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Influence of connecting plate resistance upon LiFePO4 battery performance

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  • Wang, Limei
  • Cheng, Yong
  • Zhao, Xiuliang

Abstract

The primary challenge to the commercialization of any electric vehicle is the performance management of the battery pack. The performance of the battery module is influenced by the resistance of the inter-cell connecting plates (ICCP) and the position of the battery module posts (BMP). A new battery cell model based on the Matlab–Simscape platform is developed and validated using a constant current discharge test and a pulse discharge test. Taken the ICCP as resistors, a parallel-connected battery module model (PCBMM) is established based on the battery cell model. The effect of inter-cell connecting plate resistance (ICCPR) on the battery module performance is simulated. Simulation results indicate that the ICCPR causes unevenly current flow among the battery cells. The battery cell directly connected to the BMP is the first one reaching its end-of-discharge (EOD) voltage. Also, it presents the lowest terminal voltage and state of charge (SOC) during the discharge process. The battery cell directly connected to the BMP goes into deep discharge state more easily. Therefore, it performs higher aging rate. The aging of the battery cell causes over-discharge of the adjacent battery cells. The reasonable ratio of the ICCPR to the battery ohmic internal resistance (OIR) is discussed for different average currents and different numbers of battery cells, to guarantee the maximum SOC evaluation error within a target value of 0.05.

Suggested Citation

  • Wang, Limei & Cheng, Yong & Zhao, Xiuliang, 2015. "Influence of connecting plate resistance upon LiFePO4 battery performance," Applied Energy, Elsevier, vol. 147(C), pages 353-360.
    • Handle: RePEc:eee:appene:v:147:y:2015:i:c:p:353-360
    DOI: 10.1016/j.apenergy.2015.03.016
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    Cited by:

    1. Ma, Mina & Wang, Yu & Duan, Qiangling & Wu, Tangqin & Sun, Jinhua & Wang, Qingsong, 2018. "Fault detection of the connection of lithium-ion power batteries in series for electric vehicles based on statistical analysis," Energy, Elsevier, vol. 164(C), pages 745-756.
    2. Chen, Haosen & Fan, Jinbao & Zhang, Mingliang & Feng, Xiaolong & Zhong, Ximing & He, Jianchao & Ai, Shigang, 2023. "Mechanism of inhomogeneous deformation and equal-stiffness design of large-format prismatic lithium-ion batteries," Applied Energy, Elsevier, vol. 332(C).
    3. Hua Zhang & Lei Pei & Jinlei Sun & Kai Song & Rengui Lu & Yongping Zhao & Chunbo Zhu & Tiansi Wang, 2016. "Online Diagnosis for the Capacity Fade Fault of a Parallel-Connected Lithium Ion Battery Group," Energies, MDPI, vol. 9(5), pages 1-18, May.
    4. Xiong, Rui & Sun, Wanzhou & Yu, Quanqing & Sun, Fengchun, 2020. "Research progress, challenges and prospects of fault diagnosis on battery system of electric vehicles," Applied Energy, Elsevier, vol. 279(C).
    5. Wang, Shunli & Shang, Liping & Li, Zhanfeng & Deng, Hu & Li, Jianchao, 2016. "Online dynamic equalization adjustment of high-power lithium-ion battery packs based on the state of balance estimation," Applied Energy, Elsevier, vol. 166(C), pages 44-58.
    6. Lv, Jie & Lin, Shili & Song, Wenji & Chen, Mingbiao & Feng, Ziping & Li, Yongliang & Ding, Yulong, 2019. "Performance of LiFePO4 batteries in parallel based on connection topology," Applied Energy, Elsevier, vol. 252(C), pages 1-1.
    7. Kim, Kyunghyun & Choi, Jung-Il, 2023. "Effect of cell-to-cell variation and module configuration on the performance of lithium-ion battery systems," Applied Energy, Elsevier, vol. 352(C).
    8. Li, Changlong & Cui, Naxin & Chang, Long & Cui, Zhongrui & Yuan, Haitao & Zhang, Chenghui, 2022. "Effect of parallel connection topology on air-cooled lithium-ion battery module: Inconsistency analysis and comprehensive evaluation," Applied Energy, Elsevier, vol. 313(C).
    9. Liu, Xinhua & Ai, Weilong & Naylor Marlow, Max & Patel, Yatish & Wu, Billy, 2019. "The effect of cell-to-cell variations and thermal gradients on the performance and degradation of lithium-ion battery packs," Applied Energy, Elsevier, vol. 248(C), pages 489-499.
    10. Wang, Limei & Pan, Chaofeng & Liu, Liang & Cheng, Yong & Zhao, Xiuliang, 2016. "On-board state of health estimation of LiFePO4 battery pack through differential voltage analysis," Applied Energy, Elsevier, vol. 168(C), pages 465-472.

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