Identification of dynamic parameters in vehicle suspension systems.

Abstract

This work presents the identification of dynamic parameters in automotive vehicles. In order to develop the identification problem, a dynamic model is obtained for the front suspension of a race car. Two new dynamic models are developed, the first of which is based on the Singular Value Decomposition (SVD), while the second comprises two consecutive steps: elimination of less contributive parameters and application of a SVD method. Finally, both models are analyzed and validated by means of data cross-referencing for new trajectories other than those used during the identification process. The model obtained using the elimination reproduces the dynamic behavior with very good approximation even with the inclusion of errors, so it is presented as the most viable methodology for obtaining base parameters.