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Online state of charge estimation and open circuit voltage hysteresis modeling of LiFePO4 battery using invariant imbedding method

Author

Listed:
  • Dong, Guangzhong
  • Wei, Jingwen
  • Zhang, Chenbin
  • Chen, Zonghai

Abstract

The SOC (state-of-charge) of Li-ion (Lithium-ion) battery is an important evaluation index in BMS (battery management system) for EVs (Electric Vehicles) and smart grids. However, the existing special OCV (open circuit voltage) characteristics of LiFePO4 batteries complicate the estimation of SOC. To improve the estimation accuracy and reliability for battery SOC and battery terminal voltage, an online estimation approach for SOC and parameters of a battery based on the IIM (invariant-imbedding-method) algorithm has been proposed. Firstly, by using the IIM algorithm, an online parameter identification method has been established to accurately capture the real-time characteristics of the battery, which include the OCV hysteresis phenomena. Secondly, a dual IIM algorithm is employed to develop a multi-state estimator for SOC of the battery. Note that the parameters of the battery model are updated with the real-time measurements of the battery current and voltage at each sampling interval. Finally, the proposed method has been verified by a LiFePO4 battery cell under different operating current conditions. Experimental results indicate that the estimation value based on the proposed IIM-based estimator converges to real SOC with an error of ±2%, and the battery model can simulate OCV hysteresis phenomena robustly with high accuracy.

Suggested Citation

  • Dong, Guangzhong & Wei, Jingwen & Zhang, Chenbin & Chen, Zonghai, 2016. "Online state of charge estimation and open circuit voltage hysteresis modeling of LiFePO4 battery using invariant imbedding method," Applied Energy, Elsevier, vol. 162(C), pages 163-171.
  • Handle: RePEc:eee:appene:v:162:y:2016:i:c:p:163-171
    DOI: 10.1016/j.apenergy.2015.10.092
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    References listed on IDEAS

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    1. Wang, Limei & Cheng, Yong & Zhao, Xiuliang, 2015. "A LiFePO4 battery pack capacity estimation approach considering in-parallel cell safety in electric vehicles," Applied Energy, Elsevier, vol. 142(C), pages 293-302.
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    4. Liu, Xingtao & Chen, Zonghai & Zhang, Chenbin & Wu, Ji, 2014. "A novel temperature-compensated model for power Li-ion batteries with dual-particle-filter state of charge estimation," Applied Energy, Elsevier, vol. 123(C), pages 263-272.
    5. He, Yao & Liu, XingTao & Zhang, ChenBin & Chen, ZongHai, 2013. "A new model for State-of-Charge (SOC) estimation for high-power Li-ion batteries," Applied Energy, Elsevier, vol. 101(C), pages 808-814.
    6. Ng, Kong Soon & Moo, Chin-Sien & Chen, Yi-Ping & Hsieh, Yao-Ching, 2009. "Enhanced coulomb counting method for estimating state-of-charge and state-of-health of lithium-ion batteries," Applied Energy, Elsevier, vol. 86(9), pages 1506-1511, September.
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