Quantitative diagnosis of micro-short circuit for lithium-ion batteries considering aging based on incremental capacity curve

Abstract

Early diagnosis of internal short-circuit faults for preventing thermal runaway in lithium-ion batteries stands as a pivotal task within battery management systems. With the continuous use of electric vehicles, the coexistence of aging and micro-short circuit (MSC) within battery packs is possible. These two faults manifest identical characteristics during discharge, rendering them susceptible to erroneous diagnoses. In this study, a novel fault diagnosis method based on the incremental capacity (IC) curves is proposed, devised to discern aging cells from those afflicted by MSC. This method screens out aging cells by feature parameters of IC curve. Based on the unique correspondence between IC peak and state of charge in this study, the cell that reaches the peak first is designated as the reference cell. By calculating the leakage current based on the temporal divergence of peak arrivals of each cell from this reference, this method estimates the MSC resistance to quantify the degree of the short-circuit fault. A series of experiments involving the presence of aging batteries, simultaneous occurrence of multiple MSC faults, or the evolution of MSC severity indicate the method is feasible and effective for diagnosing aging and MSC faults in battery packs simultaneously.