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A capacity model based on charging process for state of health estimation of lithium ion batteries

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  • Li, Xue
  • Jiang, Jiuchun
  • Wang, Le Yi
  • Chen, Dafen
  • Zhang, Yanru
  • Zhang, Caiping

Abstract

The incremental capacity (IC) analysis method is widely used to analyze the aging origins and state of health (SOH) of lithium ion batteries. This paper analyzes the technical difficulties during the application of the IC analysis method at first. A universal capacity model based on charging curve is then proposed, which not only inherits the advantages of IC analysis method but also avoids the tedious data preprocessing procedure, to estimate SOH of lithium ion batteries. The feasibility and accuracy of the model are demonstrated. To verify the accuracy and flexibility of the proposed capacity model, it is applied on different types of lithium ion batteries including LiFePO4,LiNi1/3Co1/3Mn1/3O2, and Li4/3Ti5/3O4. Furthermore, the proposed capacity model is applied on the aged cells to validate the model accuracy during the whole life span of lithium ion batteries. The results show that the model error is less than 4% of the nominal capacity for each case.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:appene:v:177:y:2016:i:c:p:537-543
    DOI: 10.1016/j.apenergy.2016.05.109
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    1. Xiong, Rui & Sun, Fengchun & Chen, Zheng & He, Hongwen, 2014. "A data-driven multi-scale extended Kalman filtering based parameter and state estimation approach of lithium-ion olymer battery in electric vehicles," Applied Energy, Elsevier, vol. 113(C), pages 463-476.
    2. Xiong, Rui & Sun, Fengchun & Gong, Xianzhi & Gao, Chenchen, 2014. "A data-driven based adaptive state of charge estimator of lithium-ion polymer battery used in electric vehicles," Applied Energy, Elsevier, vol. 113(C), pages 1421-1433.
    3. Berecibar, M. & Gandiaga, I. & Villarreal, I. & Omar, N. & Van Mierlo, J. & Van den Bossche, P., 2016. "Critical review of state of health estimation methods of Li-ion batteries for real applications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 56(C), pages 572-587.
    4. Dai, Haifeng & Wei, Xuezhe & Sun, Zechang & Wang, Jiayuan & Gu, Weijun, 2012. "Online cell SOC estimation of Li-ion battery packs using a dual time-scale Kalman filtering for EV applications," Applied Energy, Elsevier, vol. 95(C), pages 227-237.
    5. Miranda, D. & Costa, C.M. & Almeida, A.M. & Lanceros-Méndez, S., 2016. "Computer simulations of the influence of geometry in the performance of conventional and unconventional lithium-ion batteries," Applied Energy, Elsevier, vol. 165(C), pages 318-328.
    6. Capasso, Clemente & Veneri, Ottorino, 2014. "Experimental analysis on the performance of lithium based batteries for road full electric and hybrid vehicles," Applied Energy, Elsevier, vol. 136(C), pages 921-930.
    7. Sarasketa-Zabala, E. & Martinez-Laserna, E. & Berecibar, M. & Gandiaga, I. & Rodriguez-Martinez, L.M. & Villarreal, I., 2016. "Realistic lifetime prediction approach for Li-ion batteries," Applied Energy, Elsevier, vol. 162(C), pages 839-852.
    8. Fujimi, Toshio & Kajitani, Yoshio & Chang, Stephanie E., 2016. "Effective and persistent changes in household energy-saving behaviors: Evidence from post-tsunami Japan," Applied Energy, Elsevier, vol. 167(C), pages 93-106.
    9. Yang, Fangfang & Xing, Yinjiao & Wang, Dong & Tsui, Kwok-Leung, 2016. "A comparative study of three model-based algorithms for estimating state-of-charge of lithium-ion batteries under a new combined dynamic loading profile," Applied Energy, Elsevier, vol. 164(C), pages 387-399.
    10. Zou, Yuan & Li, Shengbo Eben & Shao, Bing & Wang, Baojin, 2016. "State-space model with non-integer order derivatives for lithium-ion battery," Applied Energy, Elsevier, vol. 161(C), pages 330-336.
    11. Wu, Ji & Zhang, Chenbin & Chen, Zonghai, 2016. "An online method for lithium-ion battery remaining useful life estimation using importance sampling and neural networks," Applied Energy, Elsevier, vol. 173(C), pages 134-140.
    12. Kong, Im Mo & Choi, Jong Won & Kim, Sung Il & Lee, Eun Sook & Kim, Min Soo, 2015. "Experimental study on the self-humidification effect in proton exchange membrane fuel cells containing double gas diffusion backing layer," Applied Energy, Elsevier, vol. 145(C), pages 345-353.
    13. 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.
    14. Chatzizacharia, Kalliopi & Benekis, Vasilis & Hatziavramidis, Dimitris, 2016. "A blueprint for an energy policy in Greece with considerations of climate change," Applied Energy, Elsevier, vol. 162(C), pages 382-389.
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