Technical Papers
Nov 19, 2019

Thermal Management of Prismatic Lithium-Ion Battery with Minichannel Cold Plate

Publication: Journal of Energy Engineering
Volume 146, Issue 1

Abstract

A battery thermal management system (BTMS) is crucial to guarantee that lithium-ion (Li-ion) batteries attain high performance, long life, and a high level of safety. To investigate an effective cooling method of prismatic Li-ion batteries for an electric vehicle, a design of BTMS using minichannel cold plates is established. The performance of the BTMS are parametrically studied by using different configurations, flow rates, and inlet coolant temperatures. With this BTMS, the maximum temperature and the temperature difference of the cell at a discharge rate of 2 C is 33.8°C and 3.5°C, respectively, using flow rate of 0.002  kgs1 and inlet coolant temperature of 30°C. The C-rate is equal to the charge–discharge current divided by its rated capacity. At higher discharge rates, higher flow rates are needed to achieve the cooling performance, and the flow rate has upper limits given the efficiency of the cooling system. When the discharge rate is increased to 3 C and 5 C, the optimal flow rate needed is 0.003 and 0.02  kgs1, respectively.

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Acknowledgments

This study is partially supported by the National Key Research and Development Program of China (2016YFB0101001), the Automotive Technology and Research Center Standardization Program of China (2016ZXFB06002), and the Beijing Natural Science Foundation (L161004).

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Published In

Go to Journal of Energy Engineering
Journal of Energy Engineering
Volume 146Issue 1February 2020

History

Received: Dec 18, 2018
Accepted: Feb 22, 2019
Published online: Nov 19, 2019
Published in print: Feb 1, 2020
Discussion open until: Apr 19, 2020

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Authors

Affiliations

Jianbiao Shen [email protected]
Postdoctoral Fellow, School of Transportation Science and Engineering, Beihang Univ., No. 37 Xueyuan Rd., Haidian District, Beijing 100191, China. Email: [email protected]
Yunpeng Wang [email protected]
Professor, School of Transportation Science and Engineering, Beihang Univ., No. 37 Xueyuan Rd., Haidian District, Beijing 100191, China. Email: [email protected]
Professor, Beijing Advanced Innovation Center for Big Data and Brain Computing, School of Transportation Science and Engineering, Beihang Univ., No. 37 Xueyuan Rd., Haidian District, Beijing 100191, China (corresponding author). Email: [email protected]
Honggang Li [email protected]
Ph.D. Student, School of Transportation Science and Engineering, Beihang Univ., No. 37 Xueyuan Rd., Haidian District, Beijing 100191, China. Email: [email protected]

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