Parameters Estimation of Three-Phase Induction Motor Using the Parameter Estimator App

Fares Bettahar; Sabrina Abdeddaim; Omar Charrouf; Achour Betka; Michael Short; Laid Guerrida; Belahcene taha lemdjed

doi:10.5935/jetia.v11i55.1892

Authors

Fares Bettahar Electrical Engineering Department, LGEB Laboratory, University of Biskra, Algeria https://orcid.org/0009-0005-0520-092X (unauthenticated)
Sabrina Abdeddaim Electrical Engineering Department, LGEB Laboratory, University of Biskra, Algeria https://orcid.org/0009-0006-0812-1554 (unauthenticated)
Omar Charrouf Electrical Engineering Department, LGEB Laboratory, University of Biskra, Algeria http://orcid.org/0000-0003-4254-464X (unauthenticated)
Achour Betka Electrical Engineering Department, LGEB Laboratory, University of Biskra, Algeria https://orcid.org/0000-0002-7116-4649 (unauthenticated)
Michael Short School of Computing Engineering and Digital Technologies ,Teesside University https://orcid.org/0000-0001-6290-4396 (unauthenticated)
Laid Guerrida Applied Automation and Industrial Diagnostics Laboratory ,University of Djelfa, Algeria https://orcid.org/0009-0003-0782-3798 (unauthenticated)
Belahcene taha lemdjed Laboratory of Identification, Control, Command, and Communication.,University of Biskra, Algeria https://orcid.org/0009-0006-9390-937X (unauthenticated)

DOI:

https://doi.org/10.5935/jetia.v11i55.1892

Abstract

Induction motors are among the most widely used electric motors worldwide, valued for their efficiency, robustness, and low maintenance. However, optimizing their performance requires accurate knowledge of electrical and mechanical parameters, which are nonlinear and subject to variation due to aging and operational wear. This study presents a parameter estimation technique using MATLAB’s Parameter Estimator app to determine key parameters, including stator and rotor resistances, leakage and magnetizing inductances, moment of inertia, and friction coefficient. The approach relies on experimentally measured inputs such as stator voltage, current, and motor speed, which are applied to a state-space induction motor model in MATLAB. The simulation results are compared with experimental data, specifically motor speed, d-axis current (ids) and q-axis current (iqs). The app iteratively refines the estimated parameters by minimizing the error between simulated and experimental responses. Validation using experimental data from a Siemens induction motor confirms the method’s accuracy and reliability, providing a robust framework for precise parameter estimation and enhanced motor control.