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Auxiliary health diagnosis method for lead-acid battery

Author

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  • Sun, Yu-Hua
  • Jou, Hurng-Liahng
  • Wu, Jinn-Chang
  • Wu, Kuen-Der

Abstract

This paper proposes a health auxiliary diagnosis method for the lead-acid battery unit. The proposed method is based on Approximate Entropy (ApEn). Since ApEn can quantify the regularity of a data sequence and the discharging curve for a health lead-acid battery unit is smooth, the proposed method can detect the degradation of battery unit caused by the internal short, opening of internal shorted or cell undergoing reversal using the distorted discharging curve. Aging experiments for the lead-acid battery are developed to verify the proposed method. The experimental results verify that the proposed health auxiliary diagnosis method can diagnosis the degradation of battery unit caused by the internal short, opening of internal shorted or cell undergoing reversal.

Suggested Citation

  • Sun, Yu-Hua & Jou, Hurng-Liahng & Wu, Jinn-Chang & Wu, Kuen-Der, 2010. "Auxiliary health diagnosis method for lead-acid battery," Applied Energy, Elsevier, vol. 87(12), pages 3691-3698, December.
    • Handle: RePEc:eee:appene:v:87:y:2010:i:12:p:3691-3698
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    References listed on IDEAS

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    Cited by:

    1. Hu, Chao & Jain, Gaurav & Tamirisa, Prabhakar & Gorka, Tom, 2014. "Method for estimating capacity and predicting remaining useful life of lithium-ion battery," Applied Energy, Elsevier, vol. 126(C), pages 182-189.
    2. Hu, Chao & Youn, Byeng D. & Chung, Jaesik, 2012. "A multiscale framework with extended Kalman filter for lithium-ion battery SOC and capacity estimation," Applied Energy, Elsevier, vol. 92(C), pages 694-704.
    3. Ma, Mina & Wang, Yu & Duan, Qiangling & Wu, Tangqin & Sun, Jinhua & Wang, Qingsong, 2018. "Fault detection of the connection of lithium-ion power batteries in series for electric vehicles based on statistical analysis," Energy, Elsevier, vol. 164(C), pages 745-756.
    4. Hua Zhang & Lei Pei & Jinlei Sun & Kai Song & Rengui Lu & Yongping Zhao & Chunbo Zhu & Tiansi Wang, 2016. "Online Diagnosis for the Capacity Fade Fault of a Parallel-Connected Lithium Ion Battery Group," Energies, MDPI, vol. 9(5), pages 1-18, May.
    5. Bai, Guangxing & Wang, Pingfeng & Hu, Chao & Pecht, Michael, 2014. "A generic model-free approach for lithium-ion battery health management," Applied Energy, Elsevier, vol. 135(C), pages 247-260.

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