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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.