Online SOC Estimation of Supercapacitor Energy Storage System Based on Fractional-Order Model

Abstract

Fast and accurate estimation of state of charge (SOC) of supercapacitors is essential for the safe and reliable operation of energy storage systems. However, existing SOC estimation methods are based on the integer-order model of supercapacitors and do not take into account the fractional-order characteristics of supercapacitors. Hence, the accuracy of SOC estimation results usually ignores the impact of modeling and relies on the correction effect of the algorithm. In this paper, a supercapacitor energy storage system is firstly established for fractional-order modeling and fractional-order SOC estimation of supercapacitors. Next, a Kalman filter is devised to track the SOC of supercapacitors in real time, and it can correct the estimation results online. Finally, experiments under different working conditions are conducted to demonstrate the effectiveness of the proposed fractional-order modeling and SOC estimation scheme. Compared with the data obtained by the traditional integer-order method, the accuracy of the proposed fractional-order method is higher, and the mean relative errors are less than 5%. With the online correction of the Kalman filter, the maximum errors under different working conditions are limited to 1.3%.