Identification of variable frequency induction motor models from operating data

Author

Proca, Amuliu Bogdan ; Keyhani, Ali

Author_Institution

Dept. of Electr. Eng., Ohio State Univ., Columbus, OH, USA

Volume

17

Issue

1

fYear

2002

fDate

3/1/2002 12:00:00 AM

Firstpage

24

Lastpage

31

Abstract

The parameters of the induction motor model vary as operating conditions change. Accurate knowledge of these parameters and their dependency on operating conditions is critical for optimal field oriented control. This paper presents a systematic approach to modeling an induction motor considering operating conditions. All parameters are assumed to vary as a function of the operating conditions. The parameters are estimated from transient data using a constrained optimization algorithm. The parameters are mapped to the operating conditions using polynomial functions and artificial neural networks. The model is validated for both steady state and transient conditions

Keywords

induction motors; machine theory; machine vector control; optimal control; optimisation; parameter estimation; rotors; sensitivity analysis; stators; artificial neural networks; constrained optimization algorithm; operating conditions; optimal field oriented control; parameters knowledge; polynomial functions; steady state conditions; systematic modelling approach; transient conditions; transient data; variable frequency induction motor models identification; Constraint optimization; Core loss; Frequency; Induction motors; Parameter estimation; Rotors; Stator cores; Synchronous motors; Testing; Voltage;

fLanguage

English

Journal_Title

Energy Conversion, IEEE Transactions on

Publisher

ieee

ISSN

0885-8969

Type

jour

DOI

10.1109/60.986433

Filename

986433