State of charge estimation for lithium battery based on fractional order square root cubature Kalman filter and adaptive multi-innovation unscented Kalman filter (Q6610145)

In the paper under consideration a novel fractional order model-based method for the state of charge (SOC) estimation is studied. The author design two filters. The first filter is fractional order square root cubature Kalman filter (FOSRCKF) and it is used for estimating the battery SOC. The second filter is adaptive multi-innovation unscented Kalman filter (AMIUKF) used for estimating the internal resistance. The effectiveness and robustness of the proposed method are verified under the Urban Dynamometer Driving Schedule (UDDS) and the US06 Highway Driving Schedule. Compared to other methods the FOSRCKF-AMIUKF has lower SOC estimation error and lower terminal voltage prediction error.