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Described in this paper is a component test methodology to evaluate the door trim armrest performance in an Insurance Institute for Highway Safety (IIHS) side impact test and to predict the SID-IIs abdomen injury metrics (rib deflection, deflection rate and V*C). The test methodology consisted of a sub-assembly of two SID-IIs abdomen ribs with spine box, mounted on a linear bearing and allowed to translate in the direction of impact. The spine box with the assembly of two abdominal ribs was rigidly attached to the sliding test fixture, and is stationary at the start of the test. The door trim armrest was mounted on the impactor, which was prescribed the door velocity profile obtained from full-vehicle test. The location and orientation of the armrest relative to the dummy abdomen ribs was maintained the same as in the full-vehicle test.

Designing a vehicle for superior crash safety performance in consumer rating tests such as US-NCAP is a compelling target in the design of passenger vehicles. In today’s context, there is also a high emphasis on making a vehicle as lightweight as possible which calls for an efficient design. In modern vehicle design, these objectives can only be achieved through Computer-Aided Engineering (CAE) for which a detailed CAD (Computer-Aided Design) model of a vehicle is a pre-requisite. In the absence of the latter (i.e. a matured CAD model) at the initial and perhaps the most crucial phase of vehicle body design, a rational approach to design would be to resort to a knowledge-based methodology which can enable crash safety assessment of an assumed design using artificial intelligence techniques such as neural networks.

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.

The goal of optimization in vehicle design is often blurred by the myriads of requirements belonging to attributes that may not be quite related. If solutions are sought by optimizing attribute performance-related objectives separately starting with a common baseline design configuration as in a traditional design environment, it becomes an arduous task to integrate the potentially conflicting solutions into one satisfactory design. It may be thus more desirable to carry out a combined multi-disciplinary design optimization (MDO) with vehicle weight as an objective function and cross-functional attribute performance targets as constraints. For the particular case of vehicle body structure design, the initial design is likely to be arrived at taking into account styling, packaging and market-driven requirements.

Rapid progress in the interdisciplinary field of automotive engineering and the pressing need for an environmental friendly alternative to metal and synthetic fiber-reinforced composites for vehicle structure have triggered recent research in the field of natural fiber-based composites. Their potential advantages are attributed to their light weight, low cost and biodegradability. However, their usage in present day automotive systems is restricted due a lower magnitude range of mechanical properties and limited study in this area. In contrast to mechanical joints, the adhesively bonded joints aid in reducing stress concentration, joining of dissimilar materials, corrosion prevention, weight reduction and a smoother finish. Thus, in the present study, failure load, and mean shear stress of single lap shear and double lap shear joints as a function of joint overlap length, are evaluated using a two part epoxy adhesive made by Huntsman.

Natural fiber-based composites such as jute-polyester composites have the potential to be more cost-effective and environment-friendly substitutes for glass fiber-reinforced composites which are commonly found in many applications. In an earlier study (Mache and Deb [1]), jute-polyester composite tubes of circular and square cross-sections were shown to perform competitively under axial impact loading conditions when compared to similar components made of bidirectional E-glass fiber mats and thermo-setting polyester resin. For jute-reinforced plastic panels to be feasible solutions for automotive interior trim panels, laminates made of such materials should have adequate perforation resistance. In the current study, a systematic characterization of jute-polyester and glass-polyester composite laminates made by compression molding is at first carried out under quasi-static tensile, compressive and flexural loading conditions.

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.

This paper presents the design of a crash detection system based on the principles of continuous-mode Hidden Markov Models (HMM) with real-valued emission parameters. Our design utilizes log-likelihood for optimizing HMM parameters including the number of states in the model and the accelerometer crash-pulse buffer size resulting in lower costs and complexity of the crash detection system. Cross validation technique based on Jackknifing is utilized to estimate the crash pulse detection rate for a variety of crash events involving rigid as well as offset deformable barriers with head-on and oblique angle impacts. The system is simulated using Matlab and Simulink, and the proposed model is able to accurately classify crash-events within 10 ms from the time of the impact.

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.

Hat sections made of steel are frequently encountered in automotive body structural components such as front rails. These components can absorb significant amount of impact energy during collisions thereby protecting occupants of vehicles from severe injury. In the initial phase of vehicle design, it will be prudent to incorporate the sectional details of such a component based on an engineering target such as peak load, mean load, energy absorption, or total crush, or a combination of these parameters. Such a goal can be accomplished if efficient and reliable data-based models are available for predicting the performance of a section of given geometry as alternatives to time-consuming and detailed engineering analysis typically based on the explicit finite element method.

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.

Adhesive bonding provides a versatile strategy for joining metallic as well as non-metallic substrates, and also offers the functionality for joining dissimilar materials. In the design of unibody vehicles for NVH (Noise, Vibration and Harshness) performance, adhesive bonding of sheet metal parts along flanges can provide enhanced stiffening of body-in-white (BIW) leading to superior vibration resistance at low frequencies and improved acoustics due to sealing of openings between flanges. However, due to the brittle nature of adhesives, they remain susceptible to failure under impact loading conditions. The viability of structural adhesives as a sole or predominant mode of joining stamped sheet metal panels into closed hollow sections such as hat-sections thus remains suspect and requires further investigation.

Adhesively bonded steel hat section components have been experimentally studied in the past as a potential alternative to traditional hat section components with spot-welded flanges. One of the concerns with such components has been their performance under axial impact loading as adhesive is far more brittle as compared to a spot weld. However, recent drop-weight impact tests have shown that the energy absorption capabilities of adhesively bonded steel hat sections are competitive with respect to geometrically similar spot-welded specimens. Although flange separation may take place in the case of a specimen employing a rubber toughened epoxy adhesive, the failure would have taken place post progressive buckling and absorption of impact energy.

Many foams exhibit significant strain rate dependency in their mechanical responses. To characterize these foams, a strain rate dependent constitutive model is formulated and implemented in an explicit dynamic finite element code developed at FORD. The constitutive model is developed in conjunction with a Lagrangian eight node solid element with twenty four degrees of freedom. The constitutive model has been used to model foams in a number crash analysis problems. Results obtained from the analyses are compared to the experimental data. Evidently, numerical results show excellent agreement with the experimental data.

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.