Parameter Estimation of Induction Motors Using Data Fitting from Single-Axis Sinusoidal Excitation

Abstract

Since motors in industrial plants often cannot be rotated for system identification due to mechanical loads or safety reasons, the need for standstill parameter identification becomes important. This paper proposes a method for identifying induction motor parameters at a standstill by utilizing a dataset created with the Second-Order Generalized Integrator (SOGI) and identifying the parameters through data fitting. This method offers advantages for identifying parameters under motor operating conditions by injecting voltages below the slip frequency and applying various magnetizing currents to determine the corresponding parameters. Through a deterministic model based on the impedance of the inverse gamma model, magnetizing inductance and rotor resistance are estimated via data fitting. The method presented in this paper was validated by comparing parameters using a 5.5 kW, 60 Hz, 4-pole induction motor to validate the proposed method. © 2024 IEEE.