zhiqing Cheng; Zhendong Zhang

doi:10.1117/12.3030224

5 June 2024 Optimization of hybrid electric vehicle energy management strategy based on dynamic programming

Junyan Fan, Zhiqing Cheng, Zhendong Zhang

Proceedings Volume 13163, Fourth International Conference on Mechanical, Electronics, and Electrical and Automation Control (METMS 2024); 131632X (2024) https://doi.org/10.1117/12.3030224
Event: International Conference on Mechanical, Electronics, and Electrical and Automation Control (METMS 2024), 2024, Xi'an, China

Abstract

To improve the fuel economy of hybrid electric vehicles, the structure of a power-split hybrid power system based on the Ravina double-row planetary gear mechanism is studied, and the mathematical control model of the system is established. At the same time, the working modes are analyzed by using the equivalent lever diagrams. Two energy management strategies based on rule and dynamic programming are designed, and economic performance simulations are performed. The results show that, compared with the rule-based strategy, the engine fuel consumption of NEDC and WLTC based on the dynamic programming strategy is reduced by 10.47% and 4.71%, respectively.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Junyan Fan, Zhiqing Cheng, and Zhendong Zhang "Optimization of hybrid electric vehicle energy management strategy based on dynamic programming", Proc. SPIE 13163, Fourth International Conference on Mechanical, Electronics, and Electrical and Automation Control (METMS 2024), 131632X (5 June 2024); https://doi.org/10.1117/12.3030224

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