Estimation of speed and rotor position of BLDC motor using extended Kalman filter

Abstract

The brushless DC motors are preferred for industrial as well as domestic applications because of their high efficiency, quiet operation, compact form etc. Efforts have been made to make this motor cost effective and reliable by avoiding the use of position sensors and employing estimators. The BLDC motor has trapezoidal electromotive force and quasi- rectangular current waveforms. Hall sensors are usually used as the position sensors to perform current commutation for every 60 degree electrical. For the servo drive applications with high stationary accuracy of the speed and rotor position, the BLDC motor requires a rotor position sensor, such as absolute encoder. All the sensors mentioned, increase the cost and size of the motor and reduce its sturdiness. Because of these reasons, the BLDC motor without position and speed sensors has attracted wide attention. In the proposed work, extended Kalman filter will be employed to estimate the motor state variables by only using measurements of the stator line voltage and current. When applying the extended Kalman filter, it is necessary to solve some specific problems related to the voltage and current waveforms of the BLDC motor. In the proposed work, EKF will be designed and implemented for the estimation of speed and rotor position of BLDC motor through simulation, so that the motor could run at, as low speed with reasonable accuracy. It is also proposed to verify the simulation results.