SOC Estimation of Li-Ion Power Battery Based on Strong Tracking UKF with Multiple Suboptimal Fading Factors

Abstract

A method based on strong tracking unscented Kalman filter with multiple suboptimal fading factors (MSTUKF) was proposed to accurately estimate the state of charge (SOC) of power batteries of electric vehicles online. Taking a certain lithium-ion battery as the research object, a second-order RC equivalent circuit model of the battery was established based on its external characteristics and related mechanism. Then the recursive least squares method with forgetting factor was adopted to identify the model parameters, and the MSTUKF nonlinear state space equation of the battery was established according to the equivalent circuit model. Finally, the SOC estimation algorithm was verified by simulation experiments under ECE15 and UDDS conditions. The results show that the error of MSTUKF in SOC estimation of lithium-ion battery is kept within 1.5%, so this method can estimate battery SOC accurately.