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Numerical methods for identification of induction motor parameters

IP.com Disclosure Number: IPCOM000128099D
Original Publication Date: 1997-Dec-31
Included in the Prior Art Database: 2005-Sep-14
Document File: 5 page(s) / 18K

Publishing Venue

Software Patent Institute

Related People

Shaw, Steven Robert: AUTHOR [+3]

Related Documents

http://theses.mit.edu:80/Dienst/UI/2.0/Describe/0018.mit.theses/1997-307: URL

Abstract

This thesis presents two methods for determining the parameters of a lumped induction motor model given stator current and voltage measurements during a startup transient. The first method extrapolates a series of biased parameter estimates obtained from reduced order models to an unbiased estimate using rational functions. The second method uses part of the lumped parameter model as a rotor current estimator. The estimated rotor currents are used to identify the mechanical subsystem and to predict the rotor voltages. Errors in the predicted rotor voltages are minimized using standard non-linear least squares techniques. Both methods are demonstrated on simulated and measured induction motor transient data.

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 This record is the front matter from a document that appears on a server at MIT and is used through permission from MIT. See http://theses.mit.edu:80/Dienst/UI/2.0/Describe/0018.mit.theses/1997-307 for copyright details and for the full document in image form.

Numerical Methods for Identification of Induction Motor Parameters

by

Steven Robert Shaw
S.B. Massachusetts Institute of Technology (1995)

Submitted in partial fulfillment of the requirements for the degree of Master of Engineering in Electrical Engineer

at the Massachusetts Institute of Technology

February 1997
SIGNATURE OF author: [[signature omitted]]

Department of Electrical Engineering and Computer Science

January 24, 1997

CERTIFIED BY: [[SIGNATURE OMITTED]]

Steven B. Leeb Assistant Professor Thesis Supervisor ACCEPTED BY: [[SIGNATURE OMITTED]]

Arthur C. Smith Chairman, Departmental Committee on Graduate Theses ARCHIVES MASSACHUSETTS INSTITUTE OF TECHNOLOGY LIBRARIES OCT 29 1997

Massachusetts Institute of Technology Page 1 Dec 31, 1997

Page 2 of 5

Numerical methods for identification of induction motor parameters

Numerical Methods for Identification of Induction Motor

Parameters

by

Steven Robert Shaw

Submitted to the Department of Electrical Engineering and Computer Science on January 24, 1997, in partial fulfillment of the requirements for the degrees of Master of Engineering in Electrical Engineering and Computer Science and Electrical Engineer

Abstract

This thesis presents two methods for determining the parameters of a lumped induction motor model given stator current and voltage measurements during a startup transient. The first method extrapolates a series of biased parameter estimates obtained from reduced order models to an unbiased estimate using rational functions. The second method uses part of the lumped parameter model as a rotor current estimator. The estimated rotor currents are used to identify the mechanical subsystem and to predict the rotor voltages. Errors in the predicted rotor voltages are minimized using standard non-linear least squares techniques. Both methods are demonstrated on simulated and measured induction motor transient data.

Thesis Supervisor: Steven B. Leeb Title: Assistant Professor

Acknowledgments

I would like to thank Professor Steven Leeb for his support, guidance and patience. Professor Leeb's enthusiasm is both unwavering and inspiring.

Tektronix and Intel generously donated equipment essential to this work.

This project was supported by ORD/EPG and Lincoln Labs, ACC Project No. 182A administered by Marc Bernstein.

Contents

1 Introduction.....11
1.1 Thesis Outline.....12
1.2 Overview of related work.....13
1.3 Methods for system identification.....16
1.3.1 Linear least squares.....17
1.3.2 Weighted least squares.....18

Massachusetts Institute of Technology Page 2 Dec 31, 1997

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Numerical methods for identification of induction motor parameters

1.3.3 Numerical methods for finding (AT A)-1.....20
1.3.4 Non-linear least sq...