RESEARCH ARTICLE

Modeling and optimization of an enhanced battery thermal management system in electric vehicles

  • Mao LI 1,2 ,
  • Yuanzhi LIU 1 ,
  • Xiaobang WANG 1,3 ,
  • Jie ZHANG , 1
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  • 1. Department of Mechanical Engineering, The University of Texas at Dallas, Richardson, TX 75080, USA
  • 2. Beijing Institute of Aerospace Testing Technology, Beijing 100074, China
  • 3. School of Mechanical Engineering, Dalian University of Technology, Dalian 116024, China

Received date: 26 Oct 2017

Accepted date: 26 Feb 2018

Published date: 05 Mar 2019

Copyright

2018 Higher Education Press and Springer-Verlag GmbH Germany, part of Springer Nature

Abstract

This paper models and optimizes an air-based battery thermal management system (BTMS) in a battery module with 36 battery lithium-ion cells. A design of experiments is performed to study the effects of three key parameters (i.e., mass flow rate of cooling air, heat flux from the battery cell to the cooling air, and passage spacing size) on the battery thermal performance. Three metrics are used to evaluate the BTMS thermal performance, including (i) the maximum temperature in the battery module, (ii) the temperature uniformity in the battery module, and (iii) the pressure drop. It is found that (i) increasing the total mass flow rate may result in a more non-uniform distribution of the passage mass flow rate among passages, and (ii) a large passage spacing size may worsen the temperature uniformity on the battery walls. Optimization is also performed to optimize the passage spacing size. Results show that the maximum temperature difference of the cooling air in passages is reduced from 23.9 to 2.1 K by 91.2%, and the maximum temperature difference among the battery cells is reduced from 25.7 to 6.4 K by 75.1%.

Cite this article

Mao LI , Yuanzhi LIU , Xiaobang WANG , Jie ZHANG . Modeling and optimization of an enhanced battery thermal management system in electric vehicles[J]. Frontiers of Mechanical Engineering, 2019 , 14(1) : 65 -75 . DOI: 10.1007/s11465-018-0520-z

Acknowledgements

This work was supported by the University of Texas at Dallas. The author of Mao Li and Xiaobang Wang were supported by the China Scholarship Council.
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