Monte Carlo assisted sensitivity analysis of a Li-ion battery with a phase change material

Abstract Safety of Li ion batteries is as important, if not more, as its performance because its usage in contemporary transport applications can otherwise lead to catastrophic scenarios. Owing to the exothermic reactions and complex heat transfer within the Li ion batteries, they are prone to overheating and possible thermal runaway in the absence of adequate thermal management systems. Therefore, to ensure a safe operation it is key to evaluate the uncertainties with respect to a thermal management system along with the uncertainties in the intricate multiphysical phenomena within the system. To achieve this, we conduct Monte Carlo simulations followed by sensitivity analysis to correlate the variability of 14 different factors with the safety of an 18650 Sony cell with a phase change material (PCM) at stressed conditions. These varied factors correspond to the properties of the 18650 battery and the PCM. From the PCM properties, we identify the temperature at which the PCM starts melting to have most influence on the safety of the battery. In addition, we also estimate the probability of the sub-optimal unsafe scenarios occurring by examining the distribution of the maximum temperature within the battery. Finally, we obtain reduced surrogate models with an accuracy of 92% through supervised machine learning algorithms.