IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v12y2020i20p8544-d428739.html
   My bibliography  Save this article

Scale-Up of Physics-Based Models for Predicting Degradation of Large Lithium Ion Batteries

Author

Listed:
  • Hong-Keun Kim

    (Department of Mechanical & Aerospace Engineering, Seoul National University, Seoul 151-744, Korea
    Current address: Chemical Sciences and Engineering Division, Argonne National Laboratory, Lemont, IL 60439, USA.)

  • Kyu-Jin Lee

    (Department of Mechanical Engineering, Myongji University, Yongin 448-728, Korea)

Abstract

Large lithium-ion batteries (LIBs) demonstrate different performance and lifetime compared to small LIB cells, owing to the size effects generated by the electrical configuration and property imbalance. However, the calculation time for performing life predictions with three-dimensional (3D) cell models is undesirably long. In this paper, a lumped cell model with equivalent resistances (LER cell model) is proposed as a reduced order model of the 3D cell model, which enables accurate and fast life predictions of large LIBs. The developed LER cell model is validated via the comparisons with results of the 3D cell models by simulating a 20-Ah commercial pouch cell (NCM/graphite) and the experimental values. In addition, the LER cell models are applied to different cell types and sizes, such as a 20-Ah cylindrical cell and a 60-Ah pouch cell.

Suggested Citation

  • Hong-Keun Kim & Kyu-Jin Lee, 2020. "Scale-Up of Physics-Based Models for Predicting Degradation of Large Lithium Ion Batteries," Sustainability, MDPI, vol. 12(20), pages 1-18, October.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:20:p:8544-:d:428739
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/12/20/8544/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/12/20/8544/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Polterovich, Victor & Popov, Vladimir, 2006. "Эволюционная Теория Экономической Политики: Часть I: Опыт Быстрого Развития [An Evolutionary Theory of Economic Policy: Part I: The Experience of Fast Development]," MPRA Paper 22168, University Library of Munich, Germany.
    2. Zhang, Cheng & Allafi, Walid & Dinh, Quang & Ascencio, Pedro & Marco, James, 2018. "Online estimation of battery equivalent circuit model parameters and state of charge using decoupled least squares technique," Energy, Elsevier, vol. 142(C), pages 678-688.
    3. Xiong, Rui & Tian, Jinpeng & Mu, Hao & Wang, Chun, 2017. "A systematic model-based degradation behavior recognition and health monitoring method for lithium-ion batteries," Applied Energy, Elsevier, vol. 207(C), pages 372-383.
    4. Deng, Zhongwei & Deng, Hao & Yang, Lin & Cai, Yishan & Zhao, Xiaowei, 2017. "Implementation of reduced-order physics-based model and multi-parameters identification strategy for lithium-ion battery," Energy, Elsevier, vol. 138(C), pages 509-519.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Kim, Hong-Keun & Lee, Kyu-Jin, 2023. "Use of a multiphysics model to investigate the performance and degradation of lithium-ion battery packs with different electrical configurations," Energy, Elsevier, vol. 262(PB).

