Dynamic model of Torus motor drive using ANN and FSE methods for the back EMF estimation

A. H. Al-Badi*, A. Gastli

*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

Abstract

In this article, two dynamic models of the Torus machine are discussed. The first model uses the Fourier series expansion for the back emf and is implemented with PSpice. The second model uses the neural network estimation of the back emf and is implemented with Matlab/Simulink. The models may be used to study the steady-state as well as the transient performances of the machine operating as a motor or as a generator. Experimental results are compared with Matlab/Simulink and PSpice predictions for a number of operating conditions, including the complete starting transient. Excellent correlation between the experimental and simulated results is obtained which validates the Torus machine modeling approach.

Original languageEnglish
Pages (from-to)555-569
Number of pages15
JournalElectric Power Components and Systems
Volume32
Issue number6
DOIs
Publication statusPublished - Jun 2004

Keywords

  • Motor control
  • SPICE modeling
  • Torus motor drives

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

Access to Document

Fingerprint Dive into the research topics of 'Dynamic model of Torus motor drive using ANN and FSE methods for the back EMF estimation'. Together they form a unique fingerprint.

Cite this