Improved rotor flux estimation at low speeds for torque MRAS-based sensorless induction motor drives

Abstract

In this paper, an improved rotor flux estimation method for the Torque model reference adaptive schemes (TMRAS) sensorless induction machine drive is proposed to enhance its performance in low and zero speed conditions. The conventional TMRAS scheme uses an open loop flux estimator and a feedforward term, with basic low pass filters replacing the pure integrators. However, the performance of this estimation technique has drawbacks at very low speeds with incorrect flux estimation significantly affecting this inherently sensorless scheme. The performance of the proposed scheme is verified by both simulated and experimental testing for an indirect vector controlled 7.5-kW induction machine. Results show the effectiveness of the proposed estimator in the low- and zero-speed regions with improved robustness against motor parameter variation compared to the conventional method.

Publication DOI: https://doi.org/10.1109/TEC.2015.2480961
Divisions: Engineering & Applied Sciences > Electrical, Electronic & Power Engineering
Engineering & Applied Sciences > Power Electronics, Machines and Power System (PEMPS)
Engineering & Applied Sciences
Additional Information: © 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Uncontrolled Keywords: Flux estimation,induction motor,model reference adaptive system (MRAS),sensorless vector control,Energy Engineering and Power Technology,Electrical and Electronic Engineering
Full Text Link:
Related URLs: http://www.scop ... tnerID=8YFLogxK (Scopus URL)
https://ieeexpl ... ocument/7299286 (Publisher URL)
PURE Output Type: Article
Published Date: 2016-03-01
Accepted Date: 2015-09-16
Authors: Smith, Andrew N.
Gadoue, Shady M.
Finch, John W.

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