Online stator and rotor resistance estimations of IM by using EKF

Yildiz R., Barut M., DEMİR R.

PAMUKKALE UNIVERSITY JOURNAL OF ENGINEERING SCIENCES-PAMUKKALE UNIVERSITESI MUHENDISLIK BILIMLERI DERGISI, sa.6, ss.771-778, 2024 (ESCI)

Özet

In this paper, a state and parameter observer, based on a novel extended Kalman filter (EKF), is designed to solve the parameter variations dependent estimation performance deterioration of induction motor (IM) drive systems. The proposed EKF based observer algorithm performs online estimation of the rotor mechanical speed, stator stationary axis component of the stator currents and rotorfluxes, stator resistance, rotor resistance, reciprocal of the total inertia of the system, and load torque including viscous friction term in a single EKF by using measured rotor mechanical speed and stator currents. Thus, frequency and temperature-dependent variations of the resistances are estimated to be updated in the observer, which leads to control performance enhancement of the IM drive. Moreover, to rise the dynamic performance of the observer, the load torque and reciprocal of the total inertia of the system which are mechanical parameters are also estimated. To verify the robustness of the IM drive and the estimation performance of the proposed observer, they have been tested under challenging scenarios including changes in parameters and speed reference. Moreover, the estimation performance of the proposed ninth order observer is compared with that of a sixth order EKF estimating the same electrical parameters by using directly measured speed. Ultimately, the simulation results obviously reveal the efficacy of the proposed IM drive.