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Statistical relationships between numerous retired lithium-ion cells and packs with random sampling for echelon utilization

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  • Ma, Chen
  • Chang, Long
  • Cui, Naxin
  • Duan, Bin
  • Zhang, Yulong
  • Yu, Zhihao

Abstract

Retired batteries are widely repurposed in energy storage packs as an economical and eco-friendly method to achieve echelon utilization. However, pack performance is strongly affected by variations in retired cells and pack configuration. Quantifying this effect in various pack configurations considering cell-to-cell variations is crucial for predicting the performance of numerous packs. Therefore, under a random sampling scenario, we developed statistical models of relationships between retired cells and packs in terms of capacity and resistance based on probability and statistics, thereby providing a solid theoretical foundation for designing and optimizing the pack structure. It is proven that parallel configuration improves the utilization efficiency and variation of pack-level capacities. Meanwhile, both parallel and series configurations reduce the pack-level resistance variation. Moreover, the statistical capacity performance of packs with parallel connections in series is superior to that of packs with series connections in parallel, although their statistical resistance characteristics are the same. Furthermore, based on the developed models, a capacity screening criterion is proposed that retired cells with a capacity greater than μC-2σC should be accepted in screening process to randomly compose energy storage packs, thereby reducing the capacity variation of packs while making full use of retired cells.

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  • Ma, Chen & Chang, Long & Cui, Naxin & Duan, Bin & Zhang, Yulong & Yu, Zhihao, 2022. "Statistical relationships between numerous retired lithium-ion cells and packs with random sampling for echelon utilization," Energy, Elsevier, vol. 257(C).
  • Handle: RePEc:eee:energy:v:257:y:2022:i:c:s036054422201595x
    DOI: 10.1016/j.energy.2022.124692
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    1. Steckel, Tobiah & Kendall, Alissa & Ambrose, Hanjiro, 2021. "Applying levelized cost of storage methodology to utility-scale second-life lithium-ion battery energy storage systems," Applied Energy, Elsevier, vol. 300(C).
    2. Zhong, Liang & Zhang, Chenbin & He, Yao & Chen, Zonghai, 2014. "A method for the estimation of the battery pack state of charge based on in-pack cells uniformity analysis," Applied Energy, Elsevier, vol. 113(C), pages 558-564.
    3. Rothgang, Susanne & Baumhöfer, Thorsten & van Hoek, Hauke & Lange, Tobias & De Doncker, Rik W. & Sauer, Dirk Uwe, 2015. "Modular battery design for reliable, flexible and multi-technology energy storage systems," Applied Energy, Elsevier, vol. 137(C), pages 931-937.
    4. Fan, Xinyuan & Zhang, Weige & Sun, Bingxiang & Zhang, Junwei & He, Xitian, 2022. "Battery pack consistency modeling based on generative adversarial networks," Energy, Elsevier, vol. 239(PE).
    5. Zhang, Caiping & Jiang, Yan & Jiang, Jiuchun & Cheng, Gong & Diao, Weiping & Zhang, Weige, 2017. "Study on battery pack consistency evolutions and equilibrium diagnosis for serial- connected lithium-ion batteries," Applied Energy, Elsevier, vol. 207(C), pages 510-519.
    6. Zhang, Youlang & Li, Yan & Tao, Yibin & Ye, Jilei & Pan, Aiqiang & Li, Xinzhou & Liao, Qiangqiang & Wang, Zhiqin, 2020. "Performance assessment of retired EV battery modules for echelon use," Energy, Elsevier, vol. 193(C).
    7. Yang Yang & Wenchao Zhu & Changjun Xie & Ying Shi & Furong Liu & Weibo Li & Zebo Tang, 2020. "A Layered Bidirectional Active Equalization Method for Retired Power Lithium-Ion Batteries for Energy Storage Applications," Energies, MDPI, vol. 13(4), pages 1-15, February.
    8. Zongwei Liu & Xinglong Liu & Han Hao & Fuquan Zhao & Amer Ahmad Amer & Hassan Babiker, 2020. "Research on the Critical Issues for Power Battery Reusing of New Energy Vehicles in China," Energies, MDPI, vol. 13(8), pages 1-19, April.
    9. 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).
    10. Rogers, Daniel J. & Aslett, Louis J.M. & Troffaes, Matthias C.M., 2021. "Modelling of modular battery systems under cell capacity variation and degradation," Applied Energy, Elsevier, vol. 283(C).
    11. Fabian Duffner & Niklas Kronemeyer & Jens Tübke & Jens Leker & Martin Winter & Richard Schmuch, 2021. "Post-lithium-ion battery cell production and its compatibility with lithium-ion cell production infrastructure," Nature Energy, Nature, vol. 6(2), pages 123-134, February.
    12. Jiang, Yan & Jiang, Jiuchun & Zhang, Caiping & Zhang, Weige & Gao, Yang & Mi, Chris, 2019. "A Copula-based battery pack consistency modeling method and its application on the energy utilization efficiency estimation," Energy, Elsevier, vol. 189(C).
    13. Astaneh, Majid & Andric, Jelena & Löfdahl, Lennart & Stopp, Peter, 2022. "Multiphysics simulation optimization framework for lithium-ion battery pack design for electric vehicle applications," Energy, Elsevier, vol. 239(PB).
    Full references (including those not matched with items on IDEAS)

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