IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v337y2025ics0360544225040691.html

Modelling of cells’ capacity distribution and fading for lithium-ion battery pack during the charge and discharge cycles

Author

Listed:
  • Li, Chengzhang
  • Zhao, Guowei
  • Li, Kaiyue
  • Zhang, Xidong
  • Wang, Jianwu

Abstract

Accurate and efficient prediction of pack-level capacity distribution and fading within lithium-ion battery packs is critical for state of health (SOH) and remaining useful life (RUL) assessment. However, different aging mechanisms and rates arising from intrinsic cell-to-cell inconsistencies and interactions complicate reliable distribution forecasting. This study proposes a modelling method based on the generalized extreme value (GEV) distribution, which offers superior generalization capability compared to single-component distributions. Using single-cell models validated with the UCL dataset, we generate comprehensive simulation data under 35 distinct conditions. Subsequently, the dataset is utilized to verify the advantages of the GEV distribution in characterizing capacity distributions and to establish formulas of the distribution parameters. The validation results show that the proposed model achieves high accuracy (MAPE ≈ 2.91 %) and computational efficiency in describing the capacity distribution of battery packs. The derived formulas intuitively reveal the relationships between pack operational/initial state parameters and key capacity distribution metrics including skewness (asymmetry), dispersion, and overall degradation level, supporting optimized battery pack management.

Suggested Citation

  • Li, Chengzhang & Zhao, Guowei & Li, Kaiyue & Zhang, Xidong & Wang, Jianwu, 2025. "Modelling of cells’ capacity distribution and fading for lithium-ion battery pack during the charge and discharge cycles," Energy, Elsevier, vol. 337(C).
    • Handle: RePEc:eee:energy:v:337:y:2025:i:c:s0360544225040691
    DOI: 10.1016/j.energy.2025.138427
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544225040691
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2025.138427?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    References listed on IDEAS

