Recent advances in early warning methods and prediction of thermal runaway events in Li-ion batteries

Abstract

Li-ion batteries find extensive utilization in electric vehicles due to their prolonged operational lifespan and impressive energy density. Nevertheless, the peril of electric vehicle accidents arising from the thermal runaway of lithium-ion batteries, leading to spontaneous combustion, poses a substantial threat to both the safety of passengers and their belongings. This review paper elucidates the intrinsic mechanisms governing the occurrence of thermal runaway in lithium-ion batteries, drawing insights from a multitude of previous studies. Within the context of this review paper, a meticulous examination is undertaken of diverse approaches based on electrochemistry, battery big data and artificial intelligence for predicting and proactively identifying instances of lithium-ion thermal runaway. This analysis encompasses an evaluation of the strengths and weaknesses associated with each approach, along with a discussion of the imminent challenges and potential future directions for the advancement of intelligent methods for predicting lithium-ion battery thermal runaway.