    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. Berrueta, Alberto & Urtasun, Andoni & Ursúa, Alfredo & Sanchis, Pablo, 2018. "A comprehensive model for lithium-ion batteries: From the physical principles to an electrical model," Energy, Elsevier, vol. 144(C), pages 286-300.
    2. Kritana Prueksakorn & Cheng-Xu Piao & Hyunchul Ha & Taehyeung Kim, 2015. "Computational and Experimental Investigation for an Optimal Design of Industrial Windows to Allow Natural Ventilation during Wind-Driven Rain," Sustainability, MDPI, vol. 7(8), pages 1-22, August.
    3. Yirigui Yirigui & Sang-Woo Lee & A. Pouyan Nejadhashemi & Matthew R. Herman & Jong-Won Lee, 2019. "Relationships between Riparian Forest Fragmentation and Biological Indicators of Streams," Sustainability, MDPI, vol. 11(10), pages 1-24, May.
    4. Vladimir Popov, 2009. "Why the West Became Rich before China and Why China Has Been Catching Up with the West since 1949: nother Explanation of the “Great Divergence” and “Great Convergence” Stories," Working Papers w0132, New Economic School (NES).
    5. Hao Sun & Bo Jiang & Heze You & Bojian Yang & Xueyuan Wang & Xuezhe Wei & Haifeng Dai, 2021. "Quantitative Analysis of Degradation Modes of Lithium-Ion Battery under Different Operating Conditions," Energies, MDPI, vol. 14(2), pages 1-19, January.
    6. George Pavlidis & Vassilios A. Tsihrintzis, 2018. "Environmental Benefits and Control of Pollution to Surface Water and Groundwater by Agroforestry Systems: a Review," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(1), pages 1-29, January.
    7. 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).
    8. Grzegorz W. Kolodko, 2009. "A Two-thirds Rate of Success: Polish Transformation and Economic Development, 1989-2008," WIDER Working Paper Series RP2009-14, World Institute for Development Economic Research (UNU-WIDER).
    9. Kudrin, A. & Gurvich, E., 2015. "Government Stimulus or Economic Incentives?," Journal of the New Economic Association, New Economic Association, vol. 26(2), pages 179-186.
    10. Ghorbanzadeh, Milad & Astaneh, Majid & Golzar, Farzin, 2019. "Long-term degradation based analysis for lithium-ion batteries in off-grid wind-battery renewable energy systems," Energy, Elsevier, vol. 166(C), pages 1194-1206.
    11. Zhang, Yajun & Liu, Yajie & Wang, Jia & Zhang, Tao, 2022. "State-of-health estimation for lithium-ion batteries by combining model-based incremental capacity analysis with support vector regression," Energy, Elsevier, vol. 239(PB).
    12. Larysa Tamilina & Natalya Tamilina, 2014. "Heterogeneity in Institutional Effects on Economic Growth: Theory and Empirical Evidence," European Journal of Comparative Economics, Cattaneo University (LIUC), vol. 11(2), pages 205-249, December.
    13. Popov, Vladimir, 2015. "Разрыв Между Югом И Западом По Уровню Экономического Развития Сокращается? [Catching up: Developing countries in pursuit of growth]," MPRA Paper 65893, University Library of Munich, Germany.
    14. Costanzo, Vincenzo & Yao, Runming & Xu, Tiantian & Xiong, Jie & Zhang, Qiulei & Li, Baizhan, 2019. "Natural ventilation potential for residential buildings in a densely built-up and highly polluted environment. A case study," Renewable Energy, Elsevier, vol. 138(C), pages 340-353.
    15. Simachev, Yuri & Kuzyk, Mikhail & Ivanov, Denis, 2012. "Fostering innovation in Russian companies in the post-crisis period: Opportunities and constraints," MPRA Paper 41284, University Library of Munich, Germany.
    16. Aijuan Li & Wanzhong Zhao & Xibo Wang & Xuyun Qiu, 2018. "ACT-R Cognitive Model Based Trajectory Planning Method Study for Electric Vehicle’s Active Obstacle Avoidance System," Energies, MDPI, vol. 11(1), pages 1-21, January.
    17. Sturm, J. & Ennifar, H. & Erhard, S.V. & Rheinfeld, A. & Kosch, S. & Jossen, A., 2018. "State estimation of lithium-ion cells using a physicochemical model based extended Kalman filter," Applied Energy, Elsevier, vol. 223(C), pages 103-123.
    18. Ma, Zeyu & Yang, Ruixin & Wang, Zhenpo, 2019. "A novel data-model fusion state-of-health estimation approach for lithium-ion batteries," Applied Energy, Elsevier, vol. 237(C), pages 836-847.
    19. VADIM Ponkratov & В. Понкратов В., 2015. "Ресурсный Потенциал Нефтегазовой Отрасли Промышленности России И Стимулирование Повышения Эффективности Его Использования // Towards A More Efficient Use Of The Resource Potential Of The Russian Oil A," Экономика. Налоги. Право // Economics, taxes & law, ФГОБУ "Финансовый университет при Правительстве Российской Федерации" // Financial University under The Government of Russian Federation, issue 3, pages 94-101.
    20. Jagdesh Kumar & Chethan Parthasarathy & Mikko Västi & Hannu Laaksonen & Miadreza Shafie-Khah & Kimmo Kauhaniemi, 2020. "Sizing and Allocation of Battery Energy Storage Systems in Åland Islands for Large-Scale Integration of Renewables and Electric Ferry Charging Stations," Energies, MDPI, vol. 13(2), pages 1-23, January.

    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:gam:jsusta:v:12:y:2020:i:20:p:8544-:d:428739. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.