SOC Estimation of Li-Ion Battery Based on Unscented Kalman Filter

The accurately estimating the battery charging state is a key problem in battery management system. In this paper, an adaptive lithium-ion battery (SOC) estimation method is presented based on the the Unscented Filter(UKF). The common equivalent circuit model is enhanced, which includes the effect of different discharge rate and temperature on SOC. The SOC estimation algorithm is improved and verified in different types of lithium-ion batteries. An adaptive joint estimation of the battery SOC is then presented to enhance system robustness with battery aging. The results show that this method can provide accurate SOC estimation and high computational efficiency, which is suitable for the embedded system applications.