Abstract
Li-ion battery mishaps are primarily attributed to short circuits, which missed early detection. In this study, a method is introduced to address this issue by analyzing the voltage relaxation, after initiating a rest period. The voltage equilibration arising from solid-concentration profile relaxation is expressed by a double-exponential model, whose time constants, τ1& τ2, capture the initial, rapid exponential contour and the long-term relaxation, respectively. By tracking τ2, which is very sensitive to small leakage currents, it is possible to detect a short early on and estimate the short resistance. This method, validated with experiments on commercial batteries induced with short circuits of varying extents, has >90% prediction accuracy and enables clear differentiation between different short severities, while factoring in the influence of temperature, state of charge (SOC), state of health (SOH), and idle currents. The method is applicable across different battery chemistries and form factors, offering precise and robust nascent-stage short detection-estimation for on-device implementation.
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