Fractional order equivalent circuit model and SOC estimation of supercapacitors for use in HESS

Abstract

Supercapacitors are an important part of the hybrid energy storage system for electric vehicles (EVs.) They not only protect the battery, but also improve the starting performance, acceleration performance, and regenerative braking performance of the EVs. Accurate modeling and state of charge (SOC) estimation of supercapacitors are essential for reliability, resilience, and safety in hybrid energy storage system operations. In this paper, a fractional order dynamic equivalent circuit model of the supercapacitor is proposed. Through the parameter identification and the experimental analysis, it is proved that the fractional equivalent circuit has better precision. Furthermore, the SOC estimation method of particle filter and Kalman filter is investigated, and a method of estimating supercapacitor SOC is proposed by combining the particle filter and the fractional Kalman filter. The validation results prove that the proposed method has better accuracy and real-time performance based on the fractional order.