Research on Estimation Methods for State of Charge and Core Temperature of Energy Storage Lithium Batteries

The State of Charge (SOC) and thermal conditions of lithium batteries are essential factors in the Battery Management System (BMS). Precise assessment of the SOC and core temperature of lithium batteries is crucial for the development of the BMS. This study utilizes the Square Root Cubature Kalman Filter (SRCKF) method along with the electro-thermal coupled model of lithium batteries to achieve accurate estimations of the battery’s SOC and core temperature. Initially, this research determines the parameters of the electro-thermal coupled model using the Forgetting Factor Recursive Least Squares method and the Hybrid Pulse Power Characterization tests, establishing the lithium battery’s electro-thermal coupled model. In order to validate the accuracy of SRCKF estimates, simulations were carried out under conditions defined by the Urban Dynamometer Driving Schedule, comparing the accuracy of its estimations with those of the Extended Kalman Filter and the Unscented Kalman Filter under identical conditions. The simulation outcomes demonstrate that the SRCKF can precisely estimate the battery’s SOC and core temperature, thus effectively meeting the requirements of the BMS in practical application scenarios. This study utilizes the open-source experimental dataset of the LG18650HG2 lithium battery.