Nonlinear estimation of stator winding resistance in a brushless DC motor

Author

Wanlin Zhang ; Gadsden, S. Andrew ; Habibi, Saeid R.

Author_Institution

Dept. of Mech. Eng., McMaster Univ., Hamilton, ON, Canada

fYear

2013

fDate

17-19 June 2013

Firstpage

4699

Lastpage

4704

Abstract

Estimation of stator winding resistance in brushless DC motors is important for fault detection and diagnosis. The most popular linear estimation method to date remains the Kalman filter (KF), and the extended form (EKF) for nonlinear systems and measurements. However, a relatively new method referred to as the smooth variable structure filter (SVSF) was introduced in an effort to overcome some of the instability issues with the KF. Further to this development, a new nonlinear estimation strategy was created based on combining elements of the EKF with the SVSF. This new method, referred to as the EK-SVSF, has been applied to a brushless DC motor for estimating the stator winding values. The results are compared with the popular EKF.

Keywords

Kalman filters; brushless DC motors; fault diagnosis; machine windings; stators; EK-SVSF; brushless DC motor; extended Kalman filter; fault detection; fault diagnosis; instability issues; nonlinear estimation; nonlinear estimation strategy; nonlinear systems; smooth variable structure filter; stator winding resistance; stator winding resistance estimation; stator winding values; Brushless DC motors; Covariance matrices; Estimation; Mathematical model; Resistance; Uncertainty; Windings;

fLanguage

English

Publisher

ieee

Conference_Titel

American Control Conference (ACC), 2013

Conference_Location

Washington, DC

ISSN

0743-1619

Print_ISBN

978-1-4799-0177-7

Type

conf

DOI

10.1109/ACC.2013.6580564

Filename

6580564