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Novel state-of-health diagnostic method for Li-ion battery in service

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  • Mingant, R.
  • Bernard, J.
  • Sauvant-Moynot, V.

Abstract

The development of improved State-of-Health (SoH) diagnostic methods is a current research topic for battery-powered applications. For instance, the current rapid development of Electric Vehicles (EV) creates a strong demand for an accurate and reliable on-board SoH indicator during operation. Such an indicator is a key parameter required to optimize battery energy management and to track the degradation of the system performance. The electrochemical impedance spectrum (EIS) of an electrochemical system is a powerful lab-based diagnostic technique, usually measured using a frequency response analyzer. In this paper, we present an innovative diagnostic technique based on analysis of free voltage and current signals to give a so called “quasi-electrochemical impedance spectrum” (QEIS) and demonstrate its application on a Li-ion battery during a real EV duty cycle. It is worth noting that in our technique no additional signal is applied to the cell, since the current flowing into cells during use on-board is directly processed in the data treatment step.

Suggested Citation

  • Mingant, R. & Bernard, J. & Sauvant-Moynot, V., 2016. "Novel state-of-health diagnostic method for Li-ion battery in service," Applied Energy, Elsevier, vol. 183(C), pages 390-398.
    • Handle: RePEc:eee:appene:v:183:y:2016:i:c:p:390-398
    DOI: 10.1016/j.apenergy.2016.08.118
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    1. Omar, Noshin & Monem, Mohamed Abdel & Firouz, Yousef & Salminen, Justin & Smekens, Jelle & Hegazy, Omar & Gaulous, Hamid & Mulder, Grietus & Van den Bossche, Peter & Coosemans, Thierry & Van Mierlo, J, 2014. "Lithium iron phosphate based battery – Assessment of the aging parameters and development of cycle life model," Applied Energy, Elsevier, vol. 113(C), pages 1575-1585.
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    5. Abdel Monem, Mohamed & Trad, Khiem & Omar, Noshin & Hegazy, Omar & Mantels, Bart & Mulder, Grietus & Van den Bossche, Peter & Van Mierlo, Joeri, 2015. "Lithium-ion batteries: Evaluation study of different charging methodologies based on aging process," Applied Energy, Elsevier, vol. 152(C), pages 143-155.
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    5. Shida Jiang & Zhengxiang Song, 2021. "Estimating the State of Health of Lithium-Ion Batteries with a High Discharge Rate through Impedance," Energies, MDPI, vol. 14(16), pages 1-20, August.
    6. Mehmet C. Yagci & Thomas Feldmann & Elmar Bollin & Michael Schmidt & Wolfgang G. Bessler, 2022. "Aging Characteristics of Stationary Lithium-Ion Battery Systems with Serial and Parallel Cell Configurations," Energies, MDPI, vol. 15(11), pages 1-19, May.
    7. Bowen Jia & Yong Guan & Lifeng Wu, 2019. "A State of Health Estimation Framework for Lithium-Ion Batteries Using Transfer Components Analysis," Energies, MDPI, vol. 12(13), pages 1-14, June.
    8. Ming Zhang & Yanshuo Liu & Dezhi Li & Xiaoli Cui & Licheng Wang & Liwei Li & Kai Wang, 2023. "Electrochemical Impedance Spectroscopy: A New Chapter in the Fast and Accurate Estimation of the State of Health for Lithium-Ion Batteries," Energies, MDPI, vol. 16(4), pages 1-16, February.
    9. Zhou, Yong & Dong, Guangzhong & Tan, Qianqian & Han, Xueyuan & Chen, Chunlin & Wei, Jingwen, 2023. "State of health estimation for lithium-ion batteries using geometric impedance spectrum features and recurrent Gaussian process regression," Energy, Elsevier, vol. 262(PB).
    10. Lai, Xin & Huang, Yunfeng & Deng, Cong & Gu, Huanghui & Han, Xuebing & Zheng, Yuejiu & Ouyang, Minggao, 2021. "Sorting, regrouping, and echelon utilization of the large-scale retired lithium batteries: A critical review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 146(C).
    11. Ko, Chi-Jyun & Chen, Kuo-Ching, 2024. "Constructing battery impedance spectroscopy using partial current in constant-voltage charging or partial relaxation voltage," Applied Energy, Elsevier, vol. 356(C).
    12. Shahjalal, Mohammad & Roy, Probir Kumar & Shams, Tamanna & Fly, Ashley & Chowdhury, Jahedul Islam & Ahmed, Md. Rishad & Liu, Kailong, 2022. "A review on second-life of Li-ion batteries: prospects, challenges, and issues," Energy, Elsevier, vol. 241(C).
    13. Pastor-Fernández, Carlos & Yu, Tung Fai & Widanage, W. Dhammika & Marco, James, 2019. "Critical review of non-invasive diagnosis techniques for quantification of degradation modes in lithium-ion batteries," Renewable and Sustainable Energy Reviews, Elsevier, vol. 109(C), pages 138-159.
    14. He, Xitian & Sun, Bingxiang & Zhang, Weige & Fan, Xinyuan & Su, Xiaojia & Ruan, Haijun, 2022. "Multi-time scale variable-order equivalent circuit model for virtual battery considering initial polarization condition of lithium-ion battery," Energy, Elsevier, vol. 244(PB).

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