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The search for improvements in occupant protection under vehicle impact is hampered by a real lack of reliable biomechanical data. To help fill this void, General Motors has initiated joint research with independent researchers such as the School of Medicine, U. C. L. A. – in this case to study localized head and facial trauma — and has developed such unique laboratory tools as “Tramasaf,” a human-simulating headform, and “MetNet,” a pressure-sensitive metal foam. Research applied directly to product design also has culminated in developments such as the Side-Guard Beam for side impact protection.

The purpose of this study was to determine the optimal location of the shoulder belts for a suspender style four-point safety belt system. This optimal location must satisfy two conditions. First, the shoulder belts must properly fit over the occupant’s shoulders for safety performance. Second, the shoulder belts location on the occupant’s body must be acceptable to the occupant. To determine the optimal acceptable location of the shoulder belts, forty-four subjects were recruited by height and tested in a reconfigurable test seat. The results showed that avoiding an interaction between the shoulder belts and the occupant’s neck improved the acceptability of the system. Variables that affected this interaction included the horizontal and vertical position of the shoulder belts and the occupant’s weight, clothing, and gender.

The increased focus on occupant protection by automobile manufacturers combined with incessant consumer demand for safety features such as dual airbags has posed design engineers with major challenges in the field of Instrument Panel (IP) design. Typically, airbags are designed to deploy when the speed of the automobile is above 13 mph in a frontal impact. The airbag door should meet head impact requirements for unbelted occupants involved in low speed impacts (<15mph) when airbags are not deployed. This paper describes how computer aided engineering (CAE) simulation techniques were used in improving the design of the passenger airbag door of a full size van for head impact performance. Fewer tests were conducted primarily for validation, which resulted in significantly less prototypes, costs and time.

In the 1999 Supplemental Notice for Proposed Rulemaking (SNPRM) for Advanced Airbags, the National Highway Traffic Safety Administration (NHTSA) sought comments on the maximum speed at which the high-speed, unbelted occupant test suite will be conducted, i.e., 48 kph vs. 40 kph. To help address this question, an analysis of constraints was performed via extensive mathematical modeling of a theoretical restraint system. First, math models (correlated with several existing physical tests) were used to predict the occupant responses associated with 336 different theoretical dual-stage driver airbag designs subjected to six specific Regulated and non-Regulated tests.

The dilemma of using a shoulder belt force limiter with a 3-point belt system is selecting a limit load that will balance the reduced risk of significant thoracic injury due to the shoulder belt loading of the chest against the increased risk of significant head injury due to the greater upper torso motion allowed by the shoulder belt load limiter. However, with the use of air bags, this dilemma is more manageable since it only occurs for non-deploy accidents where the risk of significant head injury is low even for the unbelted occupant. A study was done using a validated occupant dynamics model of the Hybrid III dummy to investigate the effects that a prescribed set of shoulder belt force limits had on head and thoracic responses for 48 and 56 km/h barrier simulations with driver air bag deployment and for threshold crash severity simulations with no air bag deployment.

The Hybrid III dummy is an anthropomorphic (humanlike) test device, generally used in crashworthiness testing to assess the extent of occupant protection provided by the vehicle structure and its restraint systems in the event of vehicle crash. Lumped-parameter analytical models are commonly used to simulate the dummy response. These models, by virtue of their limited number of degrees of freedom, can neither represent accurate three-dimensional dummy geometry nor detailed structural deformations. In an effort to improve the state-of-the-art in analytical dummy simulations, a set of finite element models of the Hybrid III dummy segments - head, neck, thorax, spine, pelvis, knee, upper extremities and lower extremities - were developed. The component models replicated the hardware geometry as closely as possible. Appropriate elastic material models were selected for the dummy “skeleton”, with the exterior “soft tissues” represented by viscoelastic materials.

In an attempt to predict the responses of side crash pressure sensors, the Corpuscular Particle Method (CPM) was adopted and enhanced in this research. Acceleration-based crash sensors have traditionally been used extensively in automotive industry to determine the air bag firing time in the event of a vehicle accident. The prediction of crash pulses obtained from the acceleration-based crash sensors by using computer simulations has been very challenging due to the high frequency and noisy responses obtained from the sensors, especially those installed in crash zones. As a result, the sensor algorithm developments for acceleration-based sensors are largely based on prototype testing. With the latest advancement in the crash sensor technology, side crash pressure sensors have emerged recently and are gradually replacing acceleration-based sensor for side impact applications.

