Title :
State and parameter estimation in induction motor using the Extended Kalman Filtering algorithm
Author :
Saadettin Aksoy;Aydin Mühürcü;Hakan Kizmaz
Author_Institution :
Department of Electrical and Electronics Engineering, Faculty of Engineering, Sakarya University 54187, Esentepe, Adapazarı
Abstract :
This paper presents an on-line estimation algorithm for parameters and states estimation of an induction motor. The algorithm is based on the measurements of the stator voltages, currents and rotor speed, and uses Extended Kalman Filtering (EKF) technique. Altough the computation of the stator currents is not always needed in practice, we include these variables to the state vector for completeness of the algorithm and to check the results. A squirrel-cage induction motor is fed from sinusoidal and six-steps sources at different times in order to observe the performance of the proposed estimator for different operation conditions. Estimation results which used experimental data showed that the proposed algorithm is capable of estimating the states and parameters of induction motors.
Keywords :
"Induction motors","Rotors","Estimation","Stators","Kalman filters","Mathematical model","Covariance matrix"
Conference_Titel :
Modern Electric Power Systems (MEPS), 2010 Proceedings of the International Symposium