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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.

Shudder vibration of a hydraulic power steering system during parking maneuver was studied with numerical and experimental methods. To quantify vibration performance of the system and recognize important stimuli for drivers, a shudder metric was derived by correlation between objective measurements and subjective ratings. A CAE model for steering wheel vibration analysis was developed and compared with measured data. In order to describe steering input dependency of shudder, a new dynamic friction modeling method, in which the magnitude of effective damping is determined by average velocity, was proposed. The developed model was validated using the measured steering wheel acceleration and the pressure change at inlet of the steering gear box. It was shown that the developed model successfully describes major modes by comparing the calculated FRF of the hydraulic system with measured one from the hydraulic excitation test.

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.

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.

The quietness of the interior of automobiles is perceived by consumers as a measure of quality and luxury. Great strides have been achieved in isolating interiors from noise sources. As noise is reduced, in particular wind and power train noise, other noise sources become evident. Noise reduction efforts are now focused on components like power steering pumps. To understand the contribution of power steering pumps a world-class noise and vibration test stand was developed. This paper describes the development of the test stand as well as it's objective to understand and improve the sound quality of power steering pumps.

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.

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.

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.

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.