Estimation of fractional SOC for lithium batteries based on OCV hysteretic characteristics

Lithium battery state of charge (SOC) estimation is an important part of the battery management system and is of great significance to the safe and efficient operation of the battery. This paper first analyzes the hysteresis characteristics of battery charging and discharging through the hysteresis main loop and small loop characteristic tests, and constructs a hysteresis model that can correct the hysteresis voltage. Then, the principle of fractional-order calculus was introduced into the traditional integer-order model, and a constant phase element (CPE) was used to describe the fractional-order dynamic characteristics of the battery. Combined with the hysteretic model, a fractional-order hysteretic equivalent circuit model was constructed., and use genetic algorithm to identify the model parameters. Improvements are proposed to address the estimation bias and filter divergence of the extended Kalman filter algorithm. Correlation coefficients and adaptive factors are added to adaptively update the noise and Kalman gains to estimate battery SOC. Finally, the DST working condition experiment shows that the SOC error of the method proposed in this article is about 1.53%, the calculation time is 0.6 s, and the absolute correlation coefficient is 0.9953.