State Estimation for Sensorless Control of BLDC Machine with Particle Filter Algorithm

This paper presents a technique in order to estimate the rotor speed and position of the BLDC machine. In the proposed method, particle filter (PF) is employed to estimate state variables of the machine using measured currents and line voltages. PF is a type of stochastic filters that has wide applications in state estimation of non-linear systems. The main aim of this paper is to utilize particle filter in the sensorless control of BLDC machine and investigate proposed PF algorithm performance. In addition, effective parameters in estimation accuracy and transient response of the filter are discussed. The simulation is performed in MATLAB/SIMULINK environment and results denote that proposed sensorless drive have good accuracy in wide speed range and load torque variation. Also, the algorithm performance is not influenced by the incorrect initial position.