An Arbitrary Lagrangian Eulerian (ALE) approach was adopted in this study to predict the responses of side crash pressure sensors in an attempt to assist pressure sensor algorithm development by using computer simulations. Acceleration-based crash sensors have traditionally been used to deploy restraint devises (e.g., airbags, air curtains, and seat belts) in vehicle crashes. The crash pulses recorded by acceleration-based crash sensors usually exhibit high frequency and noisy responses depending on the vehicle's structural design. As a result, it is very challenging to predict the responses of acceleration-based crash sensors by using computer simulations, especially those installed in crush zones. Therefore, the sensor algorithm developments for acceleration-based sensors are mostly based on physical testing.

With a goal to help develop pressure sensor calibration and deployment algorithms using computer simulations, an Arbitrary Lagrangian Eulerian (ALE) approach was adopted in this research to predict the responses of side crash pressure sensors for unitized vehicles. For occupant protection, acceleration-based crash sensors have been used in the automotive industry to deploy restraint devices when vehicle crashes occur. With improvements in the crash sensor technology, pressure sensors that detect pressure changes in door cavities have been developed recently for vehicle crash safety applications. Instead of using acceleration (or deceleration) in the acceleration-based crash sensors, the pressure sensors utilize pressure change in a door structure to determine the deployment of restraint devices. The crash pulses recorded by the acceleration-based crash sensors usually exhibit high frequency and noisy responses.

In an attempt to assist pressure sensor algorithm and calibration development using computer simulations, an Arbitrary Lagrangian Eulerian (ALE) approach was adopted in this study to predict the responses of side crash pressure sensors for body-on-frame vehicles. Acceleration based, also called G-based, crash sensors have been used extensively to deploy restraint devices, such as airbags, curtain airbags, seatbelt pre-tensioners, and inflatable seatbelts, in vehicle crashes. With advancements in crash sensor technologies, pressure sensors that measure pressure changes in vehicle side doors have been developed recently and their applications in vehicle crash safety are increasing. The pressure sensors are able to detect and record the dynamic pressure change when the volume of a vehicle door changes as a result of a crash.

A study was conducted by General Motors at its crash test facility located at the Milford Proving Ground. The intent of this study was to expand upon the currently available research regarding the safety belt buckle environment during full scale planar crash tests. Buckle accelerations and webbing tensions were measured and recorded to characterize, in part, buckle responses in a crash environment. Previous studies have focused primarily on the component level testing of safety belt buckles. The crash tests included a variety of vehicles, impact types, seating positions, Anthropomorphic Test Devices (ATDs), impact speeds, and impact angles. Also included were various safety belt restraint systems and pretensioner designs. This study reports on data recorded from 100 full scale crash tests with 180 instrumented end release safety belt buckles. Acceleration measurements were obtained with tri-axial accelerometers mounted onto the buckles.

This paper describes an analytical method to predict the sensor closure time for an airbag (Supplemental Inflatable Restraint - SIR) system in frontal impacts. The analytical tools used are the explicit finite element code, an in-house sensor closure time prediction program, and a full vehicle finite element model. Nodal point information obtained from the full vehicle finite element simulation is used to predict the sensor closure time of the airbag system. This analytical method can provide the important crash signature information for a SIR system development of a new vehicle program. In this paper, 0-degree frontal impacts at four different impact speeds with two different bumper energy absorption systems are studied using the non-linear finite element computer program DYNA3D. It is concluded that this analytical method is very useful to predict the SIR sensor closure time.

Although rollover crashes represent a small fraction (approximately 3%) of all motor vehicle crashes, they account for roughly one quarter of crash fatalities to occupants of cars, light trucks, and vans (NHTSA Traffic Safety Facts, 2004). Therefore, the National Highway Traffic Safety Administration (NHTSA) has identified rollover injuries as one of its safety priorities. Motor vehicle manufacturers are developing technologies to reduce the risk of injury associated with rollover collisions. This paper describes the development by General Motors Corporation (GM) of a suite of laboratory tests that can be used to develop sensors that can deploy occupant protection devices like roof rail side air bags and pretensioners in a rollover as well as a discussion of the challenges of conducting this suite of tests.

