The safety of lithium-ion batteries is a critical and challenging focus of current research.This perspective article systematically summarized and compared evaluation methods for the trinitrotoluene-equivalent(TNT-equ...The safety of lithium-ion batteries is a critical and challenging focus of current research.This perspective article systematically summarized and compared evaluation methods for the trinitrotoluene-equivalent(TNT-equivalent)of lithium-ion batteries(LIBs)based on various characteristic parameters and proposed a mechanism-driven calculation approach.Using experimental data for validation,the study input TNT-equivalent values derived from different methods into an explosion dynamics model to predict explosion pressures,identifying the optimal calculation method through comparison with measured data.Results showed that the mechanism-driven approach accurately predicts explosion characteristics at different SOCs,with errors below 3%.This method eliminates the need for complex dynamic testing while providing precise predictions by linking the explosion equivalent to intrinsic thermal runaway(TR)mechanisms.The findings contribute to building safety analysis databases,establishing testing standards,and supporting the safety design of battery systems.展开更多
基金sponsored by the National Natural Science Foundation of China(Nos.52072040,U21A20170)National Key Research and Development Program of China(No.2022YFB3305400)T.Shan acknowledges the support from China Scholarship Council(No.202306030127).
文摘The safety of lithium-ion batteries is a critical and challenging focus of current research.This perspective article systematically summarized and compared evaluation methods for the trinitrotoluene-equivalent(TNT-equivalent)of lithium-ion batteries(LIBs)based on various characteristic parameters and proposed a mechanism-driven calculation approach.Using experimental data for validation,the study input TNT-equivalent values derived from different methods into an explosion dynamics model to predict explosion pressures,identifying the optimal calculation method through comparison with measured data.Results showed that the mechanism-driven approach accurately predicts explosion characteristics at different SOCs,with errors below 3%.This method eliminates the need for complex dynamic testing while providing precise predictions by linking the explosion equivalent to intrinsic thermal runaway(TR)mechanisms.The findings contribute to building safety analysis databases,establishing testing standards,and supporting the safety design of battery systems.