Electrical Machine Winding Performance Optimization by Multi-Objective Particle Swarm Algorithm

The present work aims to optimize the magnetomotive force and the end-winding leakage inductance from a discrete distribution of conductors in electrical machines through multi-objective particle swarm heuristics. From the development of an application capable of generating the conductor distributio...

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Veröffentlicht in:Energies (Basel) Jg. 17; H. 10; S. 2286
Hauptverfasser: Martins, François S., Alvarenga, Bernardo P., Paula, Geyverson T.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Basel MDPI AG 01.05.2024
Schlagworte:
Algorithms
Analysis
Asymmetry
Electrical equipment and supplies
Electrical machinery
Genetic algorithms
magnetomotive force
multi-objective optimization
Optimization techniques
particle swarm
Symmetry
winding optimization
ISSN:1996-1073, 1996-1073
Online-Zugang:Volltext
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Beschreibung
Zusammenfassung:The present work aims to optimize the magnetomotive force and the end-winding leakage inductance from a discrete distribution of conductors in electrical machines through multi-objective particle swarm heuristics. From the development of an application capable of generating the conductor distribution for different machine configurations (single or poly-phase, single or double layer, integral or fractional slots, full or shortened pitch, with the presence of empty slots, etc.) the curves of magnetomotive force and the end-winding leakage inductance associated with the winding are computed. Taking as an optimal winding the one that presents, simultaneously, less harmonic distortion of the magnetomotive force and less leakage inductance, optimization by multi-objective particle swarm was used to obtain the optimal electrical machine configuration and the results are presented.
Bibliographie:ObjectType-Article-1
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ISSN:1996-1073
1996-1073
DOI:10.3390/en17102286