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 language | English |
|---|---|
| Pages (from-to) | 555-569 |
| Number of pages | 15 |
| Journal | Electric Power Components and Systems |
| Volume | 32 |
| Issue number | 6 |
| DOIs | |
| Publication status | Published - Jun 2004 |
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Keywords
- Motor control
- SPICE modeling
- Torus motor drives
ASJC Scopus subject areas
- Electrical and Electronic Engineering
Cite this
Dynamic model of Torus motor drive using ANN and FSE methods for the back EMF estimation. / Al-Badi, A. H.; Gastli, A.
In: Electric Power Components and Systems, Vol. 32, No. 6, 06.2004, p. 555-569.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Dynamic model of Torus motor drive using ANN and FSE methods for the back EMF estimation
AU - Al-Badi, A. H.
AU - Gastli, A.
PY - 2004/6
Y1 - 2004/6
N2 - 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.
AB - 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.
KW - Motor control
KW - SPICE modeling
KW - Torus motor drives
UR - http://www.scopus.com/inward/record.url?scp=2542472678&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=2542472678&partnerID=8YFLogxK
U2 - 10.1080/15325000490228405
DO - 10.1080/15325000490228405
M3 - Article
AN - SCOPUS:2542472678
VL - 32
SP - 555
EP - 569
JO - Electric Machines and Power Systems
JF - Electric Machines and Power Systems
SN - 1532-5008
IS - 6
ER -