State-of-charge estimation for lithium-ion battery using Busse´s adaptive unscented Kalman filter

State-of-charge estimation of rechargeable battery is vital to maximize the battery performance and ensure the safe operating condition. This paper presents state-of-charge estimation method for lithium-ion battery using adaptive unscented Kalman Filter. In this aspect, Busse´s adaptive rule is implemented to update the process noise covariance of the Kalman filter. Compared with the existing adaptive rules, Busse´s rule is relatively simpler and it doesn´t require huge memory capacity for storing the voltage residual. The accuracy of the proposed method is verified through experimental studies. A comparison with the unscented Kalman filter algorithms is made to compare the accuracy of each algorithm.