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

被引：1

作者：

Martins, Francois S. ^{[1
]}

Alvarenga, Bernardo P. ^{[1
]}

Paula, Geyverson T. ^{[1
]}

机构：

[1] Univ Fed Goias, Sch Elect Mech & Comp Engn, Av Univ 1488, BR-74605010 Goiania, Brazil

来源：

ENERGIES | 2024年 / 17卷 / 10期

关键词：

magnetomotive force; winding optimization; particle swarm; multi-objective optimization;

D O I：

10.3390/en17102286

中图分类号：

TE [石油、天然气工业]; TK [能源与动力工程];

学科分类号：

0807 ; 0820 ;

摘要：

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.

引用

页数：19

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