This work addresses the problem of tyre tread pattern design for optimum wet grip performance. A mathematical model of tyre behaviour on wet roads has been developed. This utilizes the finite element method in the representation of tread pattern geometry. The performance of a particular tread pattern is found in terms of the fluid pressures and film thicknesses existing within the contact patch, under wet conditions. Many modern tread patterns are based on 'blocks', and a computer model has been developed specifically to assist the tyre designer in the design of these blocks for improved wet grip. Numerical results are presented both for complete contact patches and for individual tread blocks. To allow the use of the computer models by the tyre designer, with no specialist knowledge of the finite element method, special purpose mesh generation and plotting programs have been developed. Experiments have been undertaken whereby the fluid pressures and film thicknesses existing in the tyre contact patch have been measured under high speed conditions in the wet. These measure- ments were made on an indoor testing machine, and the techniques developed can be used in the routine evaluation of tyre wet grip performance. Some results of experiments performed on plain and simple patterned tyres are presented. The main purpose of this work was the development of the mathematical models which can be used for future research into, and design of, tyres for improved wet grip. However, some conclusions are made as to possible features which could be utilized in future tyre designs.

Tire-pavement interaction noise is one of the dominant sources of vehicle noise, and one of the most significant sources of urban noise pollution. One critical generation mechanism of tire-pavement interaction noise is tire tread excitation. The tire tread contributes to the tire-pavement interaction noise mainly through two mechanisms: (1) tread block impact, and (2) the compression and expansion of the air in the tread groove at the contact patch. The tread pattern is the critical part of the tire design since it can be easily modified. Hence, the main focus of this study is to quantify the tread pattern contribution in total tire-pavement interaction noise. To achieve this goal, the noise produced by the tread pattern is separated from the total tire-pavement interaction noise. Since the tread pattern excitation is periodic with tire rotation, the noise produced by the tread is assumed to be related to the tire rotation. Hence, the order domain synchronous averaging method is used in this study to separate and quantify the tread pattern contribution to the total tire-pavement interaction noise. The experiment has been carried out using an On-Board-Sound-Intensity (OBSI) system. Five tires were tested including the Standard Reference Test Tire (SRTT). Compared to the conventional OBSI system, an optical sensor was added to the system to monitor the tire rotation. The once per revolution signal provided by the optical sensor is used to identify the noise signals associate to each revolution. In addition to the averaging method using optical signals, other data processing techniques have been investigated for separating the tread-pattern noise without utilizing the once per revolution signal. These techniques are autocorrelation analysis, a frequency domain filter, principal component analysis, and independent component analysis. In the tread-pattern noise generation, the tread profile is the most important input parameter. To characterize the tread profile, the tread pattern spectral content and air volume velocity spectral content for all the five tires are computed. Then, the tread pattern spectrum and the air volume velocity spectrum are both correlated with the separated tread-pattern noise by visual inspection of the spectra shape. / Master of Science

Tire-pavement interaction is a dominant noise source for passenger cars and trucks above 25 mph (40 km/h) and 43 mph (70 km/h), respectively. For the same pavement, tires with different tread pattern and construction generate noise of different levels and frequencies. In the present study, forty-two different tires were tested over a range of speeds (45-65 mph, i.e., 72-105 km/h) on a non-porous asphalt pavement (a section of U.S. Route 460, both eastbound and westbound). An On-Board Sound Intensity (OBSI) system was instrumented on the test vehicle to collect the tire noise data at both the leading and trailing edge of the tire contact patch. An optical sensor recording the once-per-revolution signal of the wheel was also installed to monitor the vehicle speed and, more importantly, to provide the data needed to perform the order tracking analysis in order to break down the tire noise into two components. These two components are: the tread pattern and the non-tread pattern noise. Based on the experimental noise data collected, two artificial neural networks (ANN) were developed to predict the tread pattern (ANN1) and the non-tread pattern noise (ANN2) components, separately. The inputs of ANN1 are the coherent tread profile spectrum and the air volume velocity spectrum calculated from the digitized 3D tread pattern. The inputs of ANN2 are the tire size and tread rubber hardness. The vehicle speed is also included as input for the two ANN's. The optimized ANN's are able to predict the tire-pavement interaction noise well for different tires on the pavement tested. Another outcome of this work is the complete literature review on Tire-Pavement Interaction Noise (TPIN), as an appendix of this dissertation and covering ~1000 references, which might be the most comprehensive compilation of this topic. / PHD