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A particular safety issue with Lithium-ion (Li-ion) cells is thermal runaway (TR), which is the exothermic decomposition of cell components creating an uncontrollable temperature rise leading to fires and explosions. The modelling of TR is difficult due to the broad range of cell properties and potential conditions. Understanding the effect that thermophysical and heat transfer characteristics have on the TR abuse model output is essential to develop more accurate and robust TR models. This study uses global sensitivity analysis (GSA) to investigate the effect of the cell parameters on the outcome of TR events. Using a Gaussian Process (GP) surrogate model to calculate the Sobol' indices, it is shown that the emissivity value is the dominant thermo-characteristic throughout the overall abuse scenario. Further analysis, investigating three key TR features shows the conductivity coefficient to be the most important with respect to the maximum temperature reached during TR. Results demonstrate that researchers can confidently estimate some thermo-characteristics but require accurate characterisation of the emissivity and conductivity coefficient to ensure robust predictions. Given the importance of battery technology to aid in global de-carbonisation, these findings are key to increasing their safe design and operation.

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Thermal runaway (TR) is a significant safety concern for Li-ion batteries (LIBs), which, through computational modelling can be better understood. However, TR models for LIBs lack a proper representation of the build-up of pressure inside a cell under abuse, which is integral to predicting cell venting. Here, an advanced abuse model (AAM) is developed and compared to a classical TR model, considering a lithium iron phosphate (LFP) cell case study. The AAM accounts for two additional features: 1) venting, with a novel description of the internal cell pressure governed by the bubble point of the electrolyte/decomposition-gas mixture, and 2) simmering reactions. The novel bubble pressure assumption is validated against experimental data, and we show that the AAM significantly improves the predictions of time to TR and of temperatures after TR. Further, it is shown that there is significant uncertainty in the parameters defining the decomposition reactions for LFP cells. Importantly, cell pressurisation is most dependent on the gases released by the solid electrolyte interphase reaction, and venting is dependent on cell burst pressure and reaction activation energies. The AAM is essential for accurate abuse modelling, due to its improved temperature predictions, and considerably enhances the LIB TR field of study.