Effects of Tire Attributes on Aerodynamic Performance

As fuel efficiency becomes more critical in auto industry, many researchers have started to investigate the aerodynamics of tires. Computational modelling currently is the major tool when evaluating tire aerodynamics, since the experiments are expensive and time consuming. As indicated by previous studies, many attributes of tires have been shown to have an impact on the tire aerodynamic drag. Different tire designs are compared together. However, how these attributes affect tire aerodynamics has not been systematically investigated to date. It is not clear which tire attributes has the most significant impact. Therefore, a sensitivity study on the effects of tire attributes on the tire aerodynamic performance is proposed in this study.

First, a baseline CFD model of a tire in a wind tunnel is created and validated against experimental data. A hybrid boundary condition method is used to simulate a rotating tire. Base on the validated baseline model, various tire attributes are considered and compared in the sensitivity study. The sensitivity study includes two steps. As a first step, different tire features are simulated. These features include the tire width, the longitudinal grooves, lateral grooves, the rim design, shoulder radius, and rim protector. Therefore, there are six cases in total for the first step. For each case, one of these features are changed based the baseline model. Then the effects of these features on the tire aerodynamic drag are compared. As a result, the most influencing feature can now be identified. In the second step of the sensitivity study, the geometry of the most influencing feature is parameterized. A detailed parametric study will be conducted regarding this feature. Response surface figures will be plotted. Design of experiments technique will be used to discretize the design space. A hybrid method, which combines the full factorial experimental plan and Kennard-Stone algorithm is adopted. The objective functions in this study are aerodynamic drag values. A statistical model, which represent the functional relationship between tire design parameters and objective functions can be created after the parametric study. Two statistical modelling approaches will be used in this study, multiple regression analysis (MRA) and artificial neural network (ANN). The sensitivity study will give a quantitative result for the impact of each design parameter on the objective functions. As a final result, a summary of the effects of tire attributes on aerodynamic drag will be presented. It will provide a guideline for future tire design in terms of aerodynamic drag.