PCM-assisted battery thermal management systems with hybrid fin–rib geometry using numerical modeling and AI-based optimization framework

Effective thermal regulation remains a critical challenge in high-power lithium-ion battery packs, particularly under elevated discharge rates, where excessive temperature rise and non-uniform heat distribution can accelerate degradation and compromise safety. In this numerical study, a novel phase change material (PCM)-assisted battery thermal management system (BTMS) was proposed for a compact circular battery pack comprising 15 cylindrical LiCoO 2 –26,650 cells. The design introduced a hybrid thermal control strategy that simultaneously exploits latent heat storage, enhanced solid conduction, and increased external heat-transfer area for passive heat dissipation. In addition to aluminum fins embedded within the PCM to overcome its inherently low thermal conductivity, a distinctive outer-rib architecture was introduced to increase the external heat-transfer surface area available for heat rejection. Compared with conventional PCM-based systems, the proposed geometry enhances passive heat dissipation by providing larger external surfaces exposed to the ambient environment. To systematically assess the influence of key geometric parameters, including battery distance from the enclosure wall, tilted fins spacing, and outer rib length, an artificial neural network (ANN) model was developed to predict battery temperature rise across multiple configurations. The ANN was subsequently coupled with a genetic algorithm (GA) to identify an optimal design that minimizes the increase in battery temperature, offering an efficient alternative to extensive parametric simulations. Additionally, K-fold cross-validation was conducted to evaluate the generalization capability of the trained network and to ensure that the ANN model's high prediction accuracy was not due to overfitting. The GA-based optimization identified an optimal BTMS configuration with a battery-wall distance of 30 mm, outer rib length of 11.590 mm, and tilted fins spacing of 20 mm, yielding a maximum battery temperature of 304.884 K at 1800 s under a 2C discharge rate. The optimized system reduced the peak battery temperature by nearly 12.7 K relative to the PCM-less case and by approximately 3 K compared to the Base-designs. Moreover, the optimal design achieved a total thermal energy storage of 3605 J at 1800 s, corresponding to enhancements of about 19–24% in total stored energy and 30–33% in latent heat storage compared with the Base-design configurations.

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Publication Details

Journal
Applied Thermal Engineering
Published
2026-10-16
DOI
https://doi.org/10.1016/j.applthermaleng.2026.133554
Primary Topic
Advanced Battery Technologies Research
Type
article
Field-Weighted Citation Impact
0.00

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article

PCM-assisted battery thermal management systems with hybrid fin–rib geometry using numerical modeling and AI-based optimization framework

Mohammad Jafar Mokarram, Hanaa Abu-Zinadah, Raymond Ghandour, Hind Mohammed Albalawi et al.
Applied Thermal Engineering
Advanced Battery Technologies Research
article

PCM-assisted battery thermal management systems with hybrid fin–rib geometry using numerical modeling and AI-based optimization framework

Mohammad Jafar Mokarram, Hanaa Abu-Zinadah, Raymond Ghandour, Hind Mohammed Albalawi, Ilkhom Khaydarov, Hyder H. Abed Balla, Hemn A.H. BARZANI, Yanping Wu, Xuan Yang
article en

Abstract

Effective thermal regulation remains a critical challenge in high-power lithium-ion battery packs, particularly under elevated discharge rates, where excessive temperature rise and non-uniform heat distribution can accelerate degradation and compromise safety. In this numerical study, a novel phase change material (PCM)-assisted battery thermal management system (BTMS) was proposed for a compact circular battery pack comprising 15 cylindrical LiCoO 2 –26,650 cells. The design introduced a hybrid thermal control strategy that simultaneously exploits latent heat storage, enhanced solid conduction, and increased external heat-transfer area for passive heat dissipation. In addition to aluminum fins embedded within the PCM to overcome its inherently low thermal conductivity, a distinctive outer-rib architecture was introduced to increase the external heat-transfer surface area available for heat rejection. Compared with conventional PCM-based systems, the proposed geometry enhances passive heat dissipation by providing larger external surfaces exposed to the ambient environment. To systematically assess the influence of key geometric parameters, including battery distance from the enclosure wall, tilted fins spacing, and outer rib length, an artificial neural network (ANN) model was developed to predict battery temperature rise across multiple configurations. The ANN was subsequently coupled with a genetic algorithm (GA) to identify an optimal design that minimizes the increase in battery temperature, offering an efficient alternative to extensive parametric simulations. Additionally, K-fold cross-validation was conducted to evaluate the generalization capability of the trained network and to ensure that the ANN model's high prediction accuracy was not due to overfitting. The GA-based optimization identified an optimal BTMS configuration with a battery-wall distance of 30 mm, outer rib length of 11.590 mm, and tilted fins spacing of 20 mm, yielding a maximum battery temperature of 304.884 K at 1800 s under a 2C discharge rate. The optimized system reduced the peak battery temperature by nearly 12.7 K relative to the PCM-less case and by approximately 3 K compared to the Base-designs. Moreover, the optimal design achieved a total thermal energy storage of 3605 J at 1800 s, corresponding to enhancements of about 19–24% in total stored energy and 30–33% in latent heat storage compared with the Base-design configurations.

Applied Thermal EngineeringVol. 308
Princess Nourah bint Abdulrahman University (SA), American University of the Middle East (KW), University of Jeddah (SA), Lebanese French University (IQ), Weifang University of Science and Technology (CN), Al-Furat Al-Awsat Technical University (IQ), Anhui Xinhua University (CN), National Pedagogical University of Uzbekistan named after Nizami (UZ), Weifang University (CN)
Weifang University of Science and Technology, Deanship of Scientific Research, Princess Nourah Bint Abdulrahman University
Affordable and clean energy
Openalex Percentile: Top 22%
Advanced Battery Technologies Research
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