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State of the Art of Lithium-Ion Battery SOC Estimation for Electrical Vehicles

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  • Ruifeng Zhang

    (Graduate School at Shenzhen, Tsinghua University, Shenzhen 518055, China
    College of Mechanical and Vehicle Engineering, Hunan University, Changsha 410082, China
    Sunwoda Electronic Co., Ltd., Shenzhen 518108, China)

  • Bizhong Xia

    (Graduate School at Shenzhen, Tsinghua University, Shenzhen 518055, China)

  • Baohua Li

    (Graduate School at Shenzhen, Tsinghua University, Shenzhen 518055, China)

  • Libo Cao

    (College of Mechanical and Vehicle Engineering, Hunan University, Changsha 410082, China)

  • Yongzhi Lai

    (Sunwoda Electronic Co., Ltd., Shenzhen 518108, China)

  • Weiwei Zheng

    (Sunwoda Electronic Co., Ltd., Shenzhen 518108, China)

  • Huawen Wang

    (Sunwoda Electronic Co., Ltd., Shenzhen 518108, China)

  • Wei Wang

    (Sunwoda Electronic Co., Ltd., Shenzhen 518108, China)

Abstract

Sate of charge (SOC) accurate estimation is one of the most important functions in a battery management system for battery packs used in electrical vehicles. This paper focuses on battery SOC estimation and its issues and challenges by exploring different existing estimation methodologies. The key technologies of lithium-ion battery state estimation methodologies of the electrical vehicles categorized under five groups, such as the conventional method, adaptive filter algorithm, learning algorithm, nonlinear observer, and the hybrid method, are explored in an in-depth analysis. Lithium-ion battery characteristic, battery model, estimation algorithm, and cell unbalancing are the most important factors that affect the accuracy and robustness of SOC estimation. Finally, this paper concludes with the challenges of SOC estimation and suggests other directions for possible research efforts.

Suggested Citation

  • Ruifeng Zhang & Bizhong Xia & Baohua Li & Libo Cao & Yongzhi Lai & Weiwei Zheng & Huawen Wang & Wei Wang, 2018. "State of the Art of Lithium-Ion Battery SOC Estimation for Electrical Vehicles," Energies, MDPI, vol. 11(7), pages 1-36, July.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:7:p:1820-:d:157467
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    References listed on IDEAS

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