Online State and Parameter Estimation of Ultracapacitor Using Marginalized Kalman Filter

Abstract

Recent adoption to the usage of renewable resources has emerged as a consequence of the threats posed by the decreasing amount of fossil fuels and the increase in the level of greenhouse gases (GHG) in the atmosphere. This harnessed renewable energy needs to be stored in an energy storage device. One amongst the most prominently used energy storage devices is the ultracapacitor (UC). To ensure proper deployment and safer long-term operation, the dynamic behavior of the UC has to be observed carefully which is done by estimating the parameters of the UC online, which can be further used in the deduction of the state of health (SOH) and the state of charge (SOC) of the UC. The equivalent circuit model used for the purpose of estimation is demonstrated. Then the parameter estimation is done using the marginalized Kalman filter technique. This technique is implemented in MATLAB and the results are attached. The effectiveness of the method is validated by comparing the acquired results with the results that are obtained by employing other online parameter estimation techniques.