# Sound Quality Estimation of Electric Vehicles Based on GA-BP Artificial Neural Networks
## 2 Measurement and Test
### SQ Objective Evaluation  
The psychoacoustics parameters comprehensively consider the human psychological response mechanism and the acoustic perception characteristics, reflecting the difference in the subjective feelings caused by different sound signals. After obtaining the subjective SQ scores of each sound sample, it is necessary to calculate the psychoacoustics parameters of each sound sample so as to enable a subsequent analysis of the correlation between the subjective and objective evaluation results. By referring to the characteristics and applicability of the existing objective psychoacoustic parameters, the loudness, sharpness, roughness, fluctuation strength, tonality, and articulation index were selected. Meanwhile, the A-weighted SPL was considered. These seven objective parameters can basically represent the psychological characteristics of the sound samples. As a commonly used noise evaluation index, the A-weighted sound pressure level (SPL) refers to the sound pressure level measured by the A-weighted network. Owing to the large number of sound samples, the noise inside an electric car was taken as an example for analysis. Figure 5 shows that the interior noise SPL gradually increased with the vehicle's speed. Usually, the SPL of the right ear is higher than that of the left ear, as the measuring point of the right ear is close to the outside of the vehicle body, which had more noise. Loudness is a psychoacoustic parameter reflecting the human ear's perception of sound intensity based on its masking characteristics. The change in the interior noise loudness with the vehicle's speed is shown in Figure 6, where the loudness increased with the vehicle's speed. \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline
**No.** & **Correlation** & **No.** & **Correlation** & **No.** & **Correlation** & **No.** & **Correlation** \\ \hline
1 & 0.819 & 9 & 0.806 & 17 & 0.827 & 25 & 0.818 \\
2 & 0.796 & 10 & 0.538 & 18 & 0.818 & 26 & 0.671 \\
3 & 0.821 & 11 & 0.843 & 19 & 0.821 & 27 & 0.824 \\
4 & 0.796 & 12 & 0.832 & 20 & 0.834 & 28 & 0.879 \\
5 & 0.812 & 13 & 0.740 & 21 & 0.614 & 29 & 0.788 \\
6 & 0.723 & 14 & 0.826 & 22 & 0.803 & 30 & 0.766 \\
7 & 0.869 & 15 & 0.756 & 23 & 0.798 & 31 & 0.829 \\
8 & 0.816 & 16 & 0.829 & 24 & 0.853 & 32 & 0.740 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Results of the correlation coefficients of the evaluators. \begin{table}
\begin{tabular}{c c} \hline \hline
**Cluster** & **Amount** \\ \hline
1 & 4 \\
2 & 25 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Clustering results. The sharpness is an objective psychoacoustic parameter that reflects the high-frequency components of sound signals. The change in the interior noise sharpness with the vehicle's speed is shown in Figure 7. At low speeds, the high-frequency motor noise dominates, and the sharpness also increases. As the vehicle speed increases, the motor noise is masked, and the high-frequency components of the wind noise and tire noise dominate. The roughness indicates the high-frequency variation of sound signals, while the fluctuation strength (FS) indicates the low-frequency frequency variation of sound signals. Figure 8 shows that the  
Figure 5: Interior noise sound pressure level (SPL) in the EV as a function of the vehicle’s speed. Figure 6: Interior noise loudness in the EV as a function of the vehicle’s speed. Figure 7: Interior noise sharpness in the EV as a function of the vehicle’s speed. interior noise roughness gradually increased with the vehicle's speed, and Figure 9 shows that there was no obvious variation trend for the change in the interior noise FS with speed. The tonality is a psychoacoustic parameter used to measure the proportion of pure sound components in a spectrum of sound signals. Figure 10 shows that there was no obvious variation trend for the change in the interior noise tonality with speed. The articulation index (AI) is a psychoacoustic parameter that reflects the change in the clarity of speech owing to noise in vehicles.