Design and implementation of the extended Kalman filter for thespeed and rotor position estimation of brushless DC motor
Terzic, B.
Jadric, M.
Fac. of Electr. Eng., Mech. & Naval Archit., Univ. of Split;
This paper appears in: Industrial Electronics, IEEE Transactions on
Publication Date: Dec 2001
Volume: 48,
Issue: 6
On page(s): 1065-1073
ISSN: 0278-0046
References Cited: 17
CODEN: ITIED6
INSPEC Accession Number: 7122713
Digital Object Identifier: 10.1109/41.969385
Current Version Published: 2002-08-07
Abstract
A method for speed and rotor position estimation of a brushless DC
motor (BLDCM) is presented in this paper. An extended Kalman filter
(EKF) is employed to estimate the motor state variables by only using
measurements of the stator fine voltages and currents. When applying the
EKF, it was necessary to solve some specific problems related to the
voltage and current waveforms of the BLDCM. During the estimation
procedure, the voltage- and current-measuring signals are not filtered,
which is otherwise usually done when applying similar methods. The
voltage average value during the sampling interval is obtained by
combining measurements and calculations, owing to the application of the
predictive current controller which is based on the mathematical model
of motor. Two variants of the estimation algorithm are considered: (1)
speed and rotor position are estimated with constant motor parameters
and (2) the stator resistance is estimated simultaneously with motor
state variables. In order to verify the estimation results, the
laboratory setup has been constructed using a motor with ratings of 1.5
kW, 2000 r/min, fed by an insulated gate bipolar transistor inverter.
The speed and current controls, as well as the estimation algorithm,
have been implemented by a digital signal processor (TMS320C50). The
experimental results show that is possible to estimate the speed and
rotor position of the BLDCM with sufficient accuracy in both
steady-state and dynamic operation. Introducing the estimation of the
stator resistance, the speed estimation accuracy is increased,
particularly at low speeds. At the end of the paper, the characteristics
of the sensorless drive are analyzed. A sensorless speed control system
has been achieved with maximum steady-state error between reference and
actual motor speed of ±1% at speeds above 5% of the rated value
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