Abstract
Axial-flux, Permanent-magnet machines are used in different applications where the power and torque density requirements are very high. These machines have simple structures, relatively high efficiencies and low cost. The parameters of these machines are very small compared with the parameters of conventional machines. Different measuring methods are normally used in order to obtain good estimates of the machine parameters. These methods are difficult to perform, costly and time consuming. This paper proposes the use of Particle Swarm Optimization (PSO) technique to predict the self and mutual inductances of the 11-phase Torus machine automatically.
| Original language | English |
|---|---|
| Title of host publication | IEEE Power and Energy Society 2008 General Meeting: Conversion and Delivery of Electrical Energy in the 21st Century, PES |
| DOIs | |
| Publication status | Published - 2008 |
| Event | IEEE Power and Energy Society 2008 General Meeting: Conversion and Delivery of Electrical Energy in the 21st Century, PES - Pittsburgh, PA, United States Duration: Jul 20 2008 → Jul 24 2008 |
Other
| Other | IEEE Power and Energy Society 2008 General Meeting: Conversion and Delivery of Electrical Energy in the 21st Century, PES |
|---|---|
| Country | United States |
| City | Pittsburgh, PA |
| Period | 7/20/08 → 7/24/08 |
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Keywords
- Parameter identification
- Particle Swarm Optimization technique
- Torus machine
ASJC Scopus subject areas
- Energy Engineering and Power Technology
- Electrical and Electronic Engineering
Cite this
Parameters identification of 11-phase Torus generator using Particle Swarm Optimization technique. / Al-Hinai, A.; Al-Badi, A.
IEEE Power and Energy Society 2008 General Meeting: Conversion and Delivery of Electrical Energy in the 21st Century, PES. 2008. 4596691.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Parameters identification of 11-phase Torus generator using Particle Swarm Optimization technique
AU - Al-Hinai, A.
AU - Al-Badi, A.
PY - 2008
Y1 - 2008
N2 - Axial-flux, Permanent-magnet machines are used in different applications where the power and torque density requirements are very high. These machines have simple structures, relatively high efficiencies and low cost. The parameters of these machines are very small compared with the parameters of conventional machines. Different measuring methods are normally used in order to obtain good estimates of the machine parameters. These methods are difficult to perform, costly and time consuming. This paper proposes the use of Particle Swarm Optimization (PSO) technique to predict the self and mutual inductances of the 11-phase Torus machine automatically.
AB - Axial-flux, Permanent-magnet machines are used in different applications where the power and torque density requirements are very high. These machines have simple structures, relatively high efficiencies and low cost. The parameters of these machines are very small compared with the parameters of conventional machines. Different measuring methods are normally used in order to obtain good estimates of the machine parameters. These methods are difficult to perform, costly and time consuming. This paper proposes the use of Particle Swarm Optimization (PSO) technique to predict the self and mutual inductances of the 11-phase Torus machine automatically.
KW - Parameter identification
KW - Particle Swarm Optimization technique
KW - Torus machine
UR - http://www.scopus.com/inward/record.url?scp=52349115374&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=52349115374&partnerID=8YFLogxK
U2 - 10.1109/PES.2008.4596691
DO - 10.1109/PES.2008.4596691
M3 - Conference contribution
SN - 9781424419067
BT - IEEE Power and Energy Society 2008 General Meeting: Conversion and Delivery of Electrical Energy in the 21st Century, PES
ER -