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Comparison of the impact of fast charging on the cycle life of three lithium-ion cells under several parameters of charge protocol and temperatures

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  • Mathieu, Romain
  • Briat, Olivier
  • Gyan, Philippe
  • Vinassa, Jean-Michel

Abstract

Fast charging of lithium-ion batteries is crucial for electric vehicles. As the charge current is a known degradation factor, assessing the impact of fast charging on battery ageing under several operating conditions is necessary to derive usage strategies for system integrators. To bridge existing knowledge gaps, this article reports on a comparative experimental ageing study in fast charging conditions. Three cells, differing in their materials and energy densities, were investigated. The impacts of the following three parameters are compared on these cells: charge current, end-of-charge voltage, and ambient temperature. The results reveal that the impact of fast charging on cycle life strongly depends on battery materials and internal design. The degradation of two of the cells significantly increased when the charge current and voltage increased, whereas that of the third cell was nearly independent of these parameters. While considering thermal conditions, the ageing of each cell was minimised at a different temperature, either cold, moderate, or warm. An analysis of degradation root causes indicates that distinct dominant degradation mechanisms occurred depending on the cell materials. The cells with higher energy density had a lower cycle life (between 100 and 900 cycles) than the most high-power cell (more than 1700 cycles). Experimental results allow the identification of three strategies for reducing charging time while minimising battery degradation. These strategies present several contributions to the design of energy storage systems for electric vehicles, including the choice of a cell, design of thermal management systems, and design of optimised fast charging protocols.

Suggested Citation

  • Mathieu, Romain & Briat, Olivier & Gyan, Philippe & Vinassa, Jean-Michel, 2021. "Comparison of the impact of fast charging on the cycle life of three lithium-ion cells under several parameters of charge protocol and temperatures," Applied Energy, Elsevier, vol. 283(C).
  • Handle: RePEc:eee:appene:v:283:y:2021:i:c:s0306261920317268
    DOI: 10.1016/j.apenergy.2020.116344
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    References listed on IDEAS

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    1. Mathieu, Romain & Baghdadi, Issam & Briat, Olivier & Gyan, Philippe & Vinassa, Jean-Michel, 2017. "D-optimal design of experiments applied to lithium battery for ageing model calibration," Energy, Elsevier, vol. 141(C), pages 2108-2119.
    2. Jiang, Bo & Dai, Haifeng & Wei, Xuezhe, 2020. "Incremental capacity analysis based adaptive capacity estimation for lithium-ion battery considering charging condition," Applied Energy, Elsevier, vol. 269(C).
    3. Abdel-Monem, Mohamed & Trad, Khiem & Omar, Noshin & Hegazy, Omar & Van den Bossche, Peter & Van Mierlo, Joeri, 2017. "Influence analysis of static and dynamic fast-charging current profiles on ageing performance of commercial lithium-ion batteries," Energy, Elsevier, vol. 120(C), pages 179-191.
    4. Lin, Chun-Pang & Cabrera, Javier & Yang, Fangfang & Ling, Man-Ho & Tsui, Kwok-Leung & Bae, Suk-Joo, 2020. "Battery state of health modeling and remaining useful life prediction through time series model," Applied Energy, Elsevier, vol. 275(C).
    5. Weng, Caihao & Feng, Xuning & Sun, Jing & Peng, Huei, 2016. "State-of-health monitoring of lithium-ion battery modules and packs via incremental capacity peak tracking," Applied Energy, Elsevier, vol. 180(C), pages 360-368.
    6. Eddahech, Akram & Briat, Olivier & Vinassa, Jean-Michel, 2015. "Performance comparison of four lithium–ion battery technologies under calendar aging," Energy, Elsevier, vol. 84(C), pages 542-550.
    7. Mishra, Partha Pratim & Latif, Aadil & Emmanuel, Michael & Shi, Ying & McKenna, Killian & Smith, Kandler & Nagarajan, Adarsh, 2020. "Analysis of degradation in residential battery energy storage systems for rate-based use-cases," Applied Energy, Elsevier, vol. 264(C).
    8. Mathews, Ian & Xu, Bolun & He, Wei & Barreto, Vanessa & Buonassisi, Tonio & Peters, Ian Marius, 2020. "Technoeconomic model of second-life batteries for utility-scale solar considering calendar and cycle aging," Applied Energy, Elsevier, vol. 269(C).
    9. Waag, Wladislaw & Käbitz, Stefan & Sauer, Dirk Uwe, 2013. "Experimental investigation of the lithium-ion battery impedance characteristic at various conditions and aging states and its influence on the application," Applied Energy, Elsevier, vol. 102(C), pages 885-897.
    10. 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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    4. Sieg, Johannes & Schmid, Alexander U. & Rau, Laura & Gesterkamp, Andreas & Storch, Mathias & Spier, Bernd & Birke, Kai Peter & Sauer, Dirk Uwe, 2022. "Fast-charging capability of lithium-ion cells: Influence of electrode aging and electrolyte consumption," Applied Energy, Elsevier, vol. 305(C).
    5. Jia Guo & Yaqi Li & Kjeld Pedersen & Daniel-Ioan Stroe, 2021. "Lithium-Ion Battery Operation, Degradation, and Aging Mechanism in Electric Vehicles: An Overview," Energies, MDPI, vol. 14(17), pages 1-22, August.
    6. Hyeonchang Jeon & Seokmoo Hong & Jinwon Yun & Jaeyoung Han, 2023. "Cooling Strategy Optimization of Cylindrical Lithium-Ion Battery Pack via Multi-Counter Cooling Channels," Energies, MDPI, vol. 16(23), pages 1-30, November.
    7. Hyeonchang Jeon & Daeil Hyun & Hyuntae Lee & Seongjin Son & Jaeyoung Han, 2024. "Optimization of Blades and Impellers for Electric Vehicle Centrifugal Pumps via Numerical Analysis," Energies, MDPI, vol. 17(4), pages 1-16, February.
    8. Fan, Zhaohui & Fu, Yijie & Liang, Hong & Gao, Renjing & Liu, Shutian, 2023. "A module-level charging optimization method of lithium-ion battery considering temperature gradient effect of liquid cooling and charging time," Energy, Elsevier, vol. 265(C).

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