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Efforts by vehicle manufacturers to reduce road testing have resulted in an increased reliance on the simulation methods for loads measurement and validation, including increased emphasis on methods to characterize and digitally represent test road inputs. Accurate terrain models are especially important in the case of large dynamic road inputs, and for evaluation of vehicle suspension loads and durability. In contrast to direct terrain topology measurement, methods to estimate test road input using only vehicle suspension measurements and a tire dynamic model will be presented. Applications of terrain models for generic simulation and testing will also be discussed.

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.

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 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.

The sound field in a vehicle is one of the most complex environments being a mixture of multiple, correlated and uncorrelated sound sources. The simulation of vehicle interior sound has traditionally been produced by combining multiple test results where the influence of one source is enhanced while the other sources are suppressed, such as towing the vehicle on a rough surface for road noise, or measuring noise in a wind tunnel. Such methods are costly and provide inherent inaccuracies due to source contamination and lack of synchronization between sources. In addition they preclude the addition of analytical predictions into the simulation. The authors propose an alternative approach in which the component sounds are decomposed or separated from a single operating measurement and which provide the basis for accurate sound synthesis.

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 documents the process used to correlate the secondary belt degradation experienced on the test track with the secondary belt degradation experienced during laboratory tests using a Secondary Drive Test System. Two different software products were used to produce this correlation: nCode's pseudo-damage functionality was used to estimate the proportional belt degradation and MTS's RPC Pro functionality was used to edit the field data, create a time history file, and to shift the frequency domain of the vehicle into the usable range of the servo-hydraulic actuator (time stretching). For purposes of this paper, the test data and information presented in this paper is based on two different secondary drive belts that were used on the test track as well as in the laboratory tests. As will be shown, the plot information that resulted from these tests showed very good correlation.

A major challenge facing the vehicle simulation test laboratory is correlating (and thereby validating) the simulated “test track” with the In-service environment. This simulation is key to the use of data for durability analysis from the integrated design and testing engineering process. Presented here is an approach to integrating road simulation test and fatigue life analysis that produces needed results for test, design and analysis engineers. The core of the analysis is a fatigue-based “rig-to-road” comparison for an on-highway vehicle using strain-time data acquired at fatigue sensitive locations. The cyclic and fatigue damaging content of the field and simulation profiles are compared quantitatively for purposes of validating the laboratory lest, and to illustrate a method of reporting this validation to design and analysis engineers.

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

A building-block method, often used for simulating automotive systems, is described in this paper for simulating a driveline system. In the method, a driveline supplier's design responsible components are modeled with explicit FE models. Model accuracy is verified by testing and correlating the components in a free-free condition. Non-design responsible components are modeled using lumped parameters and/or modal models. These components and the validated design responsible components are integrated into a system model and connected using simple lumped parameter connections. Correlation at the system level is performed by making adjustments to the connection parameters and to the parameters of the non-design responsible components. The resulting system model has been used to accurately predict operating responses in a driveline system.