Optimal parameter estimation of permanent magnet synchronous motor by using Mothflame optimization algorithm / Abdolmajid Dejamkhooy and Sajjad Asefi

Dejamkhooy, Abdolmajid and Asefi, Sajjad (2018) Optimal parameter estimation of permanent magnet synchronous motor by using Mothflame optimization algorithm / Abdolmajid Dejamkhooy and Sajjad Asefi. Journal of Electrical and Electronic Systems Research (JEESR), 13 (1): 13. pp. 91-97. ISSN 1985-5389

Official URL: https://jeesr.uitm.edu.my/v1/

Abstract

Precision of model parameters is vital in a permanent magnet synchronous motor high performance and controllability. Since these parameters are affected by different operation conditions and load changings, then an accurate estimation strategy is quite necessary. In this paper, stator resistance and disturbed load torque, which assumed to be variable, are estimated. For this purpose, optimal parameter estimation problem is constructed as a least squares one. In the next step, the parameter identification as an optimization problem is solved by Moth-flame optimization, which is a novel nature-inspired heuristic algorithm. Simulation results and their comparison with Particle Swarm Optimization based method show high performance and good ability of the proposed method in PMSM parameter estimation.

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Item Type: Article
Creators:
Creators
Email / ID Num.
Dejamkhooy, Abdolmajid
UNSPECIFIED
Asefi, Sajjad
UNSPECIFIED
Subjects: T Technology > TK Electrical engineering. Electronics. Nuclear engineering > Applications of electric power
T Technology > TK Electrical engineering. Electronics. Nuclear engineering > Electromagnetic fields
Divisions: Universiti Teknologi MARA, Shah Alam
Journal or Publication Title: Journal of Electrical and Electronic Systems Research (JEESR)
UiTM Journal Collections: UiTM Journals > Journal of Electrical and Electronic Systems Research (JEESR)
ISSN: 1985-5389
Volume: 13
Number: 1
Page Range: pp. 91-97
Keywords: Permanent magnet synchronous motor, Model parameter estimation, Moth-flame optimization, Particle swarm optimization
Date: December 2018
URI: https://ir.uitm.edu.my/id/eprint/63119
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