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A distributed parameter model of refrigerant-cooled multi-channel evaporator for battery thermal management

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  • Lu, Jingchao
  • Zhuang, Dawei
  • Ding, Guoliang
  • Li, Guang
  • Wang, Yueming

Abstract

Application of refrigerant-cooled multi-channel evaporators (MCEs) is a promising solution to cool electric vehicle batteries because the non-uniformly distributed heat from a battery can be efficiently dissipated by suitable arrangement of the multi-channels in an MCE. In order to provide a simulation tool for the design of an MCE, a distributed parameter model for quickly predicting the performance of an MCE at various channel arrangements and non-uniformly distributed heating conditions is useful, and thus it is developed in this study. In the model, heat and mass transfer in multiple flow paths in an MCE are separately described; the uneven mass flow distribution among these channels is predicted based on the pressure balance; each flow path is divided into multiple control volumes to reflect the non-uniformly distributed heating conditions; and the mass flow distribution among flow paths and the heat transfer in all the control volumes are jointly solved by a combined iteration algorithm of pressure drop and heat transfer. The proposed model is validated by experiments under the condition of battery heat flux ranging from 500 to 1500 W m−2. The results show that the prediction deviations of the average temperature and the highest temperature on the MCE surface from the experimental ones are 1.5 °C and 1.6 °C, respectively, which indicates that the proposed model can well predict the thermal performance of MCE under non-uniformly distributed battery heat.

Suggested Citation

  • Lu, Jingchao & Zhuang, Dawei & Ding, Guoliang & Li, Guang & Wang, Yueming, 2024. "A distributed parameter model of refrigerant-cooled multi-channel evaporator for battery thermal management," Energy, Elsevier, vol. 304(C).
    • Handle: RePEc:eee:energy:v:304:y:2024:i:c:s0360544224019443
    DOI: 10.1016/j.energy.2024.132170
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    References listed on IDEAS

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    1. Sun, Tao & Chen, Jianguo & Wang, Shaoqing & Chen, Quanwei & Han, Xuebing & Zheng, Yuejiu, 2023. "Aging mechanism analysis and capacity estimation of lithium - ion battery pack based on electric vehicle charging data," Energy, Elsevier, vol. 283(C).
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    3. Li, Li & Ling, Lei & Xie, Yajun & Zhou, Wencai & Wang, Tianbo & Zhang, Lanchun & Bei, Shaoyi & Zheng, Keqing & Xu, Qiang, 2023. "Comparative study of thermal management systems with different cooling structures for cylindrical battery modules: Side-cooling vs. terminal-cooling," Energy, Elsevier, vol. 274(C).
    4. Desreveaux, A. & Bouscayrol, A. & Trigui, R. & Hittinger, E. & Castex, E. & Sirbu, G.M., 2023. "Accurate energy consumption for comparison of climate change impact of thermal and electric vehicles," Energy, Elsevier, vol. 268(C).
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