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A Physical-Based Electro-Thermal Model for a Prismatic LFP Lithium-Ion Cell Thermal Analysis

Author

Listed:
  • Alberto Broatch

    (CMT—Clean Mobility and Thermofluids, Universitat Politècnica de València, Camino de Vera s/n, 46022 Valencia, Spain)

  • Pablo Olmeda

    (CMT—Clean Mobility and Thermofluids, Universitat Politècnica de València, Camino de Vera s/n, 46022 Valencia, Spain)

  • Xandra Margot

    (CMT—Clean Mobility and Thermofluids, Universitat Politècnica de València, Camino de Vera s/n, 46022 Valencia, Spain)

  • Luca Agizza

    (CMT—Clean Mobility and Thermofluids, Universitat Politècnica de València, Camino de Vera s/n, 46022 Valencia, Spain)

Abstract

This article presents an electro-thermal model of a prismatic lithium-ion cell, integrating physics-based models for capacity and resistance estimation. A 100 Ah prismatic cell with LFP-based chemistry was selected for analysis. A comprehensive experimental campaign was conducted to determine electrical parameters and assess their dependencies on temperature and C-rate. Capacity tests were conducted to characterize the cell’s capacity, while an OCV test was used to evaluate its open circuit voltage. Additionally, Hybrid Pulse Power Characterization tests were performed to determine the cell’s internal resistive-capacitive parameters. To describe the temperature dependence of the cell’s capacity, a physics-based Galushkin model is proposed. An Arrhenius model is used to represent the temperature dependence of resistances. The integration of physics-based models significantly reduces the required test matrix for model calibration, as temperature-dependent behavior is effectively predicted. The electrical response is represented using a first-order equivalent circuit model, while thermal behavior is described through a nodal network thermal model. Model validation was conducted under real driving emissions cycles at various temperatures, achieving a root mean square error below 1% in all cases. Furthermore, a comparative study of different cell cooling strategies is presented to identify the most effective approach for temperature control during ultra-fast charging. The results show that side cooling achieves a 36% lower temperature at the end of the charging process compared to base cooling.

Suggested Citation

  • Alberto Broatch & Pablo Olmeda & Xandra Margot & Luca Agizza, 2025. "A Physical-Based Electro-Thermal Model for a Prismatic LFP Lithium-Ion Cell Thermal Analysis," Energies, MDPI, vol. 18(5), pages 1-29, March.
  • Handle: RePEc:gam:jeners:v:18:y:2025:i:5:p:1281-:d:1606018
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    References listed on IDEAS

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    1. Fuad Un-Noor & Sanjeevikumar Padmanaban & Lucian Mihet-Popa & Mohammad Nurunnabi Mollah & Eklas Hossain, 2017. "A Comprehensive Study of Key Electric Vehicle (EV) Components, Technologies, Challenges, Impacts, and Future Direction of Development," Energies, MDPI, vol. 10(8), pages 1-84, August.
    2. Anna I. Pózna & Katalin M. Hangos & Attila Magyar, 2019. "Temperature Dependent Parameter Estimation of Electrical Vehicle Batteries," Energies, MDPI, vol. 12(19), pages 1-18, September.
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