Identification of three phase induction machines equivalent circuits parameters using multi-objective genetic algorithms

Praveen Kumar, Ankit Dalal, Amit Kumar Singh

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

20 Scopus citations

Abstract

The use of multiobjective optimization technique in determining the values of the steady-state equivalent circuit parameters of a three-phase squirrel-cage induction machine is discussed. The identification procedure is based on the steady state phase current versus slip and torque versus slip characteristics. Nonlinearities in the Induction machine such as saturation effects and skin effects are also taken into account. The proposed technique is based on Multiobjective Genetic Algorithms (MOGA). The MOGA is used to minimize the error between the actual data and the data obtained by equivalent circuit. The robustness of the method is shown by identifying parameters of the induction motor in three different cases. The simulation results show that the method successfully estimates the motor parameters.

Original languageEnglish
Title of host publicationProceedings - 2014 International Conference on Electrical Machines, ICEM 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1211-1217
Number of pages7
ISBN (Electronic)9781479943890
DOIs
StatePublished - Nov 17 2014
Externally publishedYes
Event21st International Conference on Electrical Machines, ICEM 2014 - Berlin, Germany
Duration: Sep 2 2014Sep 5 2014

Publication series

NameProceedings - 2014 International Conference on Electrical Machines, ICEM 2014

Conference

Conference21st International Conference on Electrical Machines, ICEM 2014
Country/TerritoryGermany
CityBerlin
Period09/2/1409/5/14

Keywords

  • Equivalent circuits
  • genetic algorithm
  • induction motor
  • parameter estimation

Fingerprint

Dive into the research topics of 'Identification of three phase induction machines equivalent circuits parameters using multi-objective genetic algorithms'. Together they form a unique fingerprint.

Cite this