The Adaptive Fading Extended Kalman Filter SOC Estimation Method for Lithium-ion Batteries

Abstract

The adaptive fading extended Kalman filter (AFEKF) is proposed for the accuracy and convergent speed problem of state of charge (SOC) estimation. This filter algorithm combines the adaptive extended Kalman filter and fading extended Kalman filter, which solves the problem of uncertainty of system noise and over-reliance on old data. The equivalent circuit model is utilized and the variable forgetting factor recursive least square(VFFRLS) is adopted to identify the model parameters. Experimental test platform is established to validate the method. Results show that the method is able to effectively improve the convergent speed and accuracy of SOC estimation, and the SOC error is less than 2%.