Parameter estimation of induction motors using PWM inverters

Induction motor parameter identification algorithms utilizing the DSP controlled 3 phase PWM inverter constructed in [12] are discussed. A single stator voltage test is carried out with the machine's rotor standing still. The resulting transient is used to determine machine electrical parameters. Several algorithms for this are discussed, extending work discussed in [21], (34], and (35]. The final algorithm tested uses a radial basis function network to approximate a function mapping from a time lag space consisting of the dq transformed stator currents to a space of machine electrical parameters. This algorithm is attractive because it is very easy to perform, consisting of one nonlinear step and one linear step. The original goal for the hardware of [12] was to perform adaptive field-oriented control on small induction motors. Several observers and online flux estimation methods, as well as alternative algorithms including neural networks and genetic algorithms, were looked at over the course of this year. This background is provided in the appendix, in order to aid future work on this project.

Department dc:contributor.department

Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

1999

Author dc:creator

• Evangelista, Dennis J. (Dennis Jose), 1977-

Advisor dc:contributor.advisor

• Steven B. Leeb and Steven R. Shaw.

• Electrical Engineering and Computer Science

Statement dc:rights

• M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/1721.1/9457

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/9457