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A nonlinear eight degree of freedom vehicle model has been used to examine the effects of roll stiffness on handling and performance. In addition, various control strategies have been devised which vary the total roll couple distribution in order to improve cornering capability and stopping distance. Of all cases tested, a controller which varies the total roll stiffness based on roll angle feedback, and continuously updates the roll couple distribution as a function of steering wheel angle, braking input, and the total roll stiffness, yields the greatest improvements in collision avoidance.

In order to achieve predictable handling of a race car, local mounts connecting suspension components to the chassis should be sufficiently rigid to minimize unwanted local deflection which may adversely affect suspension geometry. In this work, the effects of local chassis flexibility of the spring perch on roll stiffness, tire camber change, and steer angle change are determined from a finite element model (FEM) of a Winston Cup race car. Details such as side gussets, supporting brackets, and local curvature of the frame rail spring pocket are included in a shell model of the spring perch. The local shell model of the spring perch is integrated with the global finite element stiffness model of the chassis and suspension consisting of an assembly of beam and shell elements. A parametric study on the effects of thickness changes for seven different areas of the spring perch has been performed.

Predictable handling of a racecar may be achieved by tailoring chassis stiffness so that roll stiffness between sprung and unsprung masses are due almost entirely to the suspension. In this work, the effects of overall chassis flexibility on roll stiffness and wheel camber response, will be determined using a finite element model (FEM) of a Winston Cup racecar chassis and suspension. The FEM of the chassis/suspension is built from an assembly of beam and shell elements using geometry measured from a typical Winston cup race configuration. Care has been taken to model internal constraints between degrees-of-freedom (DOF) at suspension to chassis connections, e.g. t ball and pin joints and internal releases. To validate the model, the change in wheel loads due to an applied jacking force that rolls the chassis agrees closely with measured data.

Track testing of race cars is expensive and racing series typically limit the amount of testing that can be done on circuit tracks. Because of this, we saw the need to develop a computer model that could simulate a car on a track with any specified surface roughness and with aerodynamic loading acting on the vehicle. This model allows an analysis of the effect of aerodynamic loading on the vertical dynamic response of the vehicle. Vehicle parameters specific to an IMSA GTP car including aerodynamic data from wind tunnel testing and nonlinear shock characteristics were used in this study. Simulations were run for various speeds and ride height configurations and it was found that very small changes in the static settings of the front and rear ride heights can lead to large differences in the resulting ride heights at speed. This can be attributed to the variations in the nonlinear aerodynamic loading as the ride height and speed of the vehicle change.

The control of body roll on passenger vehicles can be used as a tool for controlling the “weight shift” that occurs during maneuvering. Distribution of load to the tires will determine the ability of each tire to generate lateral forces required for the maneuver and thus will significantly affect handling. In this investigation, the effects on weight shift and hence, on handling, of total roll stiffness, front to rear roll stiffness distribution, total roll damping, and roll damping distribution were examined. These results were then used to guide the development and analysis of several roll control algorithms. The results of the investigation indicate that roll control can be effective in improving handling and stability. However, simulation of the control algorithms showed that the controllers must be specifically tuned for the vehicle in which they are to be used.