Quantitative analysis of the effectiveness of thermal insulations for mitigating the probability of thermal runaway occurrence by using 1DCAE

Battery energy storage systems (BESSs) consisting of lithium-ion batteries (LIBs) are being increasingly used to supplement the unstable electrical power derived from renewable energy sources. As stipulated by the International Electrotechnical Commission, BESSs must be assessed for any risks, including thermal runaway (TR) and thermal runaway propagation (TRP), at the module level as well as the final system level. Several studies have focused on the hazards and risk assessments (RAs) of BESSs; however, the assessment of system-level risks is challenging due to complex system-level interactions in BESSs, which involve multiphysics and dynamic phenomena. Therefore, we have focused on using 1D model, which can model multiphysics system-level interactions between system components in multiple physical domains. This study aims at a quantitative analysis of the effectiveness of thermal insulations for the prevention of the TRP scenario that a TR of a LIB propagates to other adjacent batteries as one of the high-risk scenarios in a battery module. To estimate the frequency of the scenarios, we applied the model which was able to predict the temperature profile of individual batteries in a battery module. The probability of TRP occurred in a battery module was estimated via the TRP occurrence rate by Monte Carlo simulations using the 1D model, which considers the probability distribution of the design parameters of individual LIBs or the components of a BESS. As a result, it was possible to conduct a quantitative analysis of the effectiveness on reducing the probability of a TRP scenario due to model changes.