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Competitive pressures, globalization of markets, and integration of new materials and technologies into heavy vehicle suspension systems have increased demand for durability validation of new designs. Traditional Proving Ground and on-road testing for suspension development have the limitations of extremely long test times, poor repeatability and the corresponding difficultly in getting good engineering level data on failures. This test approach requires a complete vehicle driven continuously over severe Proving Ground events for extended periods. Such tests are not only time consuming but also costly in terms of equipment, maintenance, personnel, and fuel. Ideally multiple samples must be tested to accumulate equivalent millions of kilometers of operation in highly damaging environments.

The essential concepts for developing a moving deformable barrier that may serve as a vehicle surrogate in assessing vehicle compatibility are described in this paper. Although moving deformable barriers have been used for assessing other safety criteria, their purpose in those cases is to reproduce a limited set of responses in the struck vehicle. An MDB for vehicle compatibility however, needs to be able to reproduce the responses of both the vehicles. The present study describes the concept of developing such barriers by generating ‘response corridors’ for the significant variables by nonlinear finite element simulations and then selecting design parameters such that the MDB response is within this corridor. It is observed that the response of the equivalent MDB representing a light truck vehicle is reproducible when response corridors are utilized.

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.

This paper presents a case study on reducing road noise of a passenger vehicle. SEA, insertion loss and sound intensity measurements were the tools used in the study. A SEA model was constructed to predict the primary paths (panels or area) contributing to the overall interior sound field. Insertion loss measurements were used to verify the primary contributing paths identified using SEA. To provide further details of the primary paths, intensity maps of identified panels were measured allowing detailed reconstruction of the contributory panels. The SEA model, insertion loss, and intensity maps aided in providing possible design fixes that will effectively reduce road noise. Finally, comparisons of predicted results versus actual results at both a subsystem and a full vehicle level are included in this paper.

The paper addresses the connectivity issues related to integrating an Automated Model Based Calibration System (MTS Atlas) to a dynamometer test bed data acquisition system using an ASAM-GDI Interface. The GDI (Generic Device Interface) implementation was chosen over other ASAM interfaces due to its real-time capabilities and the ability to host new GDI drivers as these drivers become available. A structured migration process is developed showing how a new interface standard can be implemented that integrates with legacy test equipment, yet provides a simple low cost mechanism allowing replacement of old or redundant equipment.

Laboratory performance testing of larger tires requires system capability beyond larger diametric clearance and additional radial load capability. This paper describes a newly introduced Flat-Trac® tire test system designed for light truck tires and racing tires. Background on flat surface force and moment testing identifying the need for a system with more capability is presented. The MTS Flat-Trac LTR tire test system is introduced as a force and moment measurement system capable of testing light truck and racing tires. The first of these systems has been in operation at Bridgestone's Tokyo technical center since July 2002. Test results are presented to show that the Flat-Trac LTR (Light Truck/Racing) provides increased capability beyond the conventional Flat-Trac III CT (Cornering and Traction) system. Cornering force and longitudinal force test results are compared to show agreement between the Flat-Trac LTR and Flat-Trac CT systems.

The objective of this work was to increase the effectiveness and efficiency of road simulation testing with an emphasis on obtaining more information from the laboratory test system. Attaining the objective was evaluated by the criteria: 1) was vehicle damage detected before a major failure, 2) were changes in test conditions that would result in over- or under-testing detected, 3) were vehicle and test system components that require maintenance detected and 4) did the changes detected provide a better understanding of the test specimen and analytical predictions. The tools used for this process were not integrated. An integrated set of tools would be required to make this a general-purpose technique