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Research on electrochemical characteristics and heat generating properties of power battery based on multi-time scales

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  • Wu, Tingting
  • Wang, Changhong
  • Hu, Yanxin
  • Liang, Zhixuan
  • Fan, Changxiang

Abstract

A comprehensive understanding of the mechanisms of battery is essential for the design of thermal management systems. In this work, a second-order equivalent circuit model considering the hysteresis effect of the battery was developed, and a combined EIS and HPPC characterization method was used for parameter identification. The results showed that the combining EIS and HPPC parameter measurement methods could extract and analyze the parameters of the battery with different time scales and improve the accuracy of the model. It was found that the polarization internal resistance (R1 and R2) of the battery shows a stronger temperature dependence than the ohmic internal resistance at low temperatures, with R1 being about 170 times higher at low temperatures (10 °C) than high temperatures (50 °C). At the same temperature, τ2 was approximately 100 times larger than τ1, which was two orders of magnitude difference between τ1 and τ2. In addition, the dynamic heat generation results showed that the heat generation rate of the battery increases with decreasing temperature. At 3C discharge rate, the heat generation rate of the battery at low temperature (−10 °C) was about 1.5 times higher than at room temperature (25 °C).

Suggested Citation

  • Wu, Tingting & Wang, Changhong & Hu, Yanxin & Liang, Zhixuan & Fan, Changxiang, 2023. "Research on electrochemical characteristics and heat generating properties of power battery based on multi-time scales," Energy, Elsevier, vol. 265(C).
    • Handle: RePEc:eee:energy:v:265:y:2023:i:c:s0360544222033023
    DOI: 10.1016/j.energy.2022.126416
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    References listed on IDEAS

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    1. Huang, Deyang & Chen, Ziqiang & Zhou, Shiyao, 2021. "Model prediction-based battery-powered heating method for series-connected lithium-ion battery pack working at extremely cold temperatures," Energy, Elsevier, vol. 216(C).
    2. Liu, Huaqiang & Ahmad, Shakeel & Shi, Yu & Zhao, Jiyun, 2021. "A parametric study of a hybrid battery thermal management system that couples PCM/copper foam composite with helical liquid channel cooling," Energy, Elsevier, vol. 231(C).
    3. Solai, Elie & Guadagnini, Maxime & Beaugendre, Héloïse & Daccord, Rémi & Congedo, Pietro, 2022. "Validation of a data-driven fast numerical model to simulate the immersion cooling of a lithium-ion battery pack," Energy, Elsevier, vol. 249(C).
    4. Qin, Yudi & Du, Jiuyu & Lu, Languang & Gao, Ming & Haase, Frank & Li, Jianqiu & Ouyang, Minggao, 2020. "A rapid lithium-ion battery heating method based on bidirectional pulsed current: Heating effect and impact on battery life," Applied Energy, Elsevier, vol. 280(C).
    5. Leng, Ziyu & Yuan, Yanping & Cao, Xiaoling & Zeng, Chao & Zhong, Wei & Gao, Bo, 2022. "Heat pipe/phase change material thermal management of Li-ion power battery packs: A numerical study on coupled heat transfer performance," Energy, Elsevier, vol. 240(C).
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    Cited by:

    1. Yetik, Ozge & Morali, Ugur & Karakoc, Tahir Hikmet, 2023. "A numerical study of thermal management of lithium-ion battery with nanofluid," Energy, Elsevier, vol. 284(C).
    2. Zha, Yunfei & He, Shunquan & Meng, Xianfeng & Zuo, Hongyan & Zhao, Xiaohuan, 2023. "Heat dissipation performance research between drop contact and immersion contact of lithium-ion battery cooling," Energy, Elsevier, vol. 279(C).
    3. Liu, Yongjie & Huang, Zhiwu & He, Liang & Pan, Jianping & Li, Heng & Peng, Jun, 2023. "Temperature-aware charging strategy for lithium-ion batteries with adaptive current sequences in cold environments," Applied Energy, Elsevier, vol. 352(C).
    4. Lin, Mingqiang & Wu, Jian & Meng, Jinhao & Wang, Wei & Wu, Ji, 2023. "State of health estimation with attentional long short-term memory network for lithium-ion batteries," Energy, Elsevier, vol. 268(C).

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