Abstract
Sliding mode observer (SMO) for permanent magnet synchronous motor (PMSM) speed and rotor position is used in this paper to realize sensorless control. According to the PMSM mathematical model and the sliding mode control theory, the SMO model was given. The stability condition of SMO is studied to make sure that the observer is stable in converging to the sliding mode plane. This paper analyzes the structure and performance of the proposed SMO strategy with SIMULINK based simulation. Simulation results are presented to verify the proposed sensorless control algorithm.
Highlights
Permanent magnet synchronous machines (PMSM) have been increasingly applied for drive applications due to their simple structure, high power density, high torque to inertia ratio and high efficiency
To cope with the foregoing problems, this paper presents a sensorless vector control algorithm for PMSM
In order to create a mathematical model of PMSM sine wave, make the following assumptions: the effect of magnetic saturation of the rotor core and stator are ignored, the hysteresis loss and eddy current of motor are ignored; Armature reaction magnetic field generated by the permanent magnet excitation field and three-phase windings in the air gap are sinusoidal distribution; Steady-state operation, the phase windings induced electromotive force waveform is a sine wave
Summary
Permanent magnet synchronous machines (PMSM) have been increasingly applied for drive applications due to their simple structure, high power density, high torque to inertia ratio and high efficiency. High-frequency injection method at high speed, the back-electromotive force is too large, the speed and position detection accuracy of the rotor is deteriorated , system stability is poor; Extended Kalman filter method has a large calculate volume, the algorithm requires high carries for the chip, the stator voltage is very small Near zero speed, estimation error of the status will be affected by increases of measurement error and uncertainty of motor model; Artificial intelligence estimation method and technology issues is not mature yet, it need specialized hardware support and more difficult, it is difficult for the practical application; adaptive reference control method exist a problem how to choose the model reference adaptive rational adaptive law, to ensure system stability and robustness of the parameters at the same time improving the convergence rate of this method[4,5,6].
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