EKF-based estimation of SOC and temperature in ultracapacitors

In this paper, simultaneous estimation of state-of-charge (SOC) and temperature is achieved by applying extended Kalman filter (EKF) algorithm with only the terminal measurement of voltage and current. For the application of EKF algorithm, a nonlinear model which consists of a voltageand-thermal-dependent equivalent circuit model and a thermal model is used. The parameters in the equivalent circuit model are identified by applying least squares method to the electrochemical impedance spectroscopy (EIS) data. Experimental results demonstrate that the EKF-based estimator achieves improved and consistent prediction of SOC and temperature in existence of modeling errors and measurement noises, especially at low temperature. The accurate estimation of SOC and temperature enables optimum energy and thermal management of the ultracapacitors.