TY - JOUR
T1 - Parameters Estimation of Three-Phase Induction Motor Using the Parameter Estimator App
AU - Bettahar, Fares
AU - Abdeddaim, Sabrina
AU - Charrouf, Omar
AU - Betka, Achour
AU - Short, Michael
AU - Guerrida, Laid
AU - Lemdjed, Belahcene Taha
N1 - Publisher Copyright:
©2025 by authors and Galileo Institute of Technology and Education of the Amazon (ITEGAM).
PY - 2025/9/25
Y1 - 2025/9/25
N2 - 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.
AB - 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.
UR - https://www.scopus.com/pages/publications/105018181864
U2 - 10.5935/jetia.v11i55.1892
DO - 10.5935/jetia.v11i55.1892
M3 - Article
AN - SCOPUS:105018181864
SN - 2447-0228
VL - 11
SP - 73
EP - 85
JO - Journal of Engineering and Technology for Industrial Applications
JF - Journal of Engineering and Technology for Industrial Applications
IS - 55
ER -