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Research on Thermal Characteristics and Algorithm Prediction Analysis of Liquid Cooling System for Leaf Vein Structure Power Battery
by
Mingfei Yang
Mingfei Yang *,
Shanhua Zhang
Shanhua Zhang *,
Han Tian
Han Tian ,
Li Lv
Li Lv and
Jiqing Han
Jiqing Han
School of Digital Equipment, Jiangsu Vocational College of Electronics and Information, Huai’an 223003, China
*
Authors to whom correspondence should be addressed.
Batteries 2025, 11(9), 326; https://doi.org/10.3390/batteries11090326 (registering DOI)
Submission received: 20 July 2025
/
Revised: 25 August 2025
/
Accepted: 27 August 2025
/
Published: 29 August 2025
Abstract
With the increase in energy density of power batteries, the risk of thermal runaway significantly increases under extreme working conditions. Therefore, this article proposes a biomimetic liquid cooling plate design based on the fractal structure of fir needle leaf veins, combined with Murray’s mass transfer law, which has significantly improved the heat dissipation performance under extreme working conditions. A multi-field coupling model of electrochemistry fluid heat transfer was established using ANSYS 2022 Fluent, and the synergistic mechanism of environmental temperature, coolant parameters, and heating power was systematically analyzed. Research has found that compared to traditional serpentine channels, leaf vein biomimetic structures can reduce the maximum temperature of batteries by 11.78 °C at a flow rate of 4 m/s and 5000 W/m3. Further analysis reveals that there is a critical flow rate threshold of 2.5 m/s for cooling efficiency (beyond which the effectiveness of temperature reduction decreases by 86%), as well as a thermal saturation temperature of 28 °C (with a sudden increase in temperature rise slope by 284%). Under low-load conditions of 2600 W/m 3, the system exhibits a thermal hysteresis plateau of 40.29 °C. To predict the battery temperature in advance and actively intervene in cooling the battery pack, based on the experimental data and thermodynamic laws of the biomimetic liquid cooling system mentioned above, this study further constructed a support vector machine (SVM) prediction model to achieve real-time and accurate prediction of the highest temperature of the battery pack (validation set average relative error 1.57%), providing new ideas for intelligent optimization of biomimetic liquid cooling systems.
Share and Cite
MDPI and ACS Style
Yang, M.; Zhang, S.; Tian, H.; Lv, L.; Han, J.
Research on Thermal Characteristics and Algorithm Prediction Analysis of Liquid Cooling System for Leaf Vein Structure Power Battery. Batteries 2025, 11, 326.
https://doi.org/10.3390/batteries11090326
AMA Style
Yang M, Zhang S, Tian H, Lv L, Han J.
Research on Thermal Characteristics and Algorithm Prediction Analysis of Liquid Cooling System for Leaf Vein Structure Power Battery. Batteries. 2025; 11(9):326.
https://doi.org/10.3390/batteries11090326
Chicago/Turabian Style
Yang, Mingfei, Shanhua Zhang, Han Tian, Li Lv, and Jiqing Han.
2025. "Research on Thermal Characteristics and Algorithm Prediction Analysis of Liquid Cooling System for Leaf Vein Structure Power Battery" Batteries 11, no. 9: 326.
https://doi.org/10.3390/batteries11090326
APA Style
Yang, M., Zhang, S., Tian, H., Lv, L., & Han, J.
(2025). Research on Thermal Characteristics and Algorithm Prediction Analysis of Liquid Cooling System for Leaf Vein Structure Power Battery. Batteries, 11(9), 326.
https://doi.org/10.3390/batteries11090326
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