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An Optimization Study on the Operating Parameters of Liquid Cold Plate for Battery Thermal Management of Electric Vehicles

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  • Lichuan Wei

    (School of Energy and Power Engineering, Xi’an Jiaotong University, Xi’an 710049, China
    Shenzhen Envicool Technology Co. Ltd., Shenzhen 518129, China)

  • Yanhui Zou

    (School of Human Settlements and Civil Engineering, Xi’an Jiaotong University, Xi’an 710049, China)

  • Feng Cao

    (School of Energy and Power Engineering, Xi’an Jiaotong University, Xi’an 710049, China)

  • Zhendi Ma

    (School of Human Settlements and Civil Engineering, Xi’an Jiaotong University, Xi’an 710049, China)

  • Zhao Lu

    (School of Energy and Power Engineering, Xi’an Jiaotong University, Xi’an 710049, China)

  • Liwen Jin

    (School of Human Settlements and Civil Engineering, Xi’an Jiaotong University, Xi’an 710049, China)

Abstract

The development of electric vehicles plays an important role in the field of energy conservation and emission reduction. It is necessary to improve the thermal performance of battery modules in electric vehicles and reduce the power consumption of the battery thermal management system (BTMS). In this study, the heat transfer and flow resistance performance of liquid cold plates with serpentine channels were numerically investigated and optimized. Flow rate ( m ˙ ), inlet temperature ( T in ), and average heat generation ( Q ) were selected as key operating parameters, while average temperature ( T ave ), maximum temperature difference (Δ T max ), and pressure drop (Δ P ) were chosen as objective functions. The Response Surface Methodology (RSM) with a face-centered central composite design (CCD) was used to construct regression models. Combined with the multi-objective non-dominated sorting genetic algorithm (NSGA-II), the Pareto-optimal solution was obtained to optimize the operation parameters. The results show that the maximum temperature differences of the cold plate can be controlled within 0.29~3.90 °C, 1.11~15.66 °C, 2.17~31.39 °C, and 3.43~50.92 °C for the discharging rates at 1.0 C, 2.0 C, 3.0 C, and 4.0 C, respectively. The average temperature and maximum temperature difference can be simultaneously optimized by maintaining the pressure drop below 1000 Pa. It is expected that the proposed methods and results can provide theoretical guidance for developing an operational strategy for the BTMS.

Suggested Citation

  • Lichuan Wei & Yanhui Zou & Feng Cao & Zhendi Ma & Zhao Lu & Liwen Jin, 2022. "An Optimization Study on the Operating Parameters of Liquid Cold Plate for Battery Thermal Management of Electric Vehicles," Energies, MDPI, vol. 15(23), pages 1-24, December.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:23:p:9180-:d:992760
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    References listed on IDEAS

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    1. Chen, Zeyu & Xiong, Rui & Lu, Jiahuan & Li, Xinggang, 2018. "Temperature rise prediction of lithium-ion battery suffering external short circuit for all-climate electric vehicles application," Applied Energy, Elsevier, vol. 213(C), pages 375-383.
    2. Andersen, Poul H. & Mathews, John A. & Rask, Morten, 2009. "Integrating private transport into renewable energy policy: The strategy of creating intelligent recharging grids for electric vehicles," Energy Policy, Elsevier, vol. 37(7), pages 2481-2486, July.
    3. 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.
    4. Xu, X.M. & He, R., 2014. "Review on the heat dissipation performance of battery pack with different structures and operation conditions," Renewable and Sustainable Energy Reviews, Elsevier, vol. 29(C), pages 301-315.
    5. Ren, Dongsheng & Liu, Xiang & Feng, Xuning & Lu, Languang & Ouyang, Minggao & Li, Jianqiu & He, Xiangming, 2018. "Model-based thermal runaway prediction of lithium-ion batteries from kinetics analysis of cell components," Applied Energy, Elsevier, vol. 228(C), pages 633-644.
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    Cited by:

    1. Moeed Rabiei & Ayat Gharehghani & Soheil Saeedipour & Amin Mahmoudzadeh Andwari & Juho Könnö, 2023. "Proposing a Hybrid BTMS Using a Novel Structure of a Microchannel Cold Plate and PCM," Energies, MDPI, vol. 16(17), pages 1-20, August.

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