Sound quality evaluation and ridge regression prediction of in-cabin noise in heavy-duty commercial vehicles

To examine in-cabin noise characteristics under different load conditions and vehicle speeds, psychophysical objective parameters are measured and subjective ratings are obtained through paired-comparison jury tests. The effects of factors such as vehicle model, speed and load on the in-cabin sound quality of heavy-duty commercial vehicles are systematically analyzed. Furthermore, an analysis of the correlations among acoustic quality parameters under different operating conditions was conducted. Subsequently, a multiple linear regression model is constructed using ridge regression, in which psychophysical objective parameters serve as independent variables and subjective ratings as the dependent variable. The results indicate that ridge regression significantly reduces multicollinearity while maintaining a satisfactory level of predictive accuracy, thus providing valuable guidance for sound quality optimization.