Accurate estimation of internal temperature is essential for safe operation and state esti mation of lithium-ion batteries, yet it usually cannot be measured directly and requires physically grounded electro-thermal models. High fidelity 3D simulations capture geometry-dependent heat transfer behavior but are too computationally intensive for real-time use, whereas common lumped models cannot represent internal gradients. This work presents an integrated geometry-resolved workflow that combines detailed 3D finite volume thermal modelling with systematic reduction to a compact multi-node thermal network and its coupling with an equivalent circuit electrical model. A realistic 3D model of the 20 Panasonic NCR18650B cell was reconstructed from CT data and literature parameters and validated against published axial and radial thermal conductivity measurements. The automated reduction yields a five-node thermal network preserving radial temperature distribution, which was coupled with five parallel Battery Table-Based blocks in MATLAB/Simulink to capture spatially distributed heat generation. Thermal chamber validation under dynamic loading shows strong agreement with measured surface temperature (MAE ≈ 0.43 °C) and terminal voltage (MAE ≈ 16 mV). The resulting model is interpretable, computationally efficient, and suitable for digital-twin development and advanced internal-state estimation.
Bata et al. (Mon,) studied this question.