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Research on the Optimal Charging Strategy for Li-Ion Batteries Based on Multi-Objective Optimization

Author

Listed:
  • Haitao Min

    (State Key Laboratory of Automotive Simulation and Control, Jilin University, Changchun 130022, China)

  • Weiyi Sun

    (State Key Laboratory of Automotive Simulation and Control, Jilin University, Changchun 130022, China)

  • Xinyong Li

    (State Key Laboratory of Automotive Simulation and Control, Jilin University, Changchun 130022, China)

  • Dongni Guo

    (China First Automobile Work shop Group Corporation Research and Development Center, Changchun 130011, China)

  • Yuanbin Yu

    (State Key Laboratory of Automotive Simulation and Control, Jilin University, Changchun 130022, China)

  • Tao Zhu

    (State Key Laboratory of Automotive Simulation and Control, Jilin University, Changchun 130022, China)

  • Zhongmin Zhao

    (China First Automobile Work shop Bus and Coach Co., Ltd., Changchun 130033, China)

Abstract

Charging performance affects the commercial application of electric vehicles (EVs) significantly. This paper presents an optimal charging strategy for Li-ion batteries based on the voltage-based multistage constant current (VMCC) charging strategy. In order to satisfy the different charging demands of the EV users for charging time, charged capacity and energy loss, the multi-objective particle swarm optimization (MOPSO) algorithm is employed and the influences of charging stage number, charging cut-off voltage and weight factors of different charging goals are analyzed. Comparison experiments of the proposed charging strategy and the traditional normal and fast charging strategies are carried out. The experimental results demonstrate that the traditional normal and fast charging strategies can only satisfy a small range of EV users’ charging demand well while the proposed charging strategy can satisfy the whole range of the charging demand well. The relative increase in charging performance of the proposed charging strategy can reach more than 80% when compared to the normal and fast charging dependently.

Suggested Citation

  • Haitao Min & Weiyi Sun & Xinyong Li & Dongni Guo & Yuanbin Yu & Tao Zhu & Zhongmin Zhao, 2017. "Research on the Optimal Charging Strategy for Li-Ion Batteries Based on Multi-Objective Optimization," Energies, MDPI, vol. 10(5), pages 1-15, May.
    • Handle: RePEc:gam:jeners:v:10:y:2017:i:5:p:709-:d:98926
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    References listed on IDEAS

    as
    1. Yongpeng Shen & Zhendong He & Dongqi Liu & Binjie Xu, 2016. "Optimization of Fuel Consumption and Emissions for Auxiliary Power Unit Based on Multi-Objective Optimization Model," Energies, MDPI, vol. 9(2), pages 1-18, February.
    2. Dongqi Liu & Yaonan Wang & Yongpeng Shen, 2016. "Electric Vehicle Charging and Discharging Coordination on Distribution Network Using Multi-Objective Particle Swarm Optimization and Fuzzy Decision Making," Energies, MDPI, vol. 9(3), pages 1-17, March.
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    Citations

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    Cited by:

    1. In-Ho Cho & Pyeong-Yeon Lee & Jong-Hoon Kim, 2019. "Analysis of the Effect of the Variable Charging Current Control Method on Cycle Life of Li-ion Batteries," Energies, MDPI, vol. 12(15), pages 1-11, August.
    2. Haitao Min & Boshi Wang & Weiyi Sun & Zhaopu Zhang & Yuanbin Yu & Yanzhou Zhang, 2020. "Research on the Combined Control Strategy of Low Temperature Charging and Heating of Lithium-Ion Power Battery Based on Adaptive Fuzzy Control," Energies, MDPI, vol. 13(7), pages 1-21, April.
    3. Boshi Wang & Haitao Min & Weiyi Sun & Yuanbin Yu, 2021. "Research on Optimal Charging of Power Lithium-Ion Batteries in Wide Temperature Range Based on Variable Weighting Factors," Energies, MDPI, vol. 14(6), pages 1-21, March.
    4. Ran Li & Xue Wei & Hui Sun & Hao Sun & Xiaoyu Zhang, 2022. "Fast Charging Optimization for Lithium-Ion Batteries Based on Improved Electro-Thermal Coupling Model," Energies, MDPI, vol. 15(19), pages 1-19, September.
    5. Aziz Rachid & Hassan El Fadil & Khawla Gaouzi & Kamal Rachid & Abdellah Lassioui & Zakariae El Idrissi & Mohamed Koundi, 2022. "Electric Vehicle Charging Systems: Comprehensive Review," Energies, MDPI, vol. 16(1), pages 1-38, December.
    6. Ouyang, Quan & Fang, Ruyi & Xu, Guotuan & Liu, Yonggang, 2022. "User-involved charging control for lithium-ion batteries with economic cost optimization," Applied Energy, Elsevier, vol. 314(C).

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