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A Study on the Open Circuit Voltage and State of Charge Characterization of High Capacity Lithium-Ion Battery Under Different Temperature

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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)

  • Mingwang Wang

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

Abstract

Open circuit voltage (OCV) is an important characteristic parameter of lithium-ion batteries, which is used to analyze the changes of electronic energy in electrode materials, and to estimate battery state of charge (SOC) and manage the battery pack. Therefore, accurate OCV modeling is a great significance for lithium-ion battery management. In this paper, the characteristics of high-capacity lithium-ion batteries at different temperatures were considered, and the OCV-SOC characteristic curves at different temperatures were studied by modeling, exponential, polynomial, sum of sin functions, and Gaussian model fitting method with pulse test data. The parameters of fitting OCV-SOC curves by exponential model (n = 2), polynomial model (n = 3~7), sum of sin functions model (n = 3), and Gaussian model (n = 4) at temperatures of 45 °C, 25 °C, 0 °C, and −20°C are obtained, and the errors are analyzed. The experimental results show that the operating temperature of the battery influences the OCV-SOC characteristic significantly. Therefore, these factors need to be considered in order to increase the accuracy of the model and improve the accuracy of battery state estimation.

Suggested Citation

  • Ruifeng Zhang & Bizhong Xia & Baohua Li & Libo Cao & Yongzhi Lai & Weiwei Zheng & Huawen Wang & Wei Wang & Mingwang Wang, 2018. "A Study on the Open Circuit Voltage and State of Charge Characterization of High Capacity Lithium-Ion Battery Under Different Temperature," Energies, MDPI, vol. 11(9), pages 1-17, September.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:9:p:2408-:d:169266
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    References listed on IDEAS

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    16. Shrivastava, Prashant & Soon, Tey Kok & Idris, Mohd Yamani Idna Bin & Mekhilef, Saad, 2019. "Overview of model-based online state-of-charge estimation using Kalman filter family for lithium-ion batteries," Renewable and Sustainable Energy Reviews, Elsevier, vol. 113(C), pages 1-1.
    17. Fan, Kesen & Wan, Yiming & Wang, Zhuo & Jiang, Kai, 2023. "Time-efficient identification of lithium-ion battery temperature-dependent OCV-SOC curve using multi-output Gaussian process," Energy, Elsevier, vol. 268(C).
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    19. Anna I. Pózna & Katalin M. Hangos & Attila Magyar, 2019. "Temperature Dependent Parameter Estimation of Electrical Vehicle Batteries," Energies, MDPI, vol. 12(19), pages 1-18, September.

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