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Application of System Identification for Efficient Suspension Tuning in High-Performance Vehicles: Quarter-Car Study
Abstract:
One popular complement to track testing that successful race teams use to better understand their vehicle's behavior is dynamic shaker rig 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 generate a model of the experiment and then applying the model to identify potential gains for further rig study.
This study develops the method at the quarter-car scale, using data from a quarter-car rig with a Penske 7300 shock absorber. The method is first validated using data generated from a known quarter-car model to assure the method can reproduce the original model behavior. Next, the method is applied to experimental data collected from an existing quarter-car rig. The results show that this method can be used to accurately predict sensor measurements during quarter-car rig tests for various actuator inputs and shock selections. Future work will apply the lessons learned from this study to develop a full car model using 8-post rig data.