Acoustic noise of induction motor with low-frequency model predictive control

Abstract

This paper studies the acoustic noise of induction motor with low switching frequency model predictive control and compares its noise performance with the traditional pulse width modulation with proportional-integral controllers. First, the relationship among the air-gap magnetic field, the electromagnetic force, and the acoustic noise is modeled to describe the influence of control algorithm on the noise characteristics of motors. As the counterpart with the traditional pulse width modulation control, a finite control set model predictive control strategy with low switching frequency is proposed. The steady-state performance and switching frequency constraint ability of the proposed model predictive control strategy are verified on the experimental platform. Second, the noise spectrums of these two control strategies are sampled and compared in different operating conditions, and the influence of the weighting factor on the noise spectrum is also discussed. It is proved by the experimental results that model predictive control has better noise performance than the traditional sinusoidal pulse width modulation under the same switching frequency and the total harmonic distortion of stator current.