Parameter Extraction of An Ultracapacitor's Equivalent Circuit Model Using a Genetic Algorithm Approach

This paper proposes a new method for extracting some equivalent-circuit model parameters of an ultracapacitor using Genetic Algorithm (GA) approach. Ultracapacitors have two main parameters that dictates their performance: internal resistance and the capacitance. These parameters change drastically with temperature variations and age conditions. These parameters also vary from an ultracapacitor to another even if they were from the same manufacturer due to the manufacturing process. Hence, in order to allow accurate prediction of the ultracapacitor performance, an accurate value of these parameters is vital. The proposed algorithm is presented in this paper followed by experimental verification using a BCAP3000 2.7V, 3000F Maxwell ultracapacitor. The accuracy of the algorithm is evaluated and compared to the traditional Least-square Algorithm (LSA).