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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.

This paper presents the results of a study of using a neural network black box model of a shock absorber of an ATV (All Terrain Vehicle, four wheel drive, off road, single person vehicle) for accurate load modeling. This study is part of a larger investigation into the dynamic behavior and associated fatigue of an ATV vehicle, which is conducted under the auspices of the Fatigue Design and Evaluation Committee of SAE of North America (www.fatigue.org). The general objectives are to develop new correlated methodologies that will allow engineers to predict the durability of components of proposed vehicles by means of a “digital prototype” simulation. Current state of the art multi body dynamics predictions use linear frequency response functions or non-linear polynomial approximations to describe the behavior of non-linear suspension components such as shock absorbers or bushings.

Brake groan noise and vibration occurs in a stopped vehicle by the simultaneous application of torque to the wheel and the gradual release of brake pressure. Eventually the torque load breaks the friction between pad and rotor causing slippage and energy release. If the torque load is not large enough to maintain slippage, a sustained stick-slip vibration, called groan, can occur which transmits a low frequency noise to the vehicle interior. In some cases the noise levels caused by groan can be objectionable, thus procedures for developing remedial designs are needed. To this end, a project was performed to analytically simulate groan vibration in a vehicle with a McPherson strut type suspension. The goal was to demonstrate that analytical models could be used to simulate groan behavior and to identify suspension components that affect the groan behavior. The ADAMS software was used to model a brake/suspension system.

The wheel force transducer has been proven to be a cost and time effective tool for vehicle load data acquisition and simulation testing. The accuracy of wheel force transducers is typically given in terms of a static calibration, or a quasi-static system generated load case. The actual use of a wheel force transducer often involves high speed rotation, varying camber and steer of the tire on the vehicle, and other dynamic and rim related variations which deviate from the standard laboratory calibration. The Flat-Trac proves to be an excellent tool in the design process and evaluation of the wheel force transducer because it accurately controls and simulates the loading of a rotating wheel assembly. Through Flat-Trac System testing, issues that are critical to the use, accuracy, and integrity of data acquired through a wheel force transducer can be evaluated.

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.