Laboratory Tire Wear Simulation Process Using ADAMS Vehicle Model

Paper #:
  • 961001

Published:
  • 1996-02-01
Citation:
Parekh, D., Whittle, B., Stalnaker, D., and Uhlir, E., "Laboratory Tire Wear Simulation Process Using ADAMS Vehicle Model," SAE Technical Paper 961001, 1996, https://doi.org/10.4271/961001.
Pages:
12
Abstract:
Computer simulation technology coupled with indoor laboratory facilities is being used in the automotive industry to provide up-front assessment of vehicle performance. This paper presents a technique to evaluate passenger vehicle tire wear performance as related to suspension and tire design early in the design process. Motivation for developing this tool is to optimize suspension and tire design to tire wear early in the design process. This approach has resulted in reductions in vehicle development time, dependency on outdoor testing and the need for expensive prototype vehicles.A full vehicle ADAMS model of a production vehicle is used to animate vehicle suspension kinematic motions, and dynamic tire forces of vehicle maneuvers for a preselected outdoor tire wear route. Time histories of five vehicle parameters are generated: radial force, slip angle or lateral force, camber, velocity and driving and braking torques. These parameters are used as an input to indoor laboratory test facilities. The indoor machine subjects the test tire to these inputs on an abrasive surface. Both flat surface and 3 meter road wheels are used.Both front and rear axles are examined in this study. Evaluation of the data is conducted in two areas. First, overall tire wear results from the indoor tests using ADAMS inputs are compared with outdoor vehicle results. Secondly. ADAMS predicted toads are compared with measured vehicle loads. Differences between ADAMS and vehicle tire load time histories are illustrated as well as tire wear differences. Results show 1) excellent duplication of outdoor tire wear results, 2) test acceleration by a factor of four, 3) good correlation between ADAMS and measured loads, and 4) reduced variability on the indoor tests.
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