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Publishing Language: Chinese

Multi-objective Energy Management Strategy of HEV Based on Improved Dynamic Programming Method

Kegang ZHAO1Kunyang HE1Jie LI2( )Zhihao LIANG1Jinghao BEI1Yulong WANG3
School of Mechanical & Automotive Engineering, South China University of Technology, Guangzhou 510640, Guangdong, China
Guangzhou Huagong Automobile Inspection Technology Co. Ltd., Guangzhou 510640, Guangdong, China
Automotive Engineering Research Institute, Guangzhou Automobile Group Co. Ltd., Guangzhou 511434, Guangdong, China
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Abstract

Hybrid electric vehicle Energy Management Strategy (EMS) optimization is a multi-objective and multi-stage decision-making problem that needs to comprehensively optimize several performance indicators of hybrid electric vehicles. The traditional multi-objective optimization algorithm faces challenges such as low efficiency and difficult to guarantee convergence when dealing with these problems. Combined with the idea of non-dominated sorting algorithm, this paper extended the traditional Dynamic Programming (DP) to the field of multi-objective optimization, and proposed Non-dominated Sorting Dynamic Programming (NSDP). When using this algorithm, the driving condition was divided into several stages firstly. In each stage, the cumulative target value vector generated by the hybrid electric vehicle in different control strategies was obtained, and the current non dominated solution set and the corresponding control strategy were obtained through the non dominated sorting algorithm. Then, the non dominated solution set of each stage was used for reverse iteration in turn, until the leading edge of the non dominated solution set and the corresponding energy management control strategy of the whole driving cycle were obtained. In the simulation experiment, Weighting Dynamic Programming (WDP) and Non-dominated Sorting Dynamic Programming were applied to solve the optimization problem of multi-objective energy management strategy for power split hybrid electric vehicles and series parallel hybrid electric vehicles under constant acceleration conditions. The results show that NSDP not only can effectively complete the solution and ensure convergence, but also has significant advantages in homogeneity of solution set and solving efficiency. Furthermore, NSDP was used to solve the energy management optimization problem of series parallel hybrid electric vehicles running in Worldwide Harmonized Light Duty Vehicle Test Cycle (WLTC). The non dominated solution set can be used to analyze the working characteristics of vehicles and provides a reliable reference for the formulation of actual energy management strategy.

CLC number: U461.7 Article ID: 1000-565X(2022)09-0138-11

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Journal of South China University of Technology (Natural Science Edition)
Pages 138-148

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Cite this article:
ZHAO K, HE K, LI J, et al. Multi-objective Energy Management Strategy of HEV Based on Improved Dynamic Programming Method. Journal of South China University of Technology (Natural Science Edition), 2022, 50(9): 138-148. https://doi.org/10.12141/j.issn.1000-565X.210771

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Received: 06 December 2021
Published: 25 September 2022
© Journal of South China University of Technology(Natural Science Edition)