## 5 Experimental Results  
The photo of the experimental system for acoustic noise measurements is depicted in Figure 17. It consists mainly of an IM, a DSP board and a two-level VSI controlled by SVPWM, RZV_SVPWM, RPP_SVPWM and RSF_SVPWM. We have implemented all the proposed strategies using the TMS320F28335 DSP board from Texas Instruments. The motor runs at a fundamental frequency of F = 50 Hz and a switching frequency of Fc = 5 kHz. A sound level meter is used to measure the instantaneous sound pressure. After each measurement test, the saved data file is transferred to the PC. The spectral noise analysis is performed using MATLAB's FFT function. The machine used in this study is classified as a small machine. Therefore, all measurement points must be located at a 250 mm distance or more from the main machine surface. Measurements should be carried out when the machine reaches a steady state of the operating mode [8; 22; 23; 24]. The sound pressure level in decibels (dB) can be described using the sound pressure, which is determined by Equation (18):  
\[\mathrm{L_{P}(t)}=20\log_{10}\biggl{(}\frac{p(t)}{P_{0}}\biggr{)} \tag{18}\]  
where \(p_{0}\) is the reference sound pressure, and p(t) is the instantaneous sound. The human ear sensitivity can be modeled using appropriate weighting functions or curves. International standards recommend weighting curves. The A-weighting curve  
Figure 16: Electromagnetic torque waveforms and speed for different studied techniques. Figure 17: Photo of experimental platform. is widely used in electrical machine acoustics and is also utilized in this work. Figure 18 illustrates the dB(A) weighting curve according to IEC 61672-1/2002 [22]. The measured stator current waveforms and the harmonic spectrum produced by the IM supply by a two-level VSI and are controlled by the SVPWM, RZV_SVPWM, RPP_SVPWM and RSF_SVPWM techniques, where im = 1 and Fc = 5 KH are represented in Figure 19. As it can be seen from the results of the measured harmonic spectrum, with the SVPWM, RZV_SVPWM and RPP_SVPWM techniques, the dominant harmonics components are concentrated around the switching frequency and its multiples. Furthermore, the highest magnitudes of current harmonics are located around the first sideband of the switching frequency. However, it can be observed that the magnitude of current harmonics is reduced considerably with RSF_SVPWM compared to the other strategies. Furthermore, the motor current spectrum is well dispersed, and the harmonics around integer multiples of the switching frequency disappear. As a consequence, it is evident that the proposed RSF_SVPWM scheme has better performance in terms of acoustic noise, as it will be seen in the next section. The weighted frequency spectra of acoustic noise corresponding to the SVPWM, RZV_SVPWM, RPP_SVPWM and RSF_SVPWM techniques, where im = 0.8 and Fc = 5 kHz and where im = 1 and Fc = 5 kHz, are performed and demonstrated, respectively, in Figures 20 and 21. Referring to the experimental results, we can observe that the acoustic noise emitted from the IM is generated with SVPWM, RZV_SVPWM and RPP_SVPWM. The high acoustic noise components are significant around integer multiples of the switching frequency, as shown in Figure 20a-c. The dominant noise of these techniques is mainly due to the interaction of the switching frequency and the higher time harmonics. When im = 0.8, the noise amplitude is \(-\)38.33 dBA, \(-\)26.8 dBA and \(-\)50.32 dBA for SVPWM, \(-\)25 dBA, \(-\)40 dBA and \(-\)60 dBA for RZV_SVPWM and \(-\)37 dBA, \(-\)38.51 dBA and \(-\)58.2 dBA for RPP_SVPWM, respectively, at 5, 10 and 15 KHz. However, for the RSF_SVPWM technique, the dominant noise components emitted from the IM around the integer multiples of the switching frequency disappear and the spectrum is spread, as presented in Figure 20d. It is clearly noticed that RSF_SVPWM produces a less noisy component than the other techniques. The noise amplitude is \(-\)75.2 dBA, \(-\)80.1 dBA and \(-\)75.2 dBA, respectively, at 5 Khz, 10 kHz and 15 kHz.