Turkish Journal of Electrical Engineering and Computer Sciences
DOI
10.3906/elk-1211-171
Abstract
The steady-state equivalent circuit parameters of an induction motor can be estimated using the operation characteristics that are provided by manufacturers. The characteristics of the motor used in estimation methods are the starting, maximum, and nominal torque values; the power factor; and efficiency. The operation characteristics of a motor given in data sheets are generally based on design parameters and are not suitable with real values. For this reason, in this paper, the data used in the parameter estimation for induction motors are taken from the literature. Using an optimization method for parameter estimation is useful for comparing the manufacturer values and values at the end of estimation, as well as minimizing the error in between. There are many methods in the literature for the parameter estimation of induction motors. In this study, the estimation is made using the charged system search (CSS), differential evolution algorithm (DEA), particle swarm optimization, and genetic algorithm optimization techniques. The CSS algorithm is first applied for estimation of the parameters of an induction motor. The results obtained from all of the methods show that the CSS algorithm is suitable with the DEA. From the obtained results, it is understood that an exact approach can be made to equivalent circuit parameters in case the values given by the manufacturer model the motor properly.
Keywords
Induction motor, exact equivalent circuit parameters, torque values, charged system search, differential evolution algorithm, particle swarm optimization, genetic algorithm
First Page
1177
Last Page
1192
Recommended Citation
ÇANAKOĞLU, ALİ İHSAN; YETGİN, ASIM GÖKHAN; TEMURTAŞ, HASAN; and TURAN, MUSTAFA
(2014)
"Induction motor parameter estimation using metaheuristic methods,"
Turkish Journal of Electrical Engineering and Computer Sciences: Vol. 22:
No.
5, Article 6.
https://doi.org/10.3906/elk-1211-171
Available at:
https://journals.tubitak.gov.tr/elektrik/vol22/iss5/6
Included in
Computer Engineering Commons, Computer Sciences Commons, Electrical and Computer Engineering Commons