Journal of South China University of Technology(Natural Science) >

2022 , Vol. 50 >Issue 9: 138 - 148

DOI: https://doi.org/10.12141/j.issn.1000-565X.210771

Mechanical Engineering

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

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  • 1.School of Mechanical & Automotive Engineering, South China University of Technology, Guangzhou 510640, Guangdong, China
    2.Guangzhou Huagong Automobile Inspection Technology Co. Ltd. , Guangzhou 510640, Guangdong, China
    3.Automotive Engineering Research Institute, Guangzhou Automobile Group Co. Ltd. , Guangzhou 511434, Guangdong, China
赵克刚（1977-），男，博士，副教授，主要从事最优控制、节能汽车和智能网联汽车研究。E-mail:kgzhao@scut.edu.cn
黎杰（1964-），男，教授级高级工程师，主要从事汽车检测与控制方向的研究。

Received date: 2021-12-06

  Online published: 2022-02-10

Supported by

the Natural Science Foundation of Guangdong Province(2020A1515010773);the Key R&D Project of Guangdong Province(2019B090912001)

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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.

Key words： multi-objective optimization; energy management strategy; improved dynamic programming; non-dominated sorting

Cite this article

ZHAO Kegang, HE Kunyang, LI Jie, et al . Multi-objective Energy Management Strategy of HEV Based on Improved Dynamic Programming Method[J]. Journal of South China University of Technology(Natural Science), 2022 , 50(9) : 138 -148 . DOI: 10.12141/j.issn.1000-565X.210771

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