Advanced Numerical Validation of Integrated Electrochemical-Thermal Models for PCM-Based Li-Ion Battery Thermal Management System

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Abstract

In this investigation, a comprehensive validation framework for an integrated electrochemical-thermal model that addresses critical thermal management challenges in lithium-ion batteries (LIBs) is presented. The two-dimensional numerical model combines the Newman–Tiedemann–Gu–Kim (NTGK) electrochemical-thermal battery framework with the enthalpy-porosity approach for phase change material (PCM) battery thermal management systems (BTMSs). Rigorous validation against benchmarks demonstrates the model’s exceptional predictive capability across a wide range of operating conditions. Simulated temperature distribution and voltage capacity profiles at multiple discharge rates show excellent agreement with the experimental data, accurately capturing the underlying electrochemical-thermal mechanisms. Incorporating Capric acid (with a phase transition range of 302–305 K) as the PCM, the thermal management model demonstrates significantly improved accuracy over existing models in the literature. Notable error reductions include a 78.3% decrease in the Mean Squared Error (0.477 vs. 2.202), a 53.4% reduction in the Root Mean Squared Error (0.619 vs. 1.483), and a 55.5% drop in the Mean Absolute Percentage Error. Statistical analysis further confirms the model’s robustness, with a high coefficient of determination (R2 = 0.968858) and well-distributed residuals. Liquid fraction evolution analysis highlights the PCM’s ability to absorb thermal energy effectively during high-discharge operations, enhancing thermal regulation. This validated model provides a reliable foundation for the design of next-generation BTMS, aiming to improve the safety, performance, and lifespan of LIBs in advanced energy storage applications where thermal stability is critical.

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Nasiri, M., & Hadim, H. (2025). Advanced Numerical Validation of Integrated Electrochemical-Thermal Models for PCM-Based Li-Ion Battery Thermal Management System. Energies, 18(13). https://doi.org/10.3390/en18133386

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