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The intention of this work is to illustrate a method used to overcome limitations of tire models developed during an evaluation study of an Empirical Dynamic™ (ED) damper model. A quarter vehicle test system was built to support the evaluation, and a model of the test system was also developed in ADAMS™. In the model, the damper was represented by a polynomial spline function and by an ED model separately. Vehicle level comparisons between the physical measurements and the model predictions were conducted. The actuator displacement signal from the physical test was used to drive the virtual test system. Spindle acceleration, spindle force, and other signals were collected for comparison. The tire model was identified as a significant source of error and as a result, the direct vehicle level correlation study did not illustrate any advantage of the ED damper model over a spline damper model.

This paper describes an approach to simulate spindle coupled full vehicle durability tests for the purpose of completing virtual durability evaluations on components and full vehicles before a prototype is available. The reproduction of measured spindle loads was achieved on a virtual model of a passenger car coupled to a 4 Degree of Freedom (DOF) and 6 DOF spindle coupled test system. The tools and process improvements developed here will aid both test and analysis engineers in working closer together in solving their durability problems. By using Remote Parameter Control® (RPC®) technology in the virtual world, analysts have a new method to understand the virtual model by reproducing field-measured or generic road predicted signals for a variety of road surfaces. With newly created test rig models and a user friendly RPC™ iteration process, virtual testing that accurately replicates laboratory tests are now a reality.

Recent studies have shown that complex vehicle components such as shock absorbers, rubber bushings, and engine mounts can be accurately modeled by combining laboratory measurements with neural network technology. These nonlinear dynamic blackbox models (also known as Empirical Dynamics1 models) make it possible to predict nonlinear and hysteretic component behavior over wide ranges of amplitude and frequency. The models can handle realistic input waveforms as well as multiple inputs and multiple outputs. These techniques have now been applied to rolling pneumatic tires, to enable high accuracy predictions of tire and vehicle handling behavior. Models that predict high amplitude force components (three forces and three moments) using up to four randomly-varying inputs (radial deflection, slip angle, and camber angle, and slip ratio) have been successfully generated, using data obtained from MTS Flat-Trac III tire test equipment.

Hyundai Motor Company has combined physical and virtual testing tools to validate a full vehicle virtual prototype. Today a large number of physical tests are still required because the cycle of “design-build-test-change” relies on complex models of components and systems that typically are not easily validated. In order to shorten the development cycles, engineers perform multi-body simulations to dynamically excite components and systems and thereby estimate their durability under dynamic loads. The approach described herein demonstrates the feasibility of correlating the output from the corresponding physical and virtual prototype. Both synthetic and road load events are employed to excite physical and virtual vehicles, reveal difference in response, and ultimately improve the predictive capability of the model.

The automotive vehicle design process has relied for many years on both analytical studies and physical testing. Testing remains to be required due to the inherent complexities of structures and systems and the simplifications made in analytical studies. Simulation test methods, i.e. tests that load components with forces derived from actual operating conditions, have become the accepted standard. Advanced simulation tools like iterative deconvolution methods have been developed to address this need. Analytical techniques, such as multi body simulation have advanced to the degree that it is practical to investigate the dynamic behavior of components and even full vehicles under the influence of operational loads. However, the approach of testing and analysis are quite unique and no seamless bridge between the two exists. This paper demonstrates an integrated approach to combine testing and analysis together in the form of virtual testing.