ABSTRACT
The goal of every calibration is to identify an optimal setup. As modern chassis control systems are influenced by an increasing number of different parameter, the calibration task is getting also more complex. So far, the identification of an optimal parameter setup was done with an iterative attempt. This attempt seems to be overtaken by the fast growing complexity of new systems. In this approach a method is presented to simplify the calibration by techniques of Design of Experiments. Specifically the meta-model for simulation results is discussed in detail. So far, Design of Experiments is used mainly on the basis of measured results in automotive context. This paper presents the differences between interpolating modeling approaches against conventional meta-models and emphasizes on its advantages and borderlines.
