Lithium-Ion Battery Internal Short Circuit Fault Diagnosis by Joint Estimation of Internal Short Circuit Current and State of Charge

Accurate diagnosis of internal short circuits (ISC) is essential for ensuring lithium-ion battery (LIB) safety, given the severe risks of thermal runaway associated with ISC. Addressing this, the present study introduces a novel ISC diagnostic approach with strong robustness against measurement disturbances. Specifically, the ISC faulty battery is represented through an enhanced first-order RC model, with ISC current incorporated as an additional state variable within the model. By employing the extended Kalman filter, the ISC current is estimated jointly with other battery states, significantly enhancing estimation robustness in the face of voltage and current measurement fluctuations. Furthermore, a recursive least squares method is developed to determine the ISC resistance, directly reflecting the ISC fault severity. The proposed diagnostic approach is validated for accuracy and robustness, maintaining ISC current and resistance estimation errors within 5 mA and 3 Ω, respectively, even under substantial electromagnetic interference.