Meta-Heuristic Based Design and Optimization of Double Stator-Single Rotor Axial-Flux Induction Generator

In this paper, the design and optimization of a Double Stator-Single Rotor Axial-Flux Induction Generator (DSSR-AFIG), specifically for low-power wind turbine applications, have been presented. By specifying a 8-kW, 400V/50Hz design, the research utilizes Multi-Objective Grey Wolf Optimization (MOGWO) to fine-tune the generator’s geometric parameters, including the dimensions of stator and rotor slots. Different designs were examined by changing the weights of the objective functions of the optimization. First, a DSSR-AFIG design targeting 80% total loss reduction and 20% volume minimization, then a DSSR-AFIG design targeting 80% volume minimization and 20% total loss minimization, and finally a DSSR-AFIG design accepting both objective functions with equal weights were obtained. The efficiencies and power density values of these designs were compared with each others. Additionally, the consistency and accuracy of the established algorithm were also proven by the performed FEAs.

Authors

Institutions

Publication Details

Published
2025-05-18
DOI
https://doi.org/10.1109/iemdc60492.2025.11060987
Primary Topic
Electric Motor Design and Analysis
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Meta-Heuristic Based Design and Optimization of Double Stator-Single Rotor Axial-Flux Induction Generator

Tuğberk Özmen, Mehmet Onur Gülbahçe, Batı Eren Ergun, Arda Akyıldız et al.
Electric Motor Design and Analysis
article

Meta-Heuristic Based Design and Optimization of Double Stator-Single Rotor Axial-Flux Induction Generator

Tuğberk Özmen, Mehmet Onur Gülbahçe, Batı Eren Ergun, Arda Akyıldız, Bahaddin Goksun
article en

Abstract

In this paper, the design and optimization of a Double Stator-Single Rotor Axial-Flux Induction Generator (DSSR-AFIG), specifically for low-power wind turbine applications, have been presented. By specifying a 8-kW, 400V/50Hz design, the research utilizes Multi-Objective Grey Wolf Optimization (MOGWO) to fine-tune the generator’s geometric parameters, including the dimensions of stator and rotor slots. Different designs were examined by changing the weights of the objective functions of the optimization. First, a DSSR-AFIG design targeting 80% total loss reduction and 20% volume minimization, then a DSSR-AFIG design targeting 80% volume minimization and 20% total loss minimization, and finally a DSSR-AFIG design accepting both objective functions with equal weights were obtained. The efficiencies and power density values of these designs were compared with each others. Additionally, the consistency and accuracy of the established algorithm were also proven by the performed FEAs.

Manisa Celal Bayar University (TR), Istanbul Technical University (TR)
Affordable and clean energy
Openalex Percentile: Top 86%
Electric Motor Design and Analysis
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.