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A model-scale experimental and theoretical study on a mineral oil-immersed battery cooling system

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  • Liu, Jiahao
  • Fan, Yining
  • Wang, Jinhui
  • Tao, Changfa
  • Chen, Mingyi

Abstract

The concept of immersion cooling has been proposed and validated via several numerical studies in recent years, while systematical experimental studies and corresponding theoretical considerations on its heat transfer mechanism are scarcely available in the literature. In this work, a series of experiments are conducted by means of a well-designed model-scale oil-immersed battery cooling system to explore the thermal behavior of a dynamically cycling battery subjected to static and flowing mineral oil (MO). The battery temperature can be maintained below 35 °C for 5 mL/min flow rate, and below 30 °C when exceeding 15 mL/min, even at 4 C discharge rate. Increasing MO flow rate can reduce the battery temperature, while this effect gradually attenuates due to the cooling capacity limit of the system. The theoretical analysis verifies that the dominated heat transfer mechanism varies with both battery cycle rate and Reynolds number of the fluid. The rising cycle rate can enlarge the natural convection dominated range, and at 4 C cycle rate, the natural convection even dominates in currently entire Re range. The findings here quantitatively and theoretically confirm the effectiveness of the oil-immersed battery cooling system, which provides more new insights into the development of practical immersion cooling system.

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  • Liu, Jiahao & Fan, Yining & Wang, Jinhui & Tao, Changfa & Chen, Mingyi, 2022. "A model-scale experimental and theoretical study on a mineral oil-immersed battery cooling system," Renewable Energy, Elsevier, vol. 201(P1), pages 712-723.
    • Handle: RePEc:eee:renene:v:201:y:2022:i:p1:p:712-723
    DOI: 10.1016/j.renene.2022.11.010
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    References listed on IDEAS

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    1. Eddahech, Akram & Briat, Olivier & Vinassa, Jean-Michel, 2013. "Thermal characterization of a high-power lithium-ion battery: Potentiometric and calorimetric measurement of entropy changes," Energy, Elsevier, vol. 61(C), pages 432-439.
    2. Saw, Lip Huat & Ye, Yonghuang & Tay, Andrew A.O. & Chong, Wen Tong & Kuan, Seng How & Yew, Ming Chian, 2016. "Computational fluid dynamic and thermal analysis of Lithium-ion battery pack with air cooling," Applied Energy, Elsevier, vol. 177(C), pages 783-792.
    3. Wang, Tao & Tseng, K.J. & Zhao, Jiyun & Wei, Zhongbao, 2014. "Thermal investigation of lithium-ion battery module with different cell arrangement structures and forced air-cooling strategies," Applied Energy, Elsevier, vol. 134(C), pages 229-238.
    4. Ling, Ziye & Lin, Wenzhu & Zhang, Zhengguo & Fang, Xiaoming, 2020. "Computationally efficient thermal network model and its application in optimization of battery thermal management system with phase change materials and long-term performance assessment," Applied Energy, Elsevier, vol. 259(C).
    5. Jiang, Z.Y. & Qu, Z.G., 2019. "Lithium–ion battery thermal management using heat pipe and phase change material during discharge–charge cycle: A comprehensive numerical study," Applied Energy, Elsevier, vol. 242(C), pages 378-392.
    6. Prahit Dubey & Gautam Pulugundla & A. K. Srouji, 2021. "Direct Comparison of Immersion and Cold-Plate Based Cooling for Automotive Li-Ion Battery Modules," Energies, MDPI, vol. 14(5), pages 1-19, February.
    7. Liu, Xingtao & Chen, Zonghai & Zhang, Chenbin & Wu, Ji, 2014. "A novel temperature-compensated model for power Li-ion batteries with dual-particle-filter state of charge estimation," Applied Energy, Elsevier, vol. 123(C), pages 263-272.
    8. Xu, Xinhai & Li, Wenzheng & Xu, Ben & Qin, Jiang, 2019. "Numerical study on a water cooling system for prismatic LiFePO4 batteries at abused operating conditions," Applied Energy, Elsevier, vol. 250(C), pages 404-412.
    9. Liu, Yuanzhi & Zhang, Jie, 2020. "Self-adapting J-type air-based battery thermal management system via model predictive control," Applied Energy, Elsevier, vol. 263(C).
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    Cited by:

    1. Huang, Chu & Zhu, Haixi & Ma, Yinjie & E, Jiaqiang, 2023. "Evaluation of lithium battery immersion thermal management using a novel pentaerythritol ester coolant," Energy, Elsevier, vol. 284(C).
    2. Liu, Qian & Liu, Yingying & Zhang, Mingjie & Wang, Shuping & Li, Wenlong & Zhu, Xiaoqing & Ju, Xing & Xu, Chao & Wei, Bin, 2024. "Comprehensive investigation of the electro-thermal performance and heat transfer mechanism of battery system under forced flow immersion cooling," Energy, Elsevier, vol. 298(C).
    3. Daniels, Rojo Kurian & Langeh, Harsh & Kumar, Vikas & Chouhan, Satyendra Singh & Prabhakar, Aneesh, 2024. "Faulty cell prediction accuracy comparison of machine learning algorithms using temperature sensor placement optimization approach in immersion cooled Li-ion battery modules," Applied Energy, Elsevier, vol. 367(C).

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