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Currently, the final stages of chassis development are conducted on prototype vehicles, requiring vehicle manufacturers to dedicate copious resources to the development of each new vehicle platform. The objective of this work is to provide development engineers a system identification tool enabling them to use modeling and simulation to better estimate the required vehicle system parameters. This work develops a parameter identification method for existing vehicle models in which measured terrain data is used as the model excitation. The model was validated using a variety of excitation events and shown to provide accurate estimations of a vehicle’s roll, pitch, and vertical displacement.

Load data representing severe customer usage is required during the chassis development process. The use of road profiles and vehicle models to predict chassis loads is currently being researched; this research hinges on the ability to accurately measure road profiles. This work focuses on detecting possible signal defects such as leaves on the ground, reflecting surfaces, or narrow roadway gaps. The objective of this work is to develop a simulation procedure that checks the measured road profile for plausibility. The position of the vehicle body is recorded as part of the typical road profiling process. Ideally, a mathematical model can predict the body position from a road profile. The first step in verifying the plausibility of road profiles is to predict the body position. Next, the measured body position is compared to the predicted body position for the road profile in question. New criteria for plausibility checking are a major contribution of this work.

The accuracy of computer-based ground vehicle durability and ride quality simulations depends on accurate representation of road surface topology as vehicle excitation data since most of the excitation exerted on a vehicle as it traverses terrain is provided by the terrain topology. It is currently not efficient to obtain accurate terrain profile data of sufficient length to simulate the vehicle being driven over long distances. Hence, durability and ride quality evaluations of a vehicle depend mostly on data collected from physical tests. Such tests are both time consuming and expensive, and can only be performed near the end of a vehicle's design cycle. This paper covers the development of a methodology to synthesize terrain profile data based on the statistical analysis of physically measured terrain profile data.

The vertical force generated from terrain-tire interaction has long been of interest for vehicle dynamic simulations and chassis development. To improve simulation efficiency while still providing reliable load prediction, a terrain pre-filtering technique using a constraint mode tire model is developed. The wheel is assumed to convey one quarter of the vehicle load constantly. At each location along the tire's path, the wheel center height is adjusted until the spindle load reaches the pre-designated load. The resultant vertical trajectory of the wheel center can be used as an equivalent terrain profile input to a simplified tire model. During iterative simulations, the filtered terrain profile, coupled with a simple point follower tire model is used to predict the spindle force. The same vehicle dynamic simulation system coupled with constraint mode tire model is built to generate reference forces.