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Capacity Fade in Lithium-Ion Batteries and Cyclic Aging over Various State-of-Charge Ranges

Author

Listed:
  • Sophia Gantenbein

    (Institute for Applied Materials (IAM-WET), Karlsruhe Institute of Technology (KIT), 76131 Karlsruhe, Germany)

  • Michael Schönleber

    (Institute for Applied Materials (IAM-WET), Karlsruhe Institute of Technology (KIT), 76131 Karlsruhe, Germany)

  • Michael Weiss

    (Institute for Applied Materials (IAM-WET), Karlsruhe Institute of Technology (KIT), 76131 Karlsruhe, Germany)

  • Ellen Ivers-Tiffée

    (Institute for Applied Materials (IAM-WET), Karlsruhe Institute of Technology (KIT), 76131 Karlsruhe, Germany)

Abstract

In order to develop long-lifespan batteries, it is of utmost importance to identify the relevant aging mechanisms and their relation to operating conditions. The capacity loss in a lithium-ion battery originates from (i) a loss of active electrode material and (ii) a loss of active lithium. The focus of this work is the capacity loss caused by lithium loss, which is irreversibly bound to the solid electrolyte interface (SEI) on the graphite surface. During operation, the particle surface suffers from dilation, which causes the SEI to break and then be rebuilt, continuously. The surface dilation is expected to correspond with the well-known graphite staging mechanism. Therefore, a high-power 2.6 Ah graphite/LiNiCoAlO 2 cell (Sony US18650VTC5) is cycled at different, well-defined state-of-charge (SOC) ranges, covering the different graphite stages. An open circuit voltage model is applied to quantify the loss mechanisms (i) and (ii). The results show that the lithium loss is the dominant cause of capacity fade under the applied conditions. They experimentally prove the important influence of the graphite stages on the lifetime of a battery. Cycling the cell at SOCs slightly above graphite Stage II results in a high active lithium loss and hence in a high capacity fade.

Suggested Citation

  • Sophia Gantenbein & Michael Schönleber & Michael Weiss & Ellen Ivers-Tiffée, 2019. "Capacity Fade in Lithium-Ion Batteries and Cyclic Aging over Various State-of-Charge Ranges," Sustainability, MDPI, vol. 11(23), pages 1-15, November.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:23:p:6697-:d:291214
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    Citations

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    Cited by:

    1. Davide Clerici & Francesco Mocera & Aurelio Somà, 2020. "Analytical Solution for Coupled Diffusion Induced Stress Model for Lithium-Ion Battery," Energies, MDPI, vol. 13(7), pages 1-20, April.
    2. Nickolay I. Shchurov & Sergey I. Dedov & Boris V. Malozyomov & Alexander A. Shtang & Nikita V. Martyushev & Roman V. Klyuev & Sergey N. Andriashin, 2021. "Degradation of Lithium-Ion Batteries in an Electric Transport Complex," Energies, MDPI, vol. 14(23), pages 1-33, December.
    3. Xingxing Wang & Yujie Zhang & Hongjun Ni & Shuaishuai Lv & Fubao Zhang & Yu Zhu & Yinnan Yuan & Yelin Deng, 2022. "Influence of Different Ambient Temperatures on the Discharge Performance of Square Ternary Lithium-Ion Batteries," Energies, MDPI, vol. 15(15), pages 1-22, July.
    4. Wang, Shunli & Takyi-Aninakwa, Paul & Jin, Siyu & Yu, Chunmei & Fernandez, Carlos & Stroe, Daniel-Ioan, 2022. "An improved feedforward-long short-term memory modeling method for the whole-life-cycle state of charge prediction of lithium-ion batteries considering current-voltage-temperature variation," Energy, Elsevier, vol. 254(PA).
    5. Ethelbert Ezemobi & Andrea Tonoli & Mario Silvagni, 2021. "Battery State of Health Estimation with Improved Generalization Using Parallel Layer Extreme Learning Machine," Energies, MDPI, vol. 14(8), pages 1-15, April.
    6. Jie Xing & Peng Wu, 2021. "State of Charge Estimation of Lithium-Ion Battery Based on Improved Adaptive Unscented Kalman Filter," Sustainability, MDPI, vol. 13(9), pages 1-16, April.

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