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Application of Variable-Order Fractional Calculus to the Modeling of Calendar Aging in Lithium-Ion Batteries

Author

Listed:
  • Juan Antonio López-Villanueva

    (Department of Electronics and Computer Technology, CITIC, 18071 Granada, Spain)

  • Pablo Rodríguez-Iturriaga

    (Department of Electronics and Computer Technology, 18071 Granada, Spain)

  • Luis Parrilla

    (Department of Electronics and Computer Technology, 18071 Granada, Spain)

  • Salvador Rodríguez-Bolívar

    (Department of Electronics and Computer Technology, CITIC, 18071 Granada, Spain)

Abstract

Battery aging is one of the key challenges that electrochemical energy storage faces. Models for both cycling and calendar aging are valuable for quantitatively assessing their contribution to overall capacity loss. Since batteries are stored and employed under varying conditions of temperature and state of charge in their real-life operation, the availability of a suitable model to anticipate the outcome of calendar aging in lithium-ion batteries under dynamic conditions is of great interest. In this article, we extend a novel model to predict the capacity loss due to calendar aging by using variable-order fractional calculus. For this purpose, some theoretical difficulties posed by variable-order definitions are discussed and compared by applying them to fit experimental results with a multi-parameter optimization procedure. We show that employing a variable-order model allows for a significant improvement in accuracy and predictive ability with respect to its constant-order counterpart. We conclude that variable-order models constitute an interesting alternative for reproducing complex behavior in dynamical systems, such as aging in lithium-ion batteries.

Suggested Citation

  • Juan Antonio López-Villanueva & Pablo Rodríguez-Iturriaga & Luis Parrilla & Salvador Rodríguez-Bolívar, 2023. "Application of Variable-Order Fractional Calculus to the Modeling of Calendar Aging in Lithium-Ion Batteries," Energies, MDPI, vol. 16(5), pages 1-18, March.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:5:p:2484-:d:1088477
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    References listed on IDEAS

    as
    1. Daniele Stampatori & Pier Paolo Raimondi & Michel Noussan, 2020. "Li-Ion Batteries: A Review of a Key Technology for Transport Decarbonization," Energies, MDPI, vol. 13(10), pages 1-23, May.
    2. de Hoog, Joris & Timmermans, Jean-Marc & Ioan-Stroe, Daniel & Swierczynski, Maciej & Jaguemont, Joris & Goutam, Shovon & Omar, Noshin & Van Mierlo, Joeri & Van Den Bossche, Peter, 2017. "Combined cycling and calendar capacity fade modeling of a Nickel-Manganese-Cobalt Oxide Cell with real-life profile validation," Applied Energy, Elsevier, vol. 200(C), pages 47-61.
    3. Petit, Martin & Prada, Eric & Sauvant-Moynot, Valérie, 2016. "Development of an empirical aging model for Li-ion batteries and application to assess the impact of Vehicle-to-Grid strategies on battery lifetime," Applied Energy, Elsevier, vol. 172(C), pages 398-407.
    4. 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.
    5. Gert Berckmans & Maarten Messagie & Jelle Smekens & Noshin Omar & Lieselot Vanhaverbeke & Joeri Van Mierlo, 2017. "Cost Projection of State of the Art Lithium-Ion Batteries for Electric Vehicles Up to 2030," Energies, MDPI, vol. 10(9), pages 1-20, September.
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