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Joint Estimation of SOC and SOH for Single-Flow Zinc–Nickel Batteries

Author

Listed:
  • Chunning Song

    (School of Electrical Engineering, Guangxi University, Nanning 530004, China)

  • Yu Zhang

    (School of Electrical Engineering, Guangxi University, Nanning 530004, China)

  • Qijin Ling

    (School of Electrical Engineering, Guangxi University, Nanning 530004, China)

  • Shaogeng Zheng

    (School of Electrical Engineering, Guangxi University, Nanning 530004, China)

Abstract

The single-flow zinc–nickel battery (ZNB) is a new type of flow battery with a simple structure, large-scale energy storage, and low cost, and thus has attracted much attention in the battery field recently. The state of charge (SOC) and state of health (SOH) are key indicators of the battery, and their inaccurate estimation can damage the battery. However, little has been done so far to study how to jointly estimate SOC and SOH for the ZNB. In this paper, the method of adaptive IDUKF is proposed. A second-order equivalent circuit model is applied to improve the accuracy. At the same time, the double unscented Kalman filter (DUKF), which is optimized by the improved Harris hawk optimization (IHHO) algorithm, is used to estimate the SOC and parameters online. Then, the capacity update model is introduced to simulate the change in SOH. Finally, the proposed method is applied to a 16 Ah ZNB, and the experimental results confirm the validity of the proposed method.

Suggested Citation

  • Chunning Song & Yu Zhang & Qijin Ling & Shaogeng Zheng, 2022. "Joint Estimation of SOC and SOH for Single-Flow Zinc–Nickel Batteries," Energies, MDPI, vol. 15(13), pages 1-16, June.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:13:p:4781-:d:851534
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    References listed on IDEAS

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    Cited by:

    1. Pablo Carrasco Ortega & Pablo Durán Gómez & Julio César Mérida Sánchez & Fernando Echevarría Camarero & Ángel Á. Pardiñas, 2023. "Battery Energy Storage Systems for the New Electricity Market Landscape: Modeling, State Diagnostics, Management, and Viability—A Review," Energies, MDPI, vol. 16(17), pages 1-51, August.
    2. Xinfeng Zhang & Xiangjun Li & Kaikai Yang & Zhongyi Wang, 2023. "Lithium-Ion Battery Modeling and State of Charge Prediction Based on Fractional-Order Calculus," Mathematics, MDPI, vol. 11(15), pages 1-15, August.

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