Thermal performance analysis and optimization of heat pipe-assisted hybrid fin structure for lithium battery thermal management for extreme thermal conditions

Ukmin Han, Yong Joo Jun, Hongseok Choi, Hoseong Lee

Research output: Contribution to journalArticlepeer-review

8 Citations (Scopus)

Abstract

The current study proposed a heat pipe (HP)-assisted hybrid fin (HF) for inter-cell cooling in a battery thermal management system (BTMS). Its thermal performance was comprehensively investigated under extreme thermal conditions of up to 50 W along with critical variables. A numerical model for the proposed HF-BTMS was developed using the finite difference method and integrated with a performance prediction model based on an artificial neural network. After successfully validating with experimental results, the developed numerical model was intensely used for module-level thermal analysis and multivariate optimization. The proposed HF-BTMS exhibited a better thermal performance, which was experimentally verified by the reduction in the maximum temperature and deviation by 5.4 and 3.8 °C, respectively, than the BTMS with conventional plain fin (PF). The multivariate optimization indicated that the optimized performances of the HF-BTMS were all within the desired temperature ranges. The condensation lengths are known to be most influential rather than other variables related to coolant operating conditions. Finally, under the most thermally harsh condition, compared to PF-BTMS, the HF-BTMS was found out to dramatically reduce the maximum temperature and temperature deviation of the BTMS by over 17.95 °C and 16.37 °C, successfully maintaining within the safety range.

Original languageEnglish
Article number107128
JournalInternational Communications in Heat and Mass Transfer
Volume149
DOIs
Publication statusPublished - 2023 Dec

Bibliographical note

Publisher Copyright:
© 2023 Elsevier Ltd

Keywords

  • Battery thermal management
  • Finite difference method, Neural network
  • Heat pipe-assisted hybrid fin
  • Multivariate optimization

ASJC Scopus subject areas

  • Atomic and Molecular Physics, and Optics
  • General Chemical Engineering
  • Condensed Matter Physics

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