Barut, MuratDemir, RidvanZerdali, EmrahInan, Remzi2019-08-012019-08-0120120278-0046https://dx.doi.org/10.1109/TIE.2011.2178209https://hdl.handle.net/11480/4530This paper presents the real-time implementation of a bi input-extended Kalman filter (EKF) (BI-EKF)-based estimator in order to overcome the simultaneous estimation problem of the variations in stator resistance R-s and rotor resistance R-r' aside from the load torque t(L) and all states required for the speed-sensorless control of induction motors (IMs) in the wide speed range. BI-EKF algorithm consists of a single EKF algorithm using consecutively two inputs based on two extended IM models developed for the simultaneous estimation of R-r' and R-s. Therefore, from the point of real-time implementation, it requires less memory than previous EKF-based studies exploiting two separate EKF algorithms for the same aim. By using the measured stator phase voltages and currents, the developed estimation algorithm is tested with real-time experiments under challenging variations of R-s, R-r', and t(L) in a wide speed range; the results obtained from BI-EKF reveal significant improvement in the all estimated states and parameters when compared with those of the single EKFs estimating only R-r' or R-s.eninfo:eu-repo/semantics/closedAccessExtended Kalman filterinduction motors (IMs)load torque estimationrotor and stator resistance estimationsensorless controlArticle59114197420610.1109/TIE.2011.21782092-s2.0-84862998458Q1WOS:000305748500021Q1