Design of a Portable Tire Test Rig and Vehicle Roll-Over Stability Control

Abstract

Vehicle modeling and simulation have fast become the easiest and cheapest method for vehicle testing. No longer do multiple, intensive, physical tests need be performed to analyze the performance parameters that one wishes to validate. One component of the vehicle simulation that is crucial to the correctness of the result is the tire. Simulations that are run by a computer can be run many times faster than a real test could be performed, so the cost and complexity of the testing is reduced. A computer simulation is also less likely to have human errors introduced with the caveat that the data input into the model and simulation is accurate, or as accurate as one would like their results to be. Simulation can lead to real tests, or back up tests already performed. The repeatability of testing is a non-issue as well.

Tire models are the groundwork for vehicle simulations and accurate results cannot be conceived without an accurate model. The reason is that all of the forces transmitted to and from the vehicle to the ground must occur at the tire contact patches. This presents the problem of obtaining a tire model. Tire companies do not readily give out tire data since the tire industry is still as much "black art" as it is science. For tire data one must begin with a testing apparatus. The test rig must be accurate and must have been validated before results can be used.

This thesis presents the process of the design and construction of a portable tire test rig. It then will discuss tire testing procedures and validation techniques. The resulting data shows good correlation between test data and known tire test data from flat track testing provided by a tire manufacturer. Then, a simple rollover study of a military truck will be compiled in TruckSim. Lastly, a control method for the rollover case will be designed and implemented. The results of the roll control simulation are positive. The study shows an increase in dynamic roll stability due to the implementation of the control algorithm.