One popular complement to track testing that successful race teams use to better understand their vehicle’s behavior is dynamic shaker rig testing, such as 7-post and 8-post testing. Compared to track testing, rig testing is more repeatable, costs less, and can be conducted around the clock. While rig testing certainly is an attractive option, an extensive number of tests may be required to find the best setup. To make better use of rig test time, more efficient testing methods are needed. One method to expedite rig testing is to use rig test data to perform system identification and generate a model of the experiment, which may then be applied to identify potential gains for further rig study.
This study develops a system identification method for use in rig testing, using data generated from a known physical model. The results show that this method can be used to accurately predict sensor response during an 8-post test for different shock selections. Future work will apply the model developed in this study to a car tested on an 8-post rig and to perform shock selection.
