SOC estimation of Li-ion battery based on AUKF algorithm
Accurate state of charge(SOC)estimation helps battery management systems extend battery life and ensure battery safety.The estimation of SOC of Li-ion battery using the Kalman filtering algorithm is usually inaccurate due to the pseudo-positive characterization of the covariance matrix and the accumulation of noise statistical errors.Therefore,a SOC estimation method for Li-ion battery based on an adaptive unscented Kalman filter(AUKF)is proposed.The method consists of unscented Kalman filter(UKF)and adaptive algorithm.The accuracy of the proposed method for SOC estimation at different aging levels is verified by comparing with UKF.The proposed algorithm shows high SOC estimation accuracy with error within 0.5%.
lithium iron phosphateLi-ion batteryadaptive unscented Kalman filter(AUKF)state of charge(SOC)
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