Battery Pack Inconsistency Modeling and SOC Estimation Based on Improved Mean-Difference Model

As the demand for voltage and capacity in electric vehicles (EVs) continues to rise, the trend of utilizing power batteries in groups is becoming increasingly pronounced. However, the drawbacks resulting from the inconsistency in state of charge (SOC) and parameters within the battery pack are gradually becoming apparent. First, this paper proposes an improved mean-difference model (iMDM) to estimate the inconsistency of battery pack. The model improves upon the widely used mean-difference model (MDM) that considers internal resistance and SOC differences by adding a polarization network to assess the variability within the battery pack. Subsequently, the unscented Kalman filter (UKF) and the extended Kalman filter (EKF) are used to estimate the mean SOC and the cell SOC differences. Finally, experiments are conducted on a battery pack consisting of four lithium-ion batteries arranged in series. The comparison results indicate that using iMDM to represent the inconsistencies in the battery pack considers a more comprehensive range of factors and also improves accuracy. It can directly and more accurately display the differences in parameters and SOC, which is beneficial for monitoring the status of the battery pack and achieving balance.