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Influence of Electrode Density on the Performance of Li-Ion Batteries: Experimental and Simulation Results

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  • Jelle Smekens

    (Vrije Universiteit Brussel (VUB), Pleinlaan 2, 1050 Elsene, Belgium)

  • Rahul Gopalakrishnan

    (Vrije Universiteit Brussel (VUB), Pleinlaan 2, 1050 Elsene, Belgium)

  • Nils Van den Steen

    (Vrije Universiteit Brussel (VUB), Pleinlaan 2, 1050 Elsene, Belgium)

  • Noshin Omar

    (Vrije Universiteit Brussel (VUB), Pleinlaan 2, 1050 Elsene, Belgium)

  • Omar Hegazy

    (Vrije Universiteit Brussel (VUB), Pleinlaan 2, 1050 Elsene, Belgium)

  • Annick Hubin

    (Vrije Universiteit Brussel (VUB), Pleinlaan 2, 1050 Elsene, Belgium)

  • Joeri Van Mierlo

    (Vrije Universiteit Brussel (VUB), Pleinlaan 2, 1050 Elsene, Belgium)

Abstract

Lithium-ion battery (LIB) technology further enabled the information revolution by powering smartphones and tablets, allowing these devices an unprecedented performance against reasonable cost. Currently, this battery technology is on the verge of carrying the revolution in road transport and energy storage of renewable energy. However, to fully succeed in the latter, a number of hurdles still need to be taken. Battery performance and lifetime constitute a bottleneck for electric vehicles as well as stationary electric energy storage systems to penetrate the market. Electrochemical battery models are one of the engineering tools which could be used to enhance their performance. These models can help us optimize the cell design and the battery management system. In this study, we evaluate the ability of the Porous Electrode Theory (PET) to predict the effect of changing positive electrode density in the overall performance of Li-ion battery cells. It can be concluded that Porous Electrode Theory (PET) is capable of predicting the difference in cell performance due to a changing positive electrode density.

Suggested Citation

  • Jelle Smekens & Rahul Gopalakrishnan & Nils Van den Steen & Noshin Omar & Omar Hegazy & Annick Hubin & Joeri Van Mierlo, 2016. "Influence of Electrode Density on the Performance of Li-Ion Batteries: Experimental and Simulation Results," Energies, MDPI, vol. 9(2), pages 1-12, February.
    • Handle: RePEc:gam:jeners:v:9:y:2016:i:2:p:104-:d:63761
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    References listed on IDEAS

    as
    1. Shovon Goutam & Jean-Marc Timmermans & Noshin Omar & Peter Van den Bossche & Joeri Van Mierlo, 2015. "Comparative Study of Surface Temperature Behavior of Commercial Li-Ion Pouch Cells of Different Chemistries and Capacities by Infrared Thermography," Energies, MDPI, vol. 8(8), pages 1-18, August.
    2. 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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    1. Gandoman, Foad H. & Ahmadi, Abdollah & Bossche, Peter Van den & Van Mierlo, Joeri & Omar, Noshin & Nezhad, Ali Esmaeel & Mavalizadeh, Hani & Mayet, Clément, 2019. "Status and future perspectives of reliability assessment for electric vehicles," Reliability Engineering and System Safety, Elsevier, vol. 183(C), pages 1-16.
    2. Xaviery N. Penisa & Michael T. Castro & Jethro Daniel A. Pascasio & Eugene A. Esparcia & Oliver Schmidt & Joey D. Ocon, 2020. "Projecting the Price of Lithium-Ion NMC Battery Packs Using a Multifactor Learning Curve Model," Energies, MDPI, vol. 13(20), pages 1-18, October.
    3. 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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