Investigation on the Performance of Lithium-Ion Battery Thermal Management

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Abstract:

Li-ion batteries generate significant heat during operation, which leads to an increase in temperature and, consequently, a reduction in the battery's efficiency and lifespan. In this study, different cooling methods are simulated for the thermal management of the battery. The cooling using air and liquids is investigated with laminar flow at varying velocities. Results indicated that the use of water/glycol is more effective than air and mineral oil.

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111-118

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March 2026

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© 2026 Trans Tech Publications Ltd. All Rights Reserved

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[1] W. QIAN, J. BIN, L. BO, Y. YUYING, A critical review of thermal management models and solutions of lithium-ion batteries for the development of pure electric vehicles, Renewable and Sustainable Energy Reviews, Vol. 64, pp.106-128, 2016.

DOI: 10.1016/j.rser.2016.05.033

Google Scholar

[2] A. PESARAN, Battery thermal models for hybrid vehicle simulations, Journal of Power Sources, Vol. 110, No. 2, pp.377-382, 2002.

DOI: 10.1016/s0378-7753(02)00200-8

Google Scholar

[3] C. JIWEN, J. FANGMING, Li-ion power battery temperature control by a battery thermal management and vehicle cabin air conditioning integrated system, Energy for Sustainable Development, Vol. 57, pp.141-148, 2020.

DOI: 10.1016/j.esd.2020.06.004

Google Scholar

[4] S. HUAT, Y. HUANG, T. ANDREW, C. WEN TONG, K. SENG, Y. CHIAN, Computational fluid dynamic and thermal analysis of Lithium-ion battery pack with air cooling, Applied Energy, Vol. 177, pp.783-792, 2016.

DOI: 10.1016/j.apenergy.2016.05.122

Google Scholar

[5] J. KIM, J. OH, H. LEE, Review on battery thermal management system for electric vehicles, Applied Thermal Engineering, Vol. 149, pp.192-212, 2019.

DOI: 10.1016/j.applthermaleng.2018.12.020

Google Scholar

[6] L. AO, Y. ANTHONY CHUN YIN, W. WEI, C. TIMOTHY BO YUAN, L. CHUN SING, Integration of Computational Fluid Dynamics and Artificial Neural Network for Optimization Design of Battery Thermal Management System, MDPI Batteries, Vol. 8, No. 7, p.69, 2022.

Google Scholar

[7] L. YUHAO, Q. PU, L. QIANG, Numerical simulation and experiment of double chamber brake based on CFD, Scientific Reports, Vol. 13, No. 1, p.17785, 2023.

DOI: 10.1038/s41598-023-45010-9

Google Scholar

[8] R. SYAH, M. ELVENY, M. NASUTION, M. KUZNETSOVA, Numerical investigation of nanofluid flow using CFD and fuzzy-based particle swarm optimization, Scientific Reports, Vol. 11, No. 1, p.20973, 2021.

DOI: 10.1038/s41598-021-00279-6

Google Scholar

[9] J. TU, G. YEOH, Computational fluid dynamics: a practical approach, Third edition, 2018.

Google Scholar

[10] Gi-Heon. KIM, K. SMITH, KJ. LEE, Multi-Domain Modeling of Lithium-Ion Batteries Encompassing Multi-Physics in Varied Length Scales, Journal of The Electrochemical Society, Vol. 158, No. 8, pp. A955, 2011.

DOI: 10.1149/1.3597614

Google Scholar

[11] G-H. KIM, K. SMITH, K-J. LEE, Multi-Domain Modeling of Lithium-Ion Batteries Encompassing Multi-Physics in Varied Length Scales, Journal of The Electrochemical Society, Vol. 158, No. 8, pp. A955, 2011.

DOI: 10.1149/1.3597614

Google Scholar

[12] ANSYS, Inc. ANSYS FLUENT Battery Module Manual, 2013.

Google Scholar

[13] Kim, G.-H., & Pesaran, A. (2007). Battery thermal management design modeling. World Electric Vehicle Journal, 1(1), 126–133.

DOI: 10.3390/wevj1010126

Google Scholar