Ultracapacitor modelling and parameter identification using the Extended Kalman Filter

Energy storage systems (ESSs) play an important role in sinking and sourcing of power in an electric vehicle and ensuring operational safety. Ultracapacitors (UCs) are a recent addition to the types of energy storage unit that can be used in an electric vehicle as an ESS because of their high power density, fast charging or discharging, and low internal loss. They can be used in parallel with batteries or fuel cells to form a hybrid energy storage system that makes better use of merits of each component and offsets their drawbacks. Establishing a good model with properly identified parameters to precisely represent the UC dynamics is vital for energy management and optimal power control; but this is challenging. This paper firstly presents the classic circuit equivalent model that consists of a series resistance, a parallel resistance and a main capacitor. The model dynamics are described with the state space equations. The Extended Kalman Filter is then used to simultaneously estimate the state and the model parameters through a simple constant-current charging test. Finally, the obtained model is validated through a dynamic test. The model output shows a good agreement with the experimental results. They verify that the model is sufficiently precise to represent the dynamics of an UC.