A Hybrid Optimization-Based Approach for Parameter Estimation and Investigation of Fractional Dynamics in Ultracapacitors

Abstract

The increasing demand of electrical energy storage has motivated the wide usage of ultracapacitors. Ultracapacitors are capable of storing and delivering energy at a rate much higher than conventional rechargeable batteries. The dynamics characteristics of ultracapacitors are better exhibited by fractional calculus as compared to the conventional calculus. The present work aims at estimating the fractional model parameters of an ultracapacitor using experimental data and further investigating the dependency of fractional parameters on the operating conditions. The parameter estimation task has been formulated as an optimization problem which aims at minimizing the deviation between the model and experimental output using a hybrid optimization technique. The hybrid algorithm combines an improved version of seeker optimization algorithm for global exploration with a local search technique, i.e., Nelder---Mead simplex search. The results show that the hybrid algorithm is capable of identifying the model parameters efficiently in both time and frequency domain. The fractional behavior has been found to be dependent on the initial condition, magnitude and offset of the applied voltage.