Research Article

In-Situ Efficiency Estimation of Induction Motors Using Whale Optimization Algorithm

Volume: 5 Number: 2 June 16, 2025

In-Situ Efficiency Estimation of Induction Motors Using Whale Optimization Algorithm

Abstract

This paper investigates the in-situ efficiency prediction of induction motors using four optimization algorithms: genetic algorithm (GA), particle swarm optimization (PSO), whale optimization algorithm (WOA), and red fox optimization algorithm (RFO). Experimental evaluations were conducted on three induction motors with power ratings of 22 kW, 30 kW, and 132 kW under varying load conditions (25%, 50%, 75%, and 100%). The performance of the algorithms is tested not only under full load conditions but also under partial load conditions. This is an important requirement, given that motors usually do not run at full load in real-world applications. The algorithms were assessed based on their convergence behavior, accuracy, and experimentally measured efficiency values. The results revealed that the performance of the algorithms varies depending on the motor power and load level. While WOA is more successful at medium and high loads, PSO stands out at low loads. While GA provides higher accuracy, especially at full load on an motor, the performance of RFO varies according to the load level. In general, the performance of WOA and RFO stands out to some extent. The study demonstrates the advantages of non-intrusive methods for motor efficiency prediction that eliminate the need for direct shaft power measurements. It also offers practical benefits in industrial applications, such as reducing downtime and improving energy management.

Keywords

References

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Details

Primary Language

English

Subjects

Electrical Machines and Drives

Journal Section

Research Article

Publication Date

June 16, 2025

Submission Date

January 7, 2025

Acceptance Date

February 4, 2025

Published in Issue

Year 2025 Volume: 5 Number: 2

APA
Göztaş, M., Çunkaş, M., & Şahman, M. A. (2025). In-Situ Efficiency Estimation of Induction Motors Using Whale Optimization Algorithm. Turkish Journal of Electrical Power and Energy Systems, 5(2), 114-124. https://doi.org/10.5152/tepes.2025.25001
AMA
1.Göztaş M, Çunkaş M, Şahman MA. In-Situ Efficiency Estimation of Induction Motors Using Whale Optimization Algorithm. TEPES. 2025;5(2):114-124. doi:10.5152/tepes.2025.25001
Chicago
Göztaş, Murat, Mehmet Çunkaş, and Mehmet Akif Şahman. 2025. “In-Situ Efficiency Estimation of Induction Motors Using Whale Optimization Algorithm”. Turkish Journal of Electrical Power and Energy Systems 5 (2): 114-24. https://doi.org/10.5152/tepes.2025.25001.
EndNote
Göztaş M, Çunkaş M, Şahman MA (June 1, 2025) In-Situ Efficiency Estimation of Induction Motors Using Whale Optimization Algorithm. Turkish Journal of Electrical Power and Energy Systems 5 2 114–124.
IEEE
[1]M. Göztaş, M. Çunkaş, and M. A. Şahman, “In-Situ Efficiency Estimation of Induction Motors Using Whale Optimization Algorithm”, TEPES, vol. 5, no. 2, pp. 114–124, June 2025, doi: 10.5152/tepes.2025.25001.
ISNAD
Göztaş, Murat - Çunkaş, Mehmet - Şahman, Mehmet Akif. “In-Situ Efficiency Estimation of Induction Motors Using Whale Optimization Algorithm”. Turkish Journal of Electrical Power and Energy Systems 5/2 (June 1, 2025): 114-124. https://doi.org/10.5152/tepes.2025.25001.
JAMA
1.Göztaş M, Çunkaş M, Şahman MA. In-Situ Efficiency Estimation of Induction Motors Using Whale Optimization Algorithm. TEPES. 2025;5:114–124.
MLA
Göztaş, Murat, et al. “In-Situ Efficiency Estimation of Induction Motors Using Whale Optimization Algorithm”. Turkish Journal of Electrical Power and Energy Systems, vol. 5, no. 2, June 2025, pp. 114-2, doi:10.5152/tepes.2025.25001.
Vancouver
1.Murat Göztaş, Mehmet Çunkaş, Mehmet Akif Şahman. In-Situ Efficiency Estimation of Induction Motors Using Whale Optimization Algorithm. TEPES. 2025 Jun. 1;5(2):114-2. doi:10.5152/tepes.2025.25001