A new algorithm for flux and speed estimation in induction machine

Abstract

A new reduced-order extended Kalman filter to estimate the rotor flux components and speed of an induction machine for speed sensorless vector control is proposed. With this method, two rotor flux components are selected as the state variables, and the rotor speed as an estimated parameter is regarded as an augmented state variable. The algorithm with reduced order decreases the computational complexity and makes the proposed estimator feasible to be implemented in real time. The simulation results show high accuracy of the estimation algorithm, and verify the usefulness of the proposed algorithm.