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State-of-Charge Estimation with State-of-Health Calibration for Lithium-Ion Batteries

Author

Listed:
  • Tsung-Hsi Wu

    (Department of Electrical Engineering, National Sun Yat-sen University, 70 Lienhai Rd., Kaohsiung 80424, Taiwan)

  • Chin-Sien Moo

    (Department of Electrical Engineering, National Sun Yat-sen University, 70 Lienhai Rd., Kaohsiung 80424, Taiwan)

Abstract

This research is focused on state-of-charge ( SOC ) estimation with state-of-health ( SOH ) calibration for lithium-ion batteries on the basis of the coulomb counting method. The proposed approach intends to present an easy-to-use solution with high accuracy for estimating battery statuses without the need for demanding calculations or hard-earned databases. To estimate the SOC of an aged battery more accurately, the degradation of its full capacity has to be taken into account. By scheduling the battery’s charging/discharging current and monitoring the battery’s status, the existing full capacity can be updated regularly by regular calibration or occasionally by partial calibration, in which the charging/discharging rates are normalized with the latest updated full capacity to agree with the battery’s statuses. To exclude the misestimation caused by current measuring error, the SOC is reset to 0% when the battery is exhausted and 100% for a fully charged battery. With an updated SOH , the battery C-rate is re-scaled accordingly. Experimental tests are carried out to demonstrate that the proposed approach can provide an accurate online indication of batteries’ SOCs . With an implanted error of 0.3% in current measuring, the SOC estimation error can always be less than 1.905% after a number of SOH calibrations.

Suggested Citation

  • Tsung-Hsi Wu & Chin-Sien Moo, 2017. "State-of-Charge Estimation with State-of-Health Calibration for Lithium-Ion Batteries," Energies, MDPI, vol. 10(7), pages 1-10, July.
    • Handle: RePEc:gam:jeners:v:10:y:2017:i:7:p:987-:d:104515
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    References listed on IDEAS

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    1. Li, Xue & Jiang, Jiuchun & Wang, Le Yi & Chen, Dafen & Zhang, Yanru & Zhang, Caiping, 2016. "A capacity model based on charging process for state of health estimation of lithium ion batteries," Applied Energy, Elsevier, vol. 177(C), pages 537-543.
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    3. 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.
    4. 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.
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    Cited by:

    1. Mahammad A. Hannan & Mohammad M. Hoque & Pin J. Ker & Rawshan A. Begum & Azah Mohamed, 2017. "Charge Equalization Controller Algorithm for Series-Connected Lithium-Ion Battery Storage Systems: Modeling and Applications," Energies, MDPI, vol. 10(9), pages 1-20, September.
    2. Wang, Zengkai & Zeng, Shengkui & Guo, Jianbin & Qin, Taichun, 2019. "State of health estimation of lithium-ion batteries based on the constant voltage charging curve," Energy, Elsevier, vol. 167(C), pages 661-669.

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