Improved flux pattern by third harmonic injection for multiphase induction machines using neural network

Ayman Abdel-Khalik, Shady M. Gadoue

Research output: Contribution to journalArticle

4 Citations (Scopus)

Abstract

This paper presents a modified V/f control strategy using neural network with an improved flux pattern using third harmonic injection for multiphase induction machines. The control objective is to generate a nearly rectangular air-gap flux, resulting in an improved machine power density for the required speed range. If just a proportional relation is used between the third harmonic and fundamental plane voltage magnitudes with zero phase shift, variable misalignment between fundamental and third air-gap flux components occurs with varying mechanical loading as a result of stator voltage drop. Due to this misalignment, saturation may take place which affects the total flux and increases machine iron losses. Neural network is used to obtain the required injected voltage phasors magnitudes and angles to ensure that the air-gap flux is near rectangular with a maximum value of 1 pu for all loading conditions. Simulations are carried out on an eleven-phase induction machine to validate the proposed controller using MATLAB/Simulink.

Original languageEnglish
Pages (from-to)163-169
Number of pages7
JournalAlexandria Engineering Journal
Volume50
Issue number2
DOIs
Publication statusPublished - Jun 2011
Externally publishedYes

Fingerprint

Fluxes
Neural networks
Air
Electric potential
Phase shift
Stators
MATLAB
Iron
Controllers

Keywords

  • Eleven-phase
  • Multiphase induction machine
  • Rectangular air-gap flux
  • Third harmonic injection

ASJC Scopus subject areas

  • Engineering(all)

Cite this

Improved flux pattern by third harmonic injection for multiphase induction machines using neural network. / Abdel-Khalik, Ayman; Gadoue, Shady M.

In: Alexandria Engineering Journal, Vol. 50, No. 2, 06.2011, p. 163-169.

Research output: Contribution to journalArticle

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