Predictive Control of IM Drive Acoustic Noise

Abstract

Acoustic behavior of electric drives is an important factor for their application in areas where humans expect certain comfort, such as in electric vehicles. The main problem addressed in this article is high tonality of noise emitted by conventional pulsewidth modulation (PWM) controlled drives. We propose to use an explicit model of the transfer function from the electric variables to the sound pressure with experimentally identified parameters. This model is then used to include acoustic quality into the cost function of the finite control set model predictive control (FCS-MPC). Specifically, we propose to penalize the sound pressure resonant frequencies in the spectrum of the direct flux component of the stator current vector. We study the impact of this penalization on acoustic properties of the drive measured by the sound pressure level and spectral flatness measure on three experimental induction machine (IM) drives of different power and acoustic environment. In comparison with the conventional PWM, random PWM, and FCS-MPC techniques, the proposed approach improves the tonality of the noise in terms of spectral flatness and in high-speed regimes it also improves total sound pressure level by several decibel.