This paper summarizes the results of tests conducted with anesthetized animals that were exposed to a wide range of passenger inflatable restraint cushion forces for a variety of impact sled - simulated accident conditions. The test configurations and inflatable restraint system concepts were selected to produce a broad spectrum of injury types and severities to the major organs of the head, neck and torso of the animals. These data were needed to interpret the significance of the responses of an instrumented child dummy that was being used to evaluate child injury potential of the passenger inflatable restraint system being developed by General Motors Corporation. Injuries ranging from no injury to fatal were observed for the head, neck and abdomen regions. Thoracic injuries ranged from no injury to critical, survival uncertain.

This paper presents the results of a series of over 30 impact sled simulations of racing car frontal crashes conducted as part of the GM Motorsports Safety Technology Research Program. A Hyge™ impact sled fitted with a simulated racing car seat and restraint system was used to simulate realistic crash loading with a mid-size male Hybrid III dummy. The results of tests, in the form of measured loads, displacements, and accelerations, are presented and comparisons made with respect to the levels of these parameters seen in typical passenger car crash testing and to current injury threshold values.

Vehicle side impact performance is potentially affected by a large number of parameters which may be related to body stiffness and energy absorption characteristics, and packaging dimensions. An understanding of the principal variables controlling TTI (Thoracic Trauma Index) is fundamental to the achievement of high LINCAP (Lateral Impact New Car Assessment Program) rating especially for sedans. In the present study, the effects on TTI of the following are considered: response-related parameters such as velocity and intrusion (which are in turn related to body structure), countermeasures such as side airbag, and dummy to structure clearance dimensions. With the help of test data gathered from side impact tests carried out on cars and trucks at Ford, a new “best subset” regression model is developed and is shown to be able to predict TTI for a number of LINCAP tests which were not part of the suite used in the derivation of the model.

Two rigid rollover test devices were constructed to have the approximate dimensions, mass and inertial properties of a mid-sized Car and Sport Utility Vehicle (SUV). The rigid devices were used to generate vehicle and occupant responses from a series of laboratory rollover tests. For each rigid rollover test, a deceleration sled was used to subject each rigid vehicle to nearly identical lateral speeds and decelerations. The rigid vehicles were limited to a single roll by tethering the vehicles to the deceleration cart. The vehicle's roll rate, roll angle, lateral acceleration and Anthropomorphic Test Devices (ATD) neck responses generated from the rigid SUV were compared to the responses of a full vehicle production SUV under similar test conditions. The rigid SUV and Car devices were then used to examine the effects of activating safety belt pre-tensioning systems and roof mounted side curtain airbags at various times on ATD neck forces and moments.

A primary concern in the development of a passenger inflatable restraint system is the possibility that a child could be in the path of the deploying cushion either due to initial position at the time of an accident or due to precrash braking accompanying an accident. Previous studies by General Motors and Volvo have indicated that serious injuries to children are possible if the cushion/child interaction forces are not controlled by system design. This paper describes an instrumented child dummy which was developed to provide measurements of the various cushion/child interaction forces. An analysis is given describing the types of injuries which could be associated with the various types of interaction forces. These results were used to develop appropriate dummy instrumentation for indicating the severity of the cushion/child interaction. A description of the modifications made to an existing three-year-old child dummy are described.

Design optimization techniques are widely used to drive designs toward a global or a near global optimal solution. However, the achieved optimal solution often appears to be the only choice that an engineer/designer can select as the final design. This is caused by either problem topology or by the nature of optimization algorithms to converge quickly in local/global optimal or both. Problem topology can be unimodal or multimodal with many local and/or global optimal solutions. For multimodal problems, most global algorithms tend to exploit the global optimal solution quickly but at the same time leaving the engineer with only one choice of design. The paper explores the application of genetic algorithms (GA), simulated annealing (SA), and mixed integer problem sequential quadratic programming (MIPSQP) to find multiple local and global solutions using single objective optimization formulation.

In this paper, the concept of ridedown analysis is extended to provide the total occupant energy and ridedown energy as functions of time. The difference between the total occupant energy and the energy absorbed by the front structure represents the energy which is dissipated by deforming the components of the restraint system. This analysis allows an improved understanding of the restraint system as a whole, and how its components interact with each other and with the front structure of the car to dissipate the occupant's energy throughout the crash event.