The purpose of the present research relates to the sensitivity analysis of road vehicle comfort and handling performances with respect to suspension technological parameters. The envisaged suspension being of semi-active nature, this implies first to consider an hybrid modeling approach consisting of a 3D multibody model of the full car - an Audi A6 in our case - coupled with the electro-hydraulic model of the suspension dampers. Concerning parameter sensitivitie, the goal is to capture them for themselves - and not necessarily for optimization purpose - because their knowledge is of a great interest for the damper manufacturer. An important issue of the research is to consider objective functions which are based on complete time integrations along a given trajectory, the goal being - for instance - to quantify the sensitivity of the carbody rms acceleration (comfort) or of the vehicle overturning character (handling) with respect to suspension parameters. On one hand, the accuracy of the various partial derivatives computation can be greatly enhanced thanks to the symbolic capabilities of our ROBOTRAN multibody program. On the other hand, the computational efficiency of the process also takes advantage of the recursive formulation of the multibody equations of motion which must be time integrated with respect to both the generalized coordinates and their partial derivatives in case of the so-called direct method underlying sensitivity analysis.
In high-performance optical systems, small disturbances can be sufficient to put the projected image out of focus. Little stochastic excitations, for example, are a huge problem in those extremely precise opto-mechanical systems. To avoid this problem or at least to reduce it, several possibilities are thinkable. One of these possibilities is the modification of the dynamical behavior. In this method the redistribution of masses and stiffnesses is utilized to decrease the aberrations caused by dynamical excitations. Here, a multidisciplinary optimization process is required for which the basics of coupling dynamical and optical simulation methods will be introduced. The optimization is based on a method for efficiently coupling the two types of simulations. In a concluding example, the rigid body dynamics of a lithography objective is optimized with respect to its dynamical-optical behavior.