Turkish Journal of Electrical Engineering and Computer Sciences
DOI
10.3906/elk-1208-31
Abstract
This study introduces a novel bi input-extended Kalman filter (BI-EKF)-based speed-sensorless direct vector control (DVC) of an induction motor (IM). The proposed BI-EKF-based estimator includes online estimations of the stator stationary axis components of the stator currents, i_{s\alpha} and i_{s\beta}; stator stationary axis components of the rotor flux, \varphi_{r\alpha} and \varphi_{r\beta}; rotor angular velocity, \omega_m; stator resistance, R_s; rotor resistance, R_r; and load torque t_L, as well as the magnetizing inductance, L_m, by only supposing that the stator phase currents and voltages are measured. Thus, the speed-sensorless DVC of the IM with the inclusion of the proposed estimator is able to be perfectly operated at a wide speed range, varying from zero speed to beyond the rated/based speed under the extreme variations in R_s, R_r, t_L, and L_m . The simulations confirm the effectiveness of the proposed BI-EKF-based estimator and, consequently, the speed-sensorless DVC of the IM.
Keywords
Induction motor, extended Kalman filter, rotor-stator resistance estimation, load torque estimation, magnetizing inductance estimation, sensorless control
First Page
588
Last Page
604
Recommended Citation
İNAN, REMZİ and BARUT, MURAT
(2014)
"Bi input-extended Kalman filter-based speed-sensorless control of an induction machine capable of working in the field-weakening region,"
Turkish Journal of Electrical Engineering and Computer Sciences: Vol. 22:
No.
3, Article 7.
https://doi.org/10.3906/elk-1208-31
Available at:
https://journals.tubitak.gov.tr/elektrik/vol22/iss3/7
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