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January 18, 2026Modelling and Simulation in Engineering0 citationsOpen Access

Modeling and Optimization of the Immersion Evaporative Cooling Lithium‐Ion Battery System

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YSYitao ShiAZA. B. ZhangYLYaopeng Li

Key Points

  • The aim is to model and optimize the immersion evaporative cooling system for lithium-ion batteries by analyzing its performance and coupling mechanisms.
  • Developed a dynamic coupling model for heat transfer paths.
  • Conducted simulation experiments to evaluate the cooling performance.
  • Analyzed the effects of discharge current, inlet temperature, and filling rate on battery performance.
  • Performed multiobjective optimization for surface temperature and mass velocity.
  • Established a strong coupling relationship among electric, thermal, and flow parameters.
  • Identified that discharge current significantly impacts battery performance compared to inlet temperature.
  • Recommended a discharge current of 6 A for optimal performance.
  • Achieved a maximal mass velocity of approximately 490 kg/m2 s and reduced minimum surface temperature by about 18.5°C.

Abstract

This paper focuses on the coupling mechanism, performance, and optimization of the immersion evaporative cooling lithium‐ion battery system (IECLBS). A novel dynamic coupling model is established based on the whole heat transfer path. We investigated the coupling mechanism of IECLBS by examining changes in the relevant parameters. The results indicate a strong coupling relationship among the electric–thermal–flow parameters. Subsequently, we design various simulation experiments to assess the coupling performance of IECLBS. The experimental results demonstrate that the rate of mass velocity change diminishes at higher inlet temperature. The impact of variation in discharge current on battery performance is far greater than that of inlet temperature and filling rate. Furthermore, a discharge current of 6 A is recommended for optimal battery performance. Subsequently, the multiobjective optimization is performed to optimize the surface temperature and mass velocity. The optimal objective and the optimal combination are achieved, resulting in a maximal mass velocity of approximately 490 kg/m 2 s and a reduction in minimum surface temperature of about 18.5°C.

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Cite This Study

Shi et al. (2026) studied this question.

synapsesocial.com/papers/696c776ceb60fb80d1395ae2https://doi.org/10.1155/mse/3759112
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