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Optimization Approaches for Cost and Lifetime Improvements of Lithium-Ion Batteries in Electric Vehicle Powertrains

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  • Aissam Riad Meddour

    (Laboratoire des Systèmes et Energies Embarqués pour les Transports, Higher School of Aeronautical Techniques and Automobile Construction (ESTACA), Parc Universitaire Laval-Changé, Rue Georges Charpak, 53000 Laval, France)

  • Nassim Rizoug

    (Laboratoire des Systèmes et Energies Embarqués pour les Transports, Higher School of Aeronautical Techniques and Automobile Construction (ESTACA), Parc Universitaire Laval-Changé, Rue Georges Charpak, 53000 Laval, France)

  • Patrick Leserf

    (Laboratoire des Systèmes et Energies Embarqués pour les Transports, Higher School of Aeronautical Techniques and Automobile Construction (ESTACA), Parc Universitaire Laval-Changé, Rue Georges Charpak, 53000 Laval, France)

  • Christopher Vagg

    (Department of Mechanical Engineering, University of Bath, Claverton Down, Bath BA2 7AY, UK)

  • Richard Burke

    (Department of Mechanical Engineering, University of Bath, Claverton Down, Bath BA2 7AY, UK)

  • Cherif Larouci

    (Laboratoire des Systèmes et Energies Embarqués pour les Transports, Higher School of Aeronautical Techniques and Automobile Construction (ESTACA), Parc Universitaire Laval-Changé, Rue Georges Charpak, 53000 Laval, France)

Abstract

With the increasing adoption of electric vehicles (EVs), optimizing lithium-ion battery capacity is critical for overall powertrain performance. Recent studies have optimized battery capacity in isolation without considering interactions with other powertrain components. Furthermore, even when the battery is considered within the full powertrain, most works have only modeled the electrical behavior without examining thermal or ageing dynamics. However, this fails to capture systemic impacts on overall performance. This study takes a holistic approach to investigate the effects of battery capacity optimization on convergence of the full EV powertrain. A battery multiphysics model was developed in MATLAB/Simulink, incorporating experimental data on electrical, thermal, and ageing dynamics and interactions with other components. The model was evaluated using real-world WLTP and Artemis driving cycles to simulate realistic conditions lacking in prior works. The findings reveal significant impacts of battery optimization on total powertrain performance unaccounted for in previous isolated studies. By adopting a system-level perspective and realistic driving cycles, this work provides enhanced understanding of interdependent trade-offs to inform integrated EV design.

Suggested Citation

  • Aissam Riad Meddour & Nassim Rizoug & Patrick Leserf & Christopher Vagg & Richard Burke & Cherif Larouci, 2023. "Optimization Approaches for Cost and Lifetime Improvements of Lithium-Ion Batteries in Electric Vehicle Powertrains," Energies, MDPI, vol. 16(18), pages 1-29, September.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:18:p:6535-:d:1237504
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    References listed on IDEAS

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    1. Emad Roshandel & Amin Mahmoudi & Solmaz Kahourzade & Amirmehdi Yazdani & GM Shafiullah, 2021. "Losses in Efficiency Maps of Electric Vehicles: An Overview," Energies, MDPI, vol. 14(22), pages 1-27, November.
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