    as
    1. Yiqun Liu & Y. Gene Liao & Ming-Chia Lai, 2020. "Lithium-Ion Polymer Battery for 12-Voltage Applications: Experiment, Modelling, and Validation," Energies, MDPI, vol. 13(3), pages 1-15, February.
    2. Yang, Fangfang & Wang, Dong & Zhao, Yang & Tsui, Kwok-Leung & Bae, Suk Joo, 2018. "A study of the relationship between coulombic efficiency and capacity degradation of commercial lithium-ion batteries," Energy, Elsevier, vol. 145(C), pages 486-495.
    3. An, Fulai & Zhang, Weige & Sun, Bingxiang & Jiang, Jiuchun & Fan, Xinyuan, 2023. "A novel battery pack inconsistency model and influence degree analysis of inconsistency on output energy," Energy, Elsevier, vol. 271(C).
    4. Kong, Jin-zhen & Yang, Fangfang & Zhang, Xi & Pan, Ershun & Peng, Zhike & Wang, Dong, 2021. "Voltage-temperature health feature extraction to improve prognostics and health management of lithium-ion batteries," Energy, Elsevier, vol. 223(C).
    5. 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).
    6. Ferreira, Helder Lopes & Garde, Raquel & Fulli, Gianluca & Kling, Wil & Lopes, Joao Pecas, 2013. "Characterisation of electrical energy storage technologies," Energy, Elsevier, vol. 53(C), pages 288-298.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Wang, Shichao & Wang, Yujie & Soo, Yin-Yi, 2025. "Evaluation and prediction of lithium-ion battery pack inconsistency in electric vehicles based on actual operating data," Energy, Elsevier, vol. 319(C).
    2. Huang, Zhelin & Xu, Fan & Yang, Fangfang, 2023. "State of health prediction of lithium-ion batteries based on autoregression with exogenous variables model," Energy, Elsevier, vol. 262(PB).
    3. Fan, Xinyuan & Qi, Hongfeng & Zhang, Weige & Zhang, Yanru, 2024. "Experiment-free physical hybrid neural network approach for battery pack inconsistency estimation," Applied Energy, Elsevier, vol. 358(C).
    4. Angeles Cabañero, Maria & Altmann, Johannes & Gold, Lukas & Boaretto, Nicola & Müller, Jana & Hein, Simon & Zausch, Jochen & Kallo, Josef & Latz, Arnulf, 2019. "Investigation of the temperature dependence of lithium plating onset conditions in commercial Li-ion batteries," Energy, Elsevier, vol. 171(C), pages 1217-1228.
    5. Liming Deng & Wenjing Shen & Kangkang Xu & Xuhui Zhang, 2024. "An Adaptive Modeling Method for the Prognostics of Lithium-Ion Batteries on Capacity Degradation and Regeneration," Energies, MDPI, vol. 17(7), pages 1-15, April.
    6. Pietro Iurilli & Luigi Luppi & Claudio Brivio, 2022. "Non-Invasive Detection of Lithium-Metal Battery Degradation," Energies, MDPI, vol. 15(19), pages 1-14, September.
    7. Ardizzon, G. & Cavazzini, G. & Pavesi, G., 2014. "A new generation of small hydro and pumped-hydro power plants: Advances and future challenges," Renewable and Sustainable Energy Reviews, Elsevier, vol. 31(C), pages 746-761.
    8. Li, Guanzheng & Li, Bin & Li, Chao & Wang, Shuai, 2023. "State-of-health rapid estimation for lithium-ion battery based on an interpretable stacking ensemble model with short-term voltage profiles," Energy, Elsevier, vol. 263(PE).
    9. Liu, Jin-Long & Wang, Jian-Hua, 2015. "Thermodynamic analysis of a novel tri-generation system based on compressed air energy storage and pneumatic motor," Energy, Elsevier, vol. 91(C), pages 420-429.
    10. Zhang, Junwei & Zhang, Weige & Sun, Bingxiang & Zhang, Yanru & Fan, Xinyuan & Zhao, Bo, 2024. "A novel method of battery pack energy health estimation based on visual feature learning," Energy, Elsevier, vol. 293(C).
    11. Li, Yi & Liu, Kailong & Foley, Aoife M. & Zülke, Alana & Berecibar, Maitane & Nanini-Maury, Elise & Van Mierlo, Joeri & Hoster, Harry E., 2019. "Data-driven health estimation and lifetime prediction of lithium-ion batteries: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 113(C), pages 1-1.
    12. Xu, Ying & Ren, Li & Zhang, Zhongping & Tang, Yuejin & Shi, Jing & Xu, Chen & Li, Jingdong & Pu, Dongsheng & Wang, Zhuang & Liu, Huajun & Chen, Lei, 2018. "Analysis of the loss and thermal characteristics of a SMES (Superconducting Magnetic Energy Storage) magnet with three practical operating conditions," Energy, Elsevier, vol. 143(C), pages 372-384.
    13. Sick, Nathalie & Preschitschek, Nina & Leker, Jens & Bröring, Stefanie, 2019. "A new framework to assess industry convergence in high technology environments," Technovation, Elsevier, vol. 84, pages 48-58.
    14. Andre T. Puati Zau & Mpho J. Lencwe & S. P. Daniel Chowdhury & Thomas O. Olwal, 2022. "A Battery Management Strategy in a Lead-Acid and Lithium-Ion Hybrid Battery Energy Storage System for Conventional Transport Vehicles," Energies, MDPI, vol. 15(7), pages 1-29, April.
    15. Zhao, Yongliang & Song, Jian & Liu, Ming & Zhao, Yao & Olympios, Andreas V. & Sapin, Paul & Yan, Junjie & Markides, Christos N., 2022. "Thermo-economic assessments of pumped-thermal electricity storage systems employing sensible heat storage materials," Renewable Energy, Elsevier, vol. 186(C), pages 431-456.
    16. Jing Hou & He He & Yan Yang & Tian Gao & Yifan Zhang, 2019. "A Variational Bayesian and Huber-Based Robust Square Root Cubature Kalman Filter for Lithium-Ion Battery State of Charge Estimation," Energies, MDPI, vol. 12(9), pages 1-23, May.
    17. 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).
    18. Hu, Chunsheng & Ma, Liang & Guo, Shanshan & Guo, Gangsheng & Han, Zhiqiang, 2022. "Deep learning enabled state-of-charge estimation of LiFePO4 batteries: A systematic validation on state-of-the-art charging protocols," Energy, Elsevier, vol. 246(C).
    19. Al-Zareer, Maan & Dincer, Ibrahim & Rosen, Marc A., 2017. "Analysis and assessment of novel liquid air energy storage system with district heating and cooling capabilities," Energy, Elsevier, vol. 141(C), pages 792-802.
    20. Anuta, Oghenetejiri Harold & Taylor, Phil & Jones, Darren & McEntee, Tony & Wade, Neal, 2014. "An international review of the implications of regulatory and electricity market structures on the emergence of grid scale electricity storage," Renewable and Sustainable Energy Reviews, Elsevier, vol. 38(C), pages 489-508.

    More about this item

    Keywords

    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:energy:v:337:y:2025:i:c:s0360544225040691. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/energy .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.