DocumentCode :
2055739
Title :
Modeling of salient-pole wound-rotor synchronous machines for population-based design
Author :
Bash, M. ; Pekarek, S.
fYear :
2012
fDate :
22-26 July 2012
Firstpage :
1
Lastpage :
1
Abstract :
In recent years, population-based methods (evolutionary algorithms, particle swarm methods, etc.) have emerged as an effective tool for component and system design. Although relatively straightforward to apply, to capitalize on their potential, one must be able to explore a large design space. Herein a magnetic equivalent circuit model is described to enable large-design-space exploration of salient-pole wound-rotor synchronous machine drive systems. Specifically, the model has been derived to evaluate machines with an arbitrary number of poles, stator slots (integer slots/pole/phase), winding layout, magnetic material, and a wide range of stator and rotor geometries. In addition, the model and solution technique have been structured to minimize the computational effort. An important attribute of the model is that saturation is handled with relatively few iterations and without the need for a relaxation factor to obtain convergence.
Keywords :
equivalent circuits; evolutionary computation; magnetic circuits; particle swarm optimisation; rotors; synchronous motor drives; component design; evolutionary algorithm; iteration method; large-design-space exploration; magnetic equivalent circuit model; magnetic material; particle swarm methods; poles; population-based design; rotor geometry; salient-pole wound-rotor synchronous machine drive model; stator geometry; stator slots; system design; Computational modeling; Educational institutions; Evolutionary computation; Integrated circuit modeling; Stator windings; Synchronous machines;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Power and Energy Society General Meeting, 2012 IEEE
Conference_Location :
San Diego, CA
ISSN :
1944-9925
Print_ISBN :
978-1-4673-2727-5
Electronic_ISBN :
1944-9925
Type :
conf
DOI :
10.1109/PESGM.2012.6345185
Filename :
6345185
Link To Document :
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