Ultracapacitor performance determination using dynamic model parameter identification

We present a real-time adaptive process for ultracapacitor performance estimation using a dynamic model describing the device behavior. We develop a simple and linear-recursive model that proved its efficiency regarding the comparison between simulation results and real data from power cycling tests. Model shows very good performances since the maximum relative modeling error do not exceed 3%. Based on a recursive least squared algorithm with a time-variant forgetting factor, the on-line estimation of the dynamic ultracapacitor-model parameters mainly the internal resistance served as a state of health indicator.