Open Access

ARTICLE

Research on Anisotropic Electro-Thermal Coupling Model for Large-Capacity Prismatic Lithium-Ion Power Batteries

Xiang Chen^1,2,3,*, Shugang Sun¹, Xingxing Wang³, Yelin Deng²
1 School of Mechanical Engineering, Nantong Institute of Technology, 211 Yongxing Road, Nantong, China
2 School of Rail Transportation, Soochow University, 8 Jixue Road, Suzhou, China
3 School of Mechanical Engineering, Nantong University, 9 Seyuan Road, Nantong, China
* Corresponding Author: Xiang Chen. Email:
(This article belongs to the Special Issue: Advanced Multi-Physics Coupling Electrochemical-Thermal Energy Storage Modeling and Active Safety State Estimation)

Frontiers in Heat and Mass Transfer https://doi.org/10.32604/fhmt.2026.077731

Received 16 December 2025; Accepted 10 February 2026; Published online 17 March 2026

Abstract

Large-capacity energy storage batteries exhibit thermal behaviors markedly different from conventional cylindrical or pouch cells. Due to their multilayer electrode structure, they show pronounced anisotropy in thermal conductivity between through-thickness and in-plane directions. This results in uneven heat diffusion and internal–external temperature gradients that surface sensors cannot capture. Moreover, heat generation varies with temperature and state of charge (SOC) owing to changes in internal resistance. To address these challenges, an equivalent circuit and anisotropic electrothermal coupled model were established, with heat generation and transfer processes analytically derived. Parameter identification was performed through capacity calibration, specific heat and entropy measurements, hybrid pulse power characterization (HPPC), and constant-current charging tests. Results reveal strong temperature dependence of resistance and capacitances, SOC-dependent entropy heat effects, and significant anisotropic thermal resistance arising from the winding structure. The model achieved high predictive accuracy, with surface temperature RMSE below 0.3°C, demonstrating its reliability for thermal behavior prediction of large-capacity storage cells.

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Keywords

Thermal management; temperature prediction; prismatic battery; heat generation mechanism; parameter identification

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