# Laboratory Test of a Vehicle Active Noise-Control System Based on an Adaptive Step Size Algorithm
## 4 Laboratory Experiment
### The ANC Experiments  
In order to further verify the performance of the AASFxLMS algorithm proposed in this paper, an ANC experiment was conducted in an anechoic chamber via an ANC experiment. The proposed ANC system is implemented using MATLAB and Simulink, together with dSPACE. On the basis of Simulink modeling, a TLC code is used to compile the Simulink model into the C programming language and generate the model. The model is read by DspaceControldesk, so that the ANC noise reduction process can be completed. The experimental principle is shown in Figure 12. The experimental equipment used in this experiment was mainly a dspace1401 board, with parameters of 8 \(\Omega\), a 30 W speaker, an ice711 318-4 artificial ear, a B&K1704 pre-amplifier power supply, and a computer. Through the primary loudspeaker used to play different road noises, the ice711 318-4 artificial ear measured the before and after noise reduction frequency response and the corresponding time domain curve. The hardware-in-the-loop experimental platform, built according to ANC experimental principles, is shown in Figure 13.  
In this experiment, the signals collected on one side of the artificial ear were used as error signals, and the signals collected by the artificial ear before and after noise reduction were compared. The traditional FxLMS algorithm was compared with the proposed AASFxLMS algorithm. The duration of the primary noise played by the primary speaker was 15 s. Due to the short lag of dSPACE measurement data, the data from the first few seconds of dSPACE operation cannot be observed. The error signal collected at this time was timed from the 6 th second until the noise reduction process was completed, and a total  
Figure 12: Schematic diagram of the ANC experiment. Figure 13: Hardware-in-the-loop ANC experimental platform. of 10 s of noise reduction time was recorded. The frequency resolution of the frequency response graph was 0.1. In addition, the \(L_{\text{att}}\) of noise attenuation in reference [24] is adopted as the overall noise reduction amount, which is defined as:  
\[L_{\text{att}}=-10\log_{10}[\text{Tr}(S_{\alpha e})/\text{Tr}(S_{dd})] \tag{23}\]  
where Tr (\(\cdot\)) is the trace of the matrix. \(S_{dd}\) and \(S_{\alpha e}\) are the power spectral density matrix of the signal before and after noise reduction, respectively. Working condition 1: The car runs at a constant speed of 30 km/h and passes over the speed bump. The experimental results of the vehicle's internal noise, used as a reference signal under the first working condition, are shown in Figure 14. As can be seen from the time-domain response diagram, the proposed algorithm has a certain suppression effect on noise, and it also has a good suppression effect when encountering a sudden increase in signal, while the FxLMS algorithm has almost no suppression effect on noise. According to the frequency response diagram, the proposed algorithm has an obvious noise reduction effect when the frequency range is 20-100 Hz, the noise reduction amplitude is about 3-10 dB, and the noise reduction effect is 10 dB, near 45 Hz. The overall noise reduction is 3.1 dB, in the frequency range of 20-400 Hz. The FxLMS algorithm has a noise reduction effect of 1-2 dB in the 20-100 Hz frequency band but has a noise enhancement effect when the frequency is above 100 Hz. The overall noise reduction is 0.3 dB in the frequency range of 20-400 Hz. Working condition 2: The car runs at a constant speed of 40 km/h and passes over the speed bump. The experimental results of the vehicle's internal noise as a reference signal in the second working condition are shown in Figure 15. The time-domain response diagram shows that the proposed algorithm significantly reduces the amplitude of sound pressure after noise reduction, but still shows obvious suppression when the noise signal suddenly increases, and the amplitude of the FxLMS algorithm does not change significantly before and after noise reduction.