An Early Micro Internal Short Circuit Fault Diagnosis Method Based on Accumulated Correlation Coefficient for Lithium-Ion Battery Pack

Abstract

Early micro internal short circuit (ISC) fault diagnosis is crucial for the safe and reliable operation of lithium-ion batteries. In order to solve the problem that the early micro ISC fault is difficult to identify due to its weak fault characteristics, this paper proposes a fault diagnosis method based on the accumulated correlation coefficient. Specifically, the method uses the accumulated voltage value within the time window as the input feature, constructs an adjustment factor based on the distance difference of the accumulated voltage value to amplify the difference between the fault voltage correlation coefficient and the normal voltage correlation coefficient, and finally achieves the purpose of highlighting the faulty cell. The effectiveness and diagnostic capability of the proposed method are verified in experiments of short circuit faults of different severity. The results show that the proposed method can effectively identify and locate early micro ISC faults within 200 s, and improve the diagnostic capability up to 0.02 C short-circuit severity. In addition, a multi-level diagnostic warning mechanism can be established according to the decrease of the fault voltage correlation coefficient, so as to measure the severity of the fault and track the fault evolution process.

Keywords

• lithium-ion battery pack
• internal short circuit
• fault diagnosis
• correlation coefficient