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Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/865

Title: A self-training numerical method to calculate the magnetic characteristics for switched reluctance motor drives
Authors: Xue, Xiangdang
Cheng, K. W. Eric
Ho, Siu-lau
Subjects: Least squares methods
Reluctance motors
Reluctance motor drives
Variable speed drives
Issue Date: Mar-2004
Publisher: IEEE
Citation: IEEE transactions on magnetics, Mar. 2004, v. 40, no. 2, p. 734-737.
Abstract: Based on the two-dimensional (2-D) least squares method, this paper presents a novel numerical method to calculate the magnetic characteristics for switched reluctance motor drives. In this method, the 2-D orthogonal polynomials are used to model the magnetic characteristics. The coefficients in these polynomials are determined by the 2-D least squares method. These coefficients can be computed off line and can also be trained on line. The computed results agree well with the experimental results. In addition, the effect of the order number of the polynomials on the computation errors is discussed. The proposed method is very helpful in torque prediction, simulation studies and development of sensorless control of switched reluctance motor drives.
Rights: © 2004 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.
Type: Journal/Magazine Article
URI: http://hdl.handle.net/10397/865
ISSN: 00189464
Appears in Collections:EE Journal/Magazine Articles

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