In-situ efficiency and parameter estimation for induction motors using heuristic optimization
- Authors
- Murat Göztaş, Mehmet Akif Sahman, Mehmet Çunkaş
- Journal / Conference
- Scientific Reports
- Year
- 2026
Abstract
Electric motors, especially three-phase induction motors, consume a significant portion of industrial electricity, making their efficiency critical for energy conservation. Traditional efficiency assessments require intrusive, labor-intensive laboratory tests, limiting in-situ evaluations. We propose a non-intrusive, heuristic optimization-based method compliant with IEEE Std-112 A/F1 to simultaneously estimate equivalent circuit parameters and in-situ efficiency using only field-measurable electrical quantities. Eight meta-heuristic algorithms were applied across six motors of varying power ratings and load conditions, with results validated against standard test data. The method achieved mean absolute errors below 0.7% at full load, demonstrating high accuracy and stability. This approach enables reliable, low-cost, and continuous efficiency monitoring under real operating conditions, offering practical benefits for industrial energy management and motor performance assessment.
Göztaş, M., Sahman, M. A., & Çunkaş, M. (2026). Sezgisel optimizasyon kullanarak endüksiyon motorları için yerinde verimlilik ve parametre tahmini. *Scientific Reports*. https://doi.org/10.1038/s41598-025-34932-1
Göztaş, Murat, et al.. "Sezgisel optimizasyon kullanarak endüksiyon motorları için yerinde verimlilik ve parametre tahmini". *Scientific Reports*, 2026. DOI: https://doi.org/10.1038/s41598-025-34932-1.
GöZTAş, M.; SAHMAN, M. A.; ÇUNKAş, M.. Sezgisel optimizasyon kullanarak endüksiyon motorları için yerinde verimlilik ve parametre tahmini. Scientific Reports, 2026. DOI: https://doi.org/10.1038/s41598-025-34932-1
@article{gzta2026,
title = {In-situ efficiency and parameter estimation for induction motors using heuristic optimization},
author = {Göztaş, Murat and Sahman, Mehmet Akif and Çunkaş, Mehmet},
journal = {Scientific Reports},
year = {2026},
volume = {16},
number = {1},
doi = {10.1038/s41598-025-34932-1}
}