Vehicle Interior Sound Quality Evaluation Index Selection Scheme Based on Grey Relational Analysis

Abstract

In the process of vehicle interior sound quality research, the subjective assessment usually requires a lot of manpower, time and material resources. It is necessary to choose appropriate objective indexes to predict the subjective results. In this paper, a sound quality evaluation index analysis and selection scheme based on grey relational analysis (GRA) is designed. In order to make a reasonable prediction of the subjective indexes with the limited data, GRA of the objective indexes and subjective indexes is conducted. Because three subjective indexes are considered in our study, an indicator that can represent the three chosen subjective indexes is established for the subsequent analysis. Furthermore, the comprehensive ranking and the hierarchical cluster analysis (HCA) of the objective indexes are involved to make the selection of objective indexes easy and meaningful. Finally, the objective indexes are divided into five groups by HCA. According to the clustering results, four objective indexes including “fluctuation”, “sharpness”, “articulation index” and “roughness” are suitable for predicting and representing the subjective indexes to some degree. The scheme proposed in this paper lays the foundation for further optimization and control of vehicle interior sound quality. The method can also be applied to solve other similar multi-factor analysis and selection problems.