Optimization for liquid cooling cylindrical battery thermal management system based on gaussian process model

Wei Li, Akhil Garg, Mi Xiao, Liang Gao*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

62 Citations (Scopus)

Abstract

The power of electric vehicles (EVs) comes from lithium-ion batteries (LIBs). LIBs are sensitive to temperature. Too high and too low temperatures will affect the performance and safety of EVs. Therefore, a stable and efficient battery thermal management system (BTMS) is essential for an EV. This article has conducted a comprehensive study on liquid-cooled BTMS. Two cooling schemes are designed: the serpentine channel and the U-shaped channel. The results show that the cooling effect of two schemes is roughly the same, but the U-shaped channel can significantly decrease the pressure drop (PD) loss. The U-shaped channel is parameterized and modeled. A machine learning method called the Gaussian process (GP) model has been used to express the outputs such as temperature difference, temperature standard deviation, and pressure drop. A multi-objective optimization model is established using GP models, and the NSGA-II method is employed to drive the optimization process. The optimized scheme is compared with the initial design. The main findings are summarized as follows: the velocity of cooling water v decreases from 0.3 m/s to 0.22 m/s by 26.67%. Pressure drop decreases from 431.40 Pa to 327.11 Pa by 24.18%. The optimized solution has a significant reduction in pressure drop and helps to reduce parasitic power. The proposed method can provide a useful guideline for the liquid cooling design of large-scale battery packs.

Original languageEnglish
Article number021015
JournalJournal of Thermal Science and Engineering Applications
Volume13
Issue number2
DOIs
Publication statusPublished - Apr 2021
Externally publishedYes

Keywords

  • Energy systems
  • Gaussian process model
  • Liquid cooling
  • Serpentine channel
  • U-shaped channel

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