Abstract

To attain good tire performance in pass‐by noise under acceleration (as requested in Europe by 92/97/EEC), tires have to be tested with a noise‐isolated vehicle. The tire/road noise under acceleration can be evaluated without disturbance from engine noise. In a pass‐by noise program (with simultaneous measurements of sound pressure level, torque, and slip) tires with different tread compounds and patterns were chosen to study the influence of both on pass‐by noise. Due to the noise isolation of the test vehicle, the rolling noise and the tire/road pass‐by noise under acceleration can be evaluated. Test results were compared to laboratory noise tests where a driven tire runs on a drum.

Abstract

This paper focuses on four tire computational models based on two‐dimensional shear deformation theories, namely, the first‐order Timoshenko‐type theory, the higher‐order Timoshenko‐type theory, the first‐order discrete‐layer theory, and the higher‐order discrete‐layer theory. The joint influence of anisotropy, geometrical nonlinearity, and laminated material response on the tire stress‐strain fields is examined. The comparative analysis of stresses and strains of the cord‐rubber tire on the basis of these four shell computational models is given. Results show that neglecting the effect of anisotropy leads to an incorrect description of the stress‐strain fields even in bias‐ply tires.

Abstract

The 3D flow around a 195/65R15 automobile tire is calculated. To describe the free surface behavior with the usual conservation equations for mass and momentum, an additional equation for the water mass fraction is solved. For modeling the effects of turbulence, the well‐known k,ε‐model is used. The resulting fluid mechanics equation system is solved by a finite volume method. A finite element calculation considering inflation pressure and tire deflection gives the surface for the flow calculation. The goal is to determine the lift force of the tire at a certain velocity to predict the tendency of the tire to hydroplane. For a slick tire, the calculated pressure distribution in the water is presented. The lift and drag forces are evaluated from the pressure acting directly on the tire surface. The calculation is performed at three different velocities, 30, 60, and 90 km/h. A comparison with experimental data shows good agreement regarding the pressure distribution on the road in front of the tire.

Abstract

The curing process is the final step in tire manufacturing where curing reactions of rubber compounds take place under elevated pressures and temperatures in a press. A simulator for the tire curing processes was developed, which implements numerical algorithms based on a finite element method to solve the rigorous model equations governing transient heat transfer and curing reactions. Extensive simulation has been carried out ranging from simple heat conduction problems to actual tire curing processes. The results have been verified through comparison with analytical solutions or actual thermocouple measurements. The simulator successfully describes the trends in temperature and the state of cure during the tire curing process. It also serves as the core module of an optimization algorithm, which is being developed for the curing processes.

Abstract

Tire manufacturers exploit the use of cure kinetics models in the FEA for setting optimum cure cycles. The following cure process assures production of superior tire compound properties in a cost competitive manner.

It is well known that overcure of many tire compounds results in reversion. This effect is directly observed as a decrease in modulus relative to the optimum value. Reversion is directly observed on rheometric isothermal torque‐time profiles which pass through a maximum torque value. Reversion usually implies a deleterious effect on vulcanizate properties.

We are not aware of any cure models, given in the literature, which adequately account for reversion. Such models cannot be used to accurately optimize cure cycles in those cases where the extent of reversion is significant.

This paper presents a cure kinetics model that accounts for reversion. Also, the model does not need to use an “induction time.” Rather, the model predicts a continuous torque‐time trace, initially rising slowly but eventually rising sharply. The predicted and observed torque‐time traces, as shown in this paper, exhibit excellent agreement over the entire rheometric time scale. Furthermore, the constants of the model can be interpreted as indicators of the basic mechanism of the curing process, i.e., rate constants for creation and loss rates of different types of cross‐links, therefore enabling a prediction of the extent of reversion during a cure cycle.