Thermal Characterization of a High-Power Lithium-Ion Pouch Cell and Surface Temperature Prediction for Motorsport Applications

Accurate cell thermal characterisation is vital for battery modelling and thermal management, especially in motorsport, where minor temperature estimation errors can have severe consequences. Conventional methods for determining key thermal parameters, such as the specific heat capacity, often require costly calorimeters or destructive testing. Recent studies propose an alternative approach using a 1D lumped thermal network to solve the thermal balance of a heat-generating cell. However, these studies often overlook critical aspects of the heat generation equation, particularly the entropic term, which is essential for capturing nonlinear thermal behaviour, especially under dynamic cycling conditions. This study presents a cost-effective approach for rapid cell thermal characterisation and accurate surface temperature prediction. A pouch LCO cell was first tested to determine the entropic coefficient, followed by experiments under two convective conditions to evaluate its specific heat capacity. An optimisation problem was then formulated to identify the remaining thermal parameters. The thermal model was integrated with a first-order Equivalent Circuit Model (ECM), which provided the voltage response necessary for heat generation calculations. The training data for cell surface temperature predictions included two dynamic load and power tests designed to replicate a motorsport environment. The model demonstrated high accuracy (RMSE <0.5°C) across a wide range of operating conditions, confirming its robustness. This study provides valuable insights for motorsport battery applications and reinforces the need to standardise thermal parameter determination to improve research comparability.