For the Battery Management System (BMS) to manage and control the battery, State of Charge (SOC) is an important battery performance indicator. In order to identify the parameters of the LiFePO₄ battery, this paper employs the forgetting factor recursive least squares (FFRLS) method, which considers the computational volume and model correctness, to determine the parameters of the LiFePO₄ battery. On this basis, the two resistor-capacitor equivalent circuit model is selected for estimating the SOC of the Li-ion battery by combining the extended Kalman filter (EKF) with the Sage–Husa adaptive algorithm. The positivity is improved by modifying the system noise estimation matrix. The paper concludes with a MATLAB 2016B simulation, which serves to validate the SOC estimation algorithm. The results demonstrate that, in comparison to the conventional EKF, the enhanced EKF exhibits superior estimation precision and resilience to interference, along with enhanced convergence during the estimation process.

With the rapid advancement of battery technology, the energy density and power density of lithium-ion batteries (LIBs) as a key component of electric vehicles have been increasing. However, accidents triggered by the thermal runaway of LIBs have been occurring frequently. Therefore, to address this issue, it is imperative to investigate the TR characteristics of the battery under various conditions. This study investigates the TR characteristics of ternary pouch LIBs induced by surface heating, using techniques such as voltage and temperature acquisition, as well as video imaging. The experimental results are analyzed to elucidate the venting and combustion characteristics of the cells. Furthermore, in order to provide a more comprehensive elucidation of the TR behavior of the battery, a corresponding 3D model for surface-induced TR was constructed. The simulation results of this model are in good agreement with the experimental results and effectively capture the TR characteristics of the cells under surface heating. Finally, the simulation results showed that the cells are more prone to venting from the side due to the lower melting point of the polypropylene (PP) adhesive used for cell sealing. The use of high-temperature-resistant sealing adhesives is crucial in preventing uncontrolled lateral venting of the cells.