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A truck-trailer combination is modeled using ADAMS/Car from MSC Software for handling and ride comfort performance simulations. The handling events include a double lane change and lateral roll stability. The ride comfort performance events include several sized half-rounds and various RMS courses. The variables for handling performance evaluation include lateral acceleration, roll angles and tire patch normal loads. The variables for ride performance evaluation are absorbed power and peak acceleration. This study considers the trailer spring stiffness, anti-roll bar and jounce bumper gap as the design variables. Through DOE simulations, we derived the response surface models of various performance variables so that we could consider the performance sensitivities to the design variables.

In this paper, a comprehensive evaluation index for impact harshness (IH) is proposed. A mid-sized uni-body SUV is selected for this study, with the acceleration responses at the various vehicle body locations as objective functions. A sensitivity study is conducted using an ADAMS full vehicle model with flexible body structure representation over an IH event to analyze the influence of various suspension tuning parameters, including suspension springs, shock damping, steer gear ratio, unsprung mass, track-width, and bushing stiffness.

The statistical trends of the spindle loads extracted from road load test data of vehicles with different variants are presented in this paper. The road load data of a vehicle moving on the same track with single speed are considered with different variants of the vehicle. The variants considered are repeat runs, spindle loads in vehicles with different ballast conditions, difference in type of leaf spring shackles and changed number of frame to body mounts. The parameters considered for the statistical trend comparison are the spindle forces, spindle moments and spindle accelerations monitored in different directions. The data analysis was performed using the software functions in N-soft and MATLAB. The analyzed results were grouped and bar charts are prepared to bring out the statistical variations of different parameters.