Sensorless vector control of 3-phase BLDC motor using a novel Extended Kalman

Author

Ejlali, A. ; Soleimani, J.

Author_Institution

Electr. Eng. Dept., Iran Univ. of Sci. & Technol. (IUST), Tehran, Iran

fYear

2012

fDate

2-4 Aug. 2012

Firstpage

1

Lastpage

6

Abstract

This paper execute trial and error method called Active Learning Method (ALM) in Extended Kalman Filter (EKF) that is accompanied by some problems. The proposed EKF estimator used in sensorless vector control of brushless DC motor (BLDCM). This estimator uses stator voltages and currents to estimates state variables. By this estimator, filtering of current and voltage can be eliminated due to inherent properties of kalman filter. In this scheme, current controllers have been used for control strategy. Simulation results show good performance of presented sensorless scheme for BLDCM.

Keywords

Kalman filters; brushless DC motors; electric current control; estimation theory; learning systems; machine vector control; nonlinear filters; sensorless machine control; 3-phase BLDC motor; ALM; EKF estimation; active learning method; brushless DC motor; current controller; extended Kalman filter estimation; sensorless vector control; state variable estimation; stator current filtering estimation; stator voltage filtering estimation; trial-error method; Brushless DC motors; Covariance matrix; Equations; Kalman filters; Mathematical model; Active learning method; Brushless DC Motor (BLDCM); Current controller; Extended kalman filter (EKF); Vector control;

fLanguage

English

Publisher

ieee

Conference_Titel

Advances in Power Conversion and Energy Technologies (APCET), 2012 International Conference on

Conference_Location

Mylavaram, Andhra Pradesh

Print_ISBN

978-1-4673-2042-9

Type

conf

DOI

10.1109/APCET.2012.6302062

Filename

6302062