Estimation of speed, stator temperature and rotor temperature in cage induction motor drive using the extended Kalman filter algorithm

Author

Al-Tayie, J.K. ; Acarnley, P.P.

Volume

144

Issue

5

fYear

1997

fDate

9/1/1997 12:00:00 AM

Firstpage

301

Lastpage

309

Abstract

Application of the extended Kalman filter (EKF) algorithm to the estimation of speed, stator temperature and rotor temperature in induction motor drives is described. The estimation technique is based on a closed-loop observer that incorporates mathematical models of the electrical, mechanical and thermal processes occurring within the induction motor. Speed and temperature estimation is independent of the drive´s operating mode, though closed-loop estimation is possible only if stator currents are nonzero. The EKF algorithm used to perform the estimation process has been implemented using a TMS320C30 digital signal processor and experimental results demonstrate the effectiveness of the new estimation algorithm

Keywords

Kalman filters; closed loop systems; digital signal processing chips; induction motor drives; observers; parameter estimation; rotors; squirrel cage motors; stators; TMS320C30 digital signal processor; cage induction motor drive; closed-loop estimation; closed-loop observer; electrical processes; extended Kalman filter algorithm; mathematical models; mechanical processes; nonzero stator currents; rotor temperature estimation; speed estimation; stator temperature estimation; thermal processes;

fLanguage

English

Journal_Title

Electric Power Applications, IEE Proceedings -

Publisher

iet

ISSN

1350-2352

Type

jour

DOI

10.1049/ip-epa:19971166

Filename

660224