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This paper describes techniques that predict and analyze dynamic response of vehicles traversing random rough surfaces. Road irregularities are statistically classified by frequency and amplitude distribution. This classification determines the nature of random inputs to mathematical vehicle models and allows computer prediction of dynamic response of a simulated vehicle. Once inputs and models are defined, parametric analysis with output criteria specified statistically can be performed. This allows prediction of vehicle riding quality and evaluation of design concepts. Statistical analysis of accelerometer measurements on actual vehicles permits verification of the design process and meaningful comparison between vehicles.

Present techniques for classification and analysis of surface roughness are based on a trace of surface profile, or a measure of arithmetic mean, or rms value of the profile height, but this information is not adequate, and a new technique has been developed to classify surface roughness based on frequency content of the variance of the surface profile. A digital computer frequency filter has been devised to allow differentiation between roughness height and waviness or general surface contour. Three representative surfaces have been measured and classified according to this analysis and data are presented in support for roughness classification techniques.