Quantitative Diagnosis of Early Internal Short Circuit for Lithium-Ion Batteries Based on Multirate Discharge

Abstract

Accurate quantitative diagnosis of early internal short circuit (ISC) can provide an important indication for thermal runaway (TR) in lithium-ion batteries (LIBs). However, both electrical and thermal characteristics are not obvious in the early stage of ISC, traditional quantitative diagnosis methods usually employ reference battery or state estimation models to amplify the influence of ISC on battery characteristics, which consequently hinders practical application. In this article, a novel quantitative ISC diagnosis method, in which a multirate discharge test strategy is designed to amplify the effect of ISC self-discharge on measured capacity, is proposed to avoid dependency on the reference battery and state estimation model. Peukert’s equation is modified to extract the current-capacity relation under ISC and multirate discharge curves are used to identify the ISC resistance. Furthermore, the discharge current rate and voltage window are selected based on multiobjective optimization. The effectiveness of the proposed method is verified by batteries with different aging states and temperatures under multiple ISC conditions. The experimental results show the maximum estimation error is less than 5.5% with the ISC resistance values ranging from 10 to $200~\Omega $ . It implies that the proposed method could provide a promising idea for safety early warning of LIBs.