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, pp.588-604, 2014 (SCI-Expanded, Scopus, TRDizin)
- Publication Type: Article / Article
- Volume: 22 Issue: 3
- Publication Date: 2014
- Doi Number: 10.3906/elk-1208-31
- Journal Name: Turkish Journal of Electrical Engineering and Computer Sciences
- Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, TR DİZİN (ULAKBİM)
- Page Numbers: pp.588-604
- Keywords: Extended Kalman filter, Induction motor, Load torque estimation, Magnetizing inductance estimation, Rotor-stator resistance estimation, Sensorless control
- Isparta University of Applied Sciences Affiliated: Yes
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 sα and isβ; stator stationary axis components of the rotor flux, φrα and φrβ; rotor angular velocity, ωm; stator resistance, Rs; rotor resistance, Rr; and load torque tL, 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 Rs, Rr, tL, and Lm. The simulations confirm the effectiveness of the proposed BI-EKF-based estimator and, consequently, the speed-sensorless DVC of the IM. © TUBITAK.