Online detection of early stage internal short circuits in series-connected lithium-ion battery packs based on state-of-charge correlation

Internal short circuits (ISCs) may occur in lithium-ion battery packs during their use and lead to the depletion of battery power at an early stage or to thermal runaways and safety risks at a later stage. In this study, a state-ofcharge (SOC) correlation-based early stage ISC detection method for the online detection of ISCs under dynamic conditions is proposed to improve battery safety. Herein, we elucidate the principle and algorithm of the method. The SOC of each cell is estimated via the extended Kalman filter, and the correlation coefficient is calculated for adjacent cells using a moving window to ensure estimation accuracy and stability. To prevent false positives, the two correlation coefficients of cells adjacent to a target one should be below a predefined threshold to indicate ISC. Experiments are conducted using an external resistor to simulate ISCs under various dynamic conditions, and four ISC detection methods are compared to detect ISCs at three severity levels. The results show that the proposed method is fast, highly accurate, and that it enables the online detection of an early stage ISC of 100 Omega under dynamic conditions within 20.4 h, which is suitable for improving battery safety.