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Today's computers offer the potential for increasingly complex models for use in simulation of ground vehicle dynamics The tire models that support these simulations are themselves quite complex, requiring a lengthy set of input parameters to support simulation of tires across a wide range of operating conditions This paper presents a platform-independent tire model preprocessor running under an X-Motif graphical interface it provides convenient input and graphical output for a range of user-specified tire operating conditions, and it allows graphical comparison with experimental data Currently supported are models from Calspan, Gim and Nikravesh, Pacejka, and Systems Technology, Inc (STI) The paper presents examples of coefficient checking, cross-model comparisons, and comments on the consequences of operating these models outside the range of their input data

Input parameter verification is the most challenging aspect of the validation process of a computer simulation for a particular vehicle. Unreasonable parameters can arise from three sources, erroneous measurements (or bad guesses), misinterpretation of the parameter to be measured, and mistakes in data entry.

Lateral load transfer occurs when vehicles engage in directional maneuvers. The distribution of lateral load transfer between front and rear axles depends on both roll stiffness and suspension geometry. This paper uses computer simulation to examine the influence of lateral load transfer distribution on directional response. The simulation indicates that in mid-range maneuvers, say from .4g to .6g on a dry surface characterized by a friction limit of .85, the distribution of lateral load transfer has significant implications for directional response. This paper illustrates these differences by calculations in the time domain and by tracking peak response variables in ramped steer maneuvers as a function of lateral load transfer distribution. Differences are also apparent in the limit range where the distribution of lateral load transfer is shown to be very influential, differentiating in some cases between spin out and plow out response.