Li-ion batteries (LIBs) are a widely adopted energy storage device that are increasingly used in transportation and stationary
applications. However, LIBs come with the risk of thermal runaway (TR) which is known to be unpredictable. Previous computational work has assessed the sensitivity of TR to model inputs, while some experimental work has quantified the distribution
of TR behaviour. However, no work is known to have used computational simulations of cell abuse to predict the probability
of cell failure under typical abuse test standards. This work applies an abuse model to achieve this, as well as using key TR
output variables to calculate the magnitude of cell failure according to the redefined EUCAR hazard level assessment. Abuse
simulations of Underwriter Laboratory’s oven test are simulated thousands of times considering parameter distributions with two
different coefficient of variance sets. This work shows that it is possible to predict the change in the probability of failure against
the change in oven temperature and the probability of different hazard levels. However, there is a need to better understand and
refine the variance in cell parameters, specifically those related the kinetic behaviour, to allow for analysis that is more suitable
for risk assessment purposes.
CORE (COnnecting REpositories)
CORE (COnnecting REpositories)