Processing of tyre data for rolling noise prediction through a statistical modelling approach

Nowadays, tyre/road noise represents one of the main sources of environmental pollution. For this reason, tyre/road noise models are fundamental to support the design of more silent products. In this paper, a statistical modelling approach is discussed, with particular focus on the identification and processing of noise-related tyre/road parameters. At first, the workflow for the development of a statistical tyre/road noise model is described. This strategy is then applied to the prediction of sound intensity levels of indoor tests performed on drum at different rolling speeds. The measurement of input and output data and their processing are discussed and applied to the define a suitable database. The proposed approach is then tested with a neural network. The results show the potential of the presented methodology in terms of selection of descriptive parameters and features’ extraction procedure.