SOC Estimation of Lithium Battery Based on Monte Carlo and SH-AUKF Algorithm

Aiming at the problem of low estimation accuracy of SOC of lithium battery, a new adaptive filtering algorithm, SH-AUKF algorithm is proposed by combining Sage-Husa adaptive algorithm with AUKF method. SH-AUKF algorithm can update and modify system noise continuously. UKF, AUKF and SH-AUKF algorithms are used to estimate SOC under DST conditions. The results show that SH-AUKF algorithm has the lowest estimation error and the highest estimation accuracy. Compared with UKF, the estimation accuracy of SH-AUKF algorithm is improved by 45.4%. Compared with AUKF, the estimation accuracy of SH-AUKF algorithm is improved by 14.3%. In order to further reduce the influence of accidental and sudden noise interference on SOC estimation, Monte Carlo sampling method is added in the estimation process. The results show that the error range of SH-AUKF algorithm combined with Monte Carlo method is only ±1×10^-3, which effectively improves the estimation accuracy.