Parameter Extraction Of An Ultracapacitor'S Equivalent Circuit Model Using A Genetic Algorithm Approach
Keywords
Genetic algorithm; Least-square algorithm; Parameter extraction; Ultracapacitor
Abstract
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).
Publication Date
12-3-2018
Publication Title
2018 IEEE Energy Conversion Congress and Exposition, ECCE 2018
Number of Pages
2493-2497
Document Type
Article; Proceedings Paper
Personal Identifier
scopus
DOI Link
https://doi.org/10.1109/ECCE.2018.8558196
Copyright Status
Unknown
Socpus ID
85060284512 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/85060284512
STARS Citation
Chen, Xi; Pise, Anirudh; Hussein, Ala; and Batarseh, Issa, "Parameter Extraction Of An Ultracapacitor'S Equivalent Circuit Model Using A Genetic Algorithm Approach" (2018). Scopus Export 2015-2019. 9533.
https://stars.library.ucf.edu/scopus2015/9533