Lithium-Ion Batteries Early Internal Short-Circuit Fault Quantitative Identification During Charging and Setting Periods

Abstract

This article proposes a new algorithm to quantitatively identify the lithium-ion batteries soft and microlevel internal short-circuit (ISC) faults with the charging and setting data. Compared with the existing methodologies for lithium-ion battery ISC faults identification, the algorithm proposed in this work can hierarchically recognize the early ISC faults on the single battery unit, effectively. The NCM622 batteries with about 40.2 Ah capacity are used to verify the algorithm’s accuracy and efficiency. The results illustrate that at the charging span about 1/380 C fault or more serious at 25 and 55 °C while about 1/100 C fault or more severely at −10 °C can be identified, and an around 1/1100 C fault or more severe for setting period. Additionally, the fault level is also quantitatively calculated for two operating conditions, and the relative error is around 13% for charging period and less than 7% for setting periods, which verify the effectiveness of the algorithm proposed by this work and could provide significant guideline for industry application.