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Cited by 1,292

The DOI matches its Crossref record; 9 of the 9 references it cites were found in a registry or an index.

Review on battery thermal management system for electric vehicles

Kim, Jaewan, Oh, Jinwoo, Lee, Hoseong·2019·Applied Thermal Engineering

Abstract

Abstract The lithium-ion batteries are widely used for electric vehicles due to high energy density and long cycle life. Since the performance and life of lithium-ion batteries are very sensitive to temperature, it is important to maintain the proper temperature range. In this context, an effective battery thermal management system solution is discussed in this paper. This paper reviews the heat generation phenomena and critical thermal issues of lithium-ion batteries. Then various battery thermal management system studies are comprehensively reviewed and categorized according to thermal cycle options. The battery thermal management system with a vapor compression cycle includes cabin air cooling, second-loop liquid cooling and direct refrigerant two-phase cooling. The battery thermal management system without vapor compression cycle includes phase change material cooling, heat pipe cooling and thermoelectric element cooling. Each battery thermal management system is reviewed in terms of the maximum temperature and maximum temperature difference of the batteries and an effective BTMS that complements the disadvantages of each system is discussed. Lastly, a novel battery thermal management system is proposed to provide an effective thermal management solution for the high energy density lithium-ion batteries.

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Crossref · 10.1016/j.applthermaleng.2018.12.020

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Metadata

Authors
Kim, J., Oh, J., & Lee, H.
Venue
Applied Thermal Engineering
Publisher
Elsevier BV
Published
2019-02
Volume
149
Pages
192-212
ISSN
1359-4311 (ISSN-L)
OpenAlex
W2902540127
Cited by
1,292
References
9
FWCI
35.60
Type
journal article
Language
en
Open access
closed

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.