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Computer simulations of the influence of geometry in the performance of conventional and unconventional lithium-ion batteries

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  • Miranda, D.
  • Costa, C.M.
  • Almeida, A.M.
  • Lanceros-Méndez, S.

Abstract

In order to optimize battery performance, different geometries have been evaluated taking into account their suitability for different applications. These different geometries include conventional, interdigitated batteries and unconventional geometries such as horseshoe, spiral, ring, antenna and gear batteries. The geometry optimization was performed by the finite element method, applying the Doyle/Fuller/Newman model. At 330C, the capacity values for conventional, ring, spiral, horseshoe, gear and interdigitated geometries are 0.58Ahm−2, 149Ahm−2, 182Ahm−2, 216Ahm−2, 289Ahm−2 and 318Ahm−2, respectively.

Suggested Citation

  • Miranda, D. & Costa, C.M. & Almeida, A.M. & Lanceros-Méndez, S., 2016. "Computer simulations of the influence of geometry in the performance of conventional and unconventional lithium-ion batteries," Applied Energy, Elsevier, vol. 165(C), pages 318-328.
    • Handle: RePEc:eee:appene:v:165:y:2016:i:c:p:318-328
    DOI: 10.1016/j.apenergy.2015.12.068
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    References listed on IDEAS

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    Cited by:

    1. Miranda, D. & Costa, C.M. & Almeida, A.M. & Lanceros-Méndez, S., 2018. "Computer simulation of the influence of thermal conditions on the performance of conventional and unconventional lithium-ion battery geometries," Energy, Elsevier, vol. 149(C), pages 262-278.
    2. Jiang, Z.Y. & Qu, Z.G. & Zhou, L. & Tao, W.Q., 2017. "A microscopic investigation of ion and electron transport in lithium-ion battery porous electrodes using the lattice Boltzmann method," Applied Energy, Elsevier, vol. 194(C), pages 530-539.
    3. Feng, Xuning & Zheng, Siqi & Ren, Dongsheng & He, Xiangming & Wang, Li & Cui, Hao & Liu, Xiang & Jin, Changyong & Zhang, Fangshu & Xu, Chengshan & Hsu, Hungjen & Gao, Shang & Chen, Tianyu & Li, Yalun , 2019. "Investigating the thermal runaway mechanisms of lithium-ion batteries based on thermal analysis database," Applied Energy, Elsevier, vol. 246(C), pages 53-64.
    4. Liu, Binghe & Yin, Sha & Xu, Jun, 2016. "Integrated computation model of lithium-ion battery subject to nail penetration," Applied Energy, Elsevier, vol. 183(C), pages 278-289.
    5. Miranda, D. & Almeida, A.M. & Lanceros-Méndez, S. & Costa, C.M., 2019. "Effect of the active material type and battery geometry on the thermal behavior of lithium-ion batteries," Energy, Elsevier, vol. 185(C), pages 1250-1262.
    6. Li, Xue & Jiang, Jiuchun & Wang, Le Yi & Chen, Dafen & Zhang, Yanru & Zhang, Caiping, 2016. "A capacity model based on charging process for state of health estimation of lithium ion batteries," Applied Energy, Elsevier, vol. 177(C), pages 537-543.

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