Novel version of bi input-extended Kalman filter for speed-sensorless control of induction motors with estimations of rotor and stator resistances, load torque, and inertia


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Zerdali E. , Barut M.

TURKISH JOURNAL OF ELECTRICAL ENGINEERING AND COMPUTER SCIENCES, vol.24, no.5, pp.4525-4544, 2016 (Journal Indexed in SCI) identifier identifier

  • Publication Type: Article / Article
  • Volume: 24 Issue: 5
  • Publication Date: 2016
  • Doi Number: 10.3906/elk-1408-136
  • Title of Journal : TURKISH JOURNAL OF ELECTRICAL ENGINEERING AND COMPUTER SCIENCES
  • Page Numbers: pp.4525-4544

Abstract

This study aims to develop a novel version of bi input-extended Kalman filter (BI-EKF)-based estimation technique in order to increase the number of state and parameter estimations required for speed-sensorless direct vector control (DVC) systems, which perform velocity and position controls of induction motors (IMs). For this purpose, all states required for the speed-sensorless DVC systems, besides the stator resistance R-s, the rotor resistance R-r, the load torque t(L) including the viscous friction term, and the reciprocal of total inertia 1/j(T), are simultaneously estimated by the novel BI-EKF algorithm using the measured phase currents and voltages. The effectiveness of the proposed speed-sensorless DVC systems is tested by simulations under the challenging variations of R-s, R-r, t(L), j(T), and velocity/position reference. Later, the state and parameter estimations of the novel BI-EKF algorithm are confirmed with real-time experiments in a wide speed range. Finally, in both transient and steady states, a satisfactory estimation and control performance that make this study unique are achieved.