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This paper examines the use of camera-matching video analysis techniques to quantify the vehicle dynamics and deformation for a dolly rollover test run in accordance with the SAE Recommended Practice J2114. The method presented enables vehicle motion data and deformation measurements to be obtained without the use of the automated target tracking employed by existing motion tracking systems. Since it does not rely on this automated target tracking, the method can be used to analyze video from rollover tests which were not setup in accordance with the requirements of these automated motion tracking systems. The method also provides a straightforward technique for relating the motion of points on the test vehicle to the motion of the vehicle's center-of-mass. This paper, first, describes the specific rollover test that was utilized. Then, the camera-matching method that was used to obtain the vehicle motion data and deformation measurements is described.

Yaw rate of a vehicle is highly influenced by the lateral forces generated at the tire contact patch to attain the desired lateral acceleration, and/or by external disturbances resulting from factors such as crosswinds, flat tire or, split-μ braking. The presence of the latter and the insufficiency of the former may lead to undesired yaw motion of a vehicle. This paper proposes a steer-by-wire system based on fuzzy logic as yaw-stability controller for a four-wheeled road vehicle with active front steering. The dynamics governing the yaw behavior of the vehicle has been modeled in MATLAB/Simulink. The fuzzy controller receives the yaw rate error of the vehicle and the steering signal given by the driver as inputs and generates an additional steering angle as output which provides the corrective yaw moment.

An attractive strategy for joining metallic as well as non-metallic substrates through adhesive bonding. This technique of joining also offers the functionality for joining dissimilar materials. However, doubts are often expressed on the ability of such joints to perform on par with other mechanical fastening methodologies such as welding, riveting, etc. In the current study, adhesively-bonded single lap shear (SLS), double lap shear (DLS) and T-peel joints are studied initially under quasi-static loading using substrates made of a grade of mild steel and an epoxy-based adhesive of a renowned make (Huntsman). Additionally, single lap shear joints comprised of a single spot weld are tested under quasi-static loading. The shear strengths of adhesively-bonded SLS joints and spot-welded SLS joints are found to be similar. An important consideration in the deployment of adhesively bonded joints in automotive body structures would be the performance of such joints under impact loading.

Recent experimental studies on the behavior of adhesively-bonded steel double-hat section components under axial impact loading have produced encouraging results in terms of load-displacement response and energy absorption when compared to traditional spot-welded hat- sections. However, it appears that extremely limited study has been carried out on the behavior of such components under transverse impact loading keeping in mind applications such as automotive body structures subject to lateral/side impact. In the present work, lateral impact studies have been carried out in a drop-weight test set-up on adhesively-bonded steel double-hat section components and the performance of such components has been compared against their conventional spot-welded and hybrid counterparts. It is clarified that hybrid components in the present context refer to adhesively-bonded hat-sections with a few spot welds only aimed at preventing catastrophic flange separations.

A number of studies, using data from NASS-CDS, have shown a large percentage of rollover crashes can be classified as tripped events. In many cases, the requirements for a tripped rollover detection algorithm are driven by the timely activation of an occupant containment device. To meet these requirements rollover detection algorithms have been developed by utilizing vehicle roll rate, lateral and vertical accelerations data collected primarily from laboratory tests. This study identifies and examines several challenges associated with developing a rollover detection algorithm with enhanced capabilities. Enhancement of the detection algorithm is explored by considering additional vehicle responses: forward velocity and sideslip angle. With the additional signals, discrimination of rollover crashes from other crash modes is discussed. Potential field/laboratory test modes are proposed to generate the additional vehicle signals.

Space frame type vehicle construction with extruded aluminum members holds promise in terms of desirable vibration-resistant and crashworthiness characteristics. Efficient design of such vehicles for superior frontal crash performance can be accomplished by judicious use of validated finite element and lumped parameter modeling and analysis. However, design iterations can be reduced considerably by employing energy-absorption targets for key members such as front rails in arriving at the initial design concept. For the NCAP (New Car Assessment Program) test procedure, a constraint is laid in terms of achieving a desirable level of vehicle peak deceleration for occupant safety. Using the information obtained through analysis, a numerical target can be set for energy to be absorbed by front rails. For this energy target, a new relationship is then derived which can be utilized for preliminary design of rail cross-section and material strength.

This paper presents an image analysis of a laboratory-based rollover crash test using camera-matching photogrammetry. The procedures pertaining to setup, analysis and data process used in this method are outlined. Vehicle roll angle and rate calculated using the method are presented and compared to the measured values obtained using a vehicle mounted angular rate sensor. Areas for improvement, accuracy determination, and vehicle kinematics analysis are discussed. This paper concludes that the photogrammetric method presented is a useful tool to extract vehicle roll angle data from test video. However, development of a robust post-processing tool for general application to crash safety analysis requires further exploration.

The design of structural components requires a knowledge of their crush characteristics, particularly the load-carrying capacity during dynamic crash. Although many attempts have been made to develop analytical techniques or methods for predicting these characteristics, experimental tests are still needed to provide data for real structures for either development or validation. This report describes an experimental method for determining the force-deflection characteristics during dynamic crush of square steel columns using a drop tower test facility. The custom-designed load cells were used for the measurements of the impact and the reaction forces at both ends of specimens, which were subjected to a 30 mph impact. Instrumentation for data acquisition and detailed data reduction for analysis are also presented.

A computational model of a mid-size sport utility vehicle was developed using MADYMO. The model includes a detailed description of the suspension system and tire characteristics that incorporated the Delft-Tyre magic formula description. The model was correlated by simulating a vehicle suspension kinematics and compliance test. The correlated model was then used to simulate a J-turn vehicle dynamics test maneuver, a roll and non-roll ditch test, corkscrew ramp and a lateral trip test, the results of which are presented in this paper. The results indicate that MADYMO is able to reasonably predict the vehicle and occupant responses in these types of applications and is potentially suited as a tool to help setup a suite of vehicle configurations and test conditions for rollover sensor testing. A suspension system sensitivity study is presented for the laterally tripped non-roll event.