Optimization the dynamical parameters of three phase induction motor using genetic algorithm

• Autorzy: Mohammed M.H.
• Konferencja: Computer Applications in Electrical Engineering 2012 (23-24.04.2012; Poznań, Polska)
• Języki publikacji: EN

Abstrakty

EN

This paper deals with the optimization of the induction motor design with respect to torque as a dynamical parameter. Most studies on the design of an induction motor using optimization techniques are concerned with the minimization of the motor cost and describe the optimization technique that was employed, giving the results of a single (or several) optimal design(s).Procedure includes the relationship between torque of motor and other effects as they occur in an optimal design. The optimization method that was used in this paper is Differential Evolution as genetic algorithm. Optimal results are in picture as curves or in tabula.

Słowa kluczowe

EN

induction motor; genetic algorithm; differential evolution; DE

• Wydawca: Wydawnictwo Politechniki Poznańskiej
• Czasopismo: Poznan University of Technology Academic Journals. Electrical Engineering
• Rocznik: 2012
• Tom: No. 72
• Strony: 123--128
• Opis fizyczny: Bibliogr. 6 poz., rys., tab.

Twórcy

autor

Mohammed M.H.

• Brno University of Technology

Bibliografia

• [1] IEEE Standard Test Procedure for Polyphase Induction Motor and Generators, IEEE Standard 112-1996, New York, May 1997.
• [2] J.S. Hsu, J.D. Kueck, M. Olszewski, D.A. Casada, P.J. Otaduy, and L.M. Tolbert, "Comparison of induction motor field efficiency evaluation methods," IEEE Transactions on Industry Appli., vol. 34, issue: 1, pp. l 17-125, Jan./Feb. 1998.
• [3] F. Alonge, F. D’lppolito, G. Ferrante and F.M. Raimondi, "Parameter identification of induction motor model using genetic algorithms", IEE Proc.,Control Theory Appl., vol. 145, no. 6, pp. 587-593, Nov. 1998.
• [4] T. Phumiphak, and C. Chat-uthai, Estimation of Induction Motor Parameters Based on Field Test Coupled with Genetic Algorithm. Dec. 2002.
• [5] Vasan Arunachalam, Optimization Using Differential Evolution, The University Of Western Ontario, London, Ontario, Canada lSSN: (print) 1913-3200; (online) 1913-3219; ISBN: (print) 978-0-7714-2689-6; (online) 978-0-7714-2690-2;July 2008.
• [6] RNDr. Jaroslav, Mgr.,Genetic algorithms and their application in practice, 2005.