SUSPENSION SYSTEM-IDENTIFICATION BASED ON IMPULSE-MOMENTUM EQUATIONS

This paper considers a novel method of parametric identification of dy namic models, that is particularly appropriate for vehicle dynamics. T he aim is to provide best possible estimates for parameters such as ma ss, stiffness and damping on the basis of experimental data. The parti cular issue addressed, is the robustness of the identification procedu re to data corruption arising from unmodelled dynamic modes. The new m ethod is based on a linear regression of impulse-momentum equations, o btained as the first integral of the ordinary differential equations o f motion. Using randomised time intervals for the integration process, the new method is found to provide useful benefits. A simplified form of the method is also proposed. Both forms of the new method are appl icable to both linear and non-linear dynamic models.