Research on Energy Management Strategies Based on Bargaining Game for Range-Extended Electric Vehicle Considering Battery Life

Zhenhai Gao, Jiewen Liu, Shiqing Long, Zihang Su, Hanwu Liu (), Cheng Chang and Wang Song
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Zhenhai Gao: Xinxiang Vocational and Technical College, Xinxiang 453000, China
Jiewen Liu: College of Automotive Engineering, Jilin University, Changchun 130022, China
Shiqing Long: College of Transportation, Jilin University, Changchun 130022, China
Zihang Su: College of Transportation, Jilin University, Changchun 130022, China
Hanwu Liu: College of Transportation, Jilin University, Changchun 130022, China
Cheng Chang: School of Vehicle and Traffic Engineering, Henan Institute of Technology, Xinxiang 453003, China
Wang Song: College of Materials Science and Engineering, Changchun University of Science and Technology, Changchun 130022, China

Energies, 2024, vol. 17, issue 24, 1-21

Abstract: Effective energy management techniques are essential for the full utilization of energy in the field of extended-range electric vehicle research, with the goals of lowering energy consumption and exhaust emissions, enhancing driving comfort, and extending battery life. To achieve optimal comprehensive usage costs, this article uses bargaining game theory to design an adaptive energy management strategy ( EMS ad-bg ) that focuses on battery life. In the study, a power system model was first built based on AVL/Cruise software and MATLAB/Simulink software. The impact of discount factors on strategy results was analyzed through simulation experiments. The results showed that the discount factor for auxiliary power unit (APU) focused more on energy optimization, while the discount factor for battery focused more on optimizing the degradation of battery life. When the initial state of charge (SoC) is high, the specific value of the discount factor also has a significant impact on the battery SoC value at the end of the trip. To improve the strategy’s adaptability to various initial SoC values, a fuzzy controller was created that can adaptively modify the discount factor based on the battery SoC. The results of the simulation experiment demonstrate that the bargaining game strategy taking SoC into account has more pronounced advantages in terms of overall usage cost when compared to the strategy of the fixed discount factor. The creation of an EMS ad-bg that takes battery life into account based on a bargaining game can serve as a helpful model for the creation of a clever EMS that lowers the total cost of operating a vehicle.

Keywords: range-extended electric vehicle; energy management strategy; bargaining game; battery life optimization; comprehensive usage costs (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2024
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