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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.

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.

Vehicle idle quality has become an increasing quality concern for automobile manufacturers because of its impact on customer satisfaction. There are two factors that critical to vehicle idle quality, the engine excitation force and vehicle sensitivity (transfer function). To better understand the contribution to the idle quality from these two factors and carry out well-planned improvement measures, a quick and easy way to measure vehicle sensitivity at idle conditions is desired. There are several different ways to get vehicle sensitivity at idle conditions. A typical way is to use CAE. One of the biggest advantages using CAE is that it can separate vehicle sensitivities to different forcing inputs. As always, the CAE results need to be validated before being fully utilized. Another way to get vehicle sensitivity is through impact test using impact hammer or shaker. However this method doesn't include the mount preload due to engine firing torque [3, 4, & 5].

The ability to extract and evaluate the time history of structural deformations or crush during vehicle crashes represents a significant challenge to automotive safety researchers. Current methods are limited by the use of electro-mechanical devices such as string pots and/or linear variable displacement transducers (LVDT). Typically, one end of the transducer must be mounted to a point on the structure that will remain un-deformed during the event; the other end is then attached to the point on the structure where the deformation is to be measured. This approach measures the change in distance between these two points and is unable to resolve any movement into its respective X, Y, or Z directions. Also, the accuracy of electro-mechanical transducers is limited by their dynamic response to crash conditions. The photogrammetry technique has been used successfully in a wide variety of applications including aerial surveying, civil engineering and documentation of traffic accidents.

This paper reports a study of the dynamic characteristics of body mounts in body on frame vehicles and their effects on structural and occupant CAE results. The body mount stiffness and damping are computed from spring-damper models and component test results. The model parameters are converted to those used in the full vehicle structural model to simulate the vehicle crash performance. An effective body mount in a CAE crash model requires a set of coordinated damping and stiffness to transfer the frame pulse to the body. The ability of the pulse transfer, defined as transient transmissibility[1]1, is crucial in the early part of the crash pulse prediction using a structural model such as Radioss[2]. Traditionally, CAE users input into the model the force-deflection data of the body mount obtained from the component and/or full vehicle tests. In this practice, the body mount in the CAE model is essentially represented by a spring with the prescribed force-deflection data.

For more than 30 years, field research and laboratory testing have consistently demonstrated that properly wearing a seat belt dramatically reduces the risk of occupant death or serious injury in motor vehicle crashes. In severe rollover crashes, deformation to vehicle body structures can relocate body-mounted seat belt anchors altering seat belt geometry. In particular, roof pillar mounted shoulder belt anchors (“D-rings”) are subject to vertical and lateral deformation in the vehicle coordinate system. The ROllover Component test System (ROCS) test device was utilized to evaluate seat belt system performance in simulated severe rollover roof-to-ground impacts. A mechanical actuator was designed to dynamically relocate the D-ring assembly during a roof-to-ground impact event in an otherwise rigid test vehicle fixture. Anthropomorphic test device (ATD) kinematics and kinetics and seat belt tensions were compared between tests with and without D-ring relocation.

The head, chest and femurs of three Hybrid II dummies were impacted with a ballistic pendulum at various angles to determine what differences in accelerometer and femur load cell output would result for a constant energy input. Also evaluated were suspicious tension loads in the femur load cell output when the legs were subjected to obvious off-center impacts during crash tests. It was found that the dummy legs can be subjected to very high torsion and bending loads which can have a significant effect on the femur load cell axial load outputs.

Variations in human skull thickness affecting human head dynamic impact responses were studied by finite element modeling techniques, experimental measurements, and histology examinations. The aims of the study were to better understand the influences of skull thickness variations on human head dynamic impact responses and the injury mechanisms of human head during direct impact. The thicknesses of the frontal bone of seven human cadaver skulls were measured using ultrasonic technology. These measurements were compared with previous experimental data. Histology of the skull was recorded and examined. The measured data were analyzed and then served as a reference to vary the skull thickness of a previously published three-dimensional finite element human head model to create four models with different skull thickness. The skull thicknesses modeled are 4.6 mm, 5.98 mm, 7.68 mm, and 9.61 mm.

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.

There has been a general consensus in the scientific literature that a rim gouging, not scraping, into a roadway surface generates very high forces which can cause a vehicle to overturn in some situations. However, a paper published in 2004 attempts to minimize the forces created during wheel rim gouging and the effect on vehicle rollover. This paper relied largely on heavily filtered lateral acceleration data and discounted additional test runs by the authors and NHTSA that did not support the supposed conclusions. This paper will discuss the effect of rim gouging using accepted scientific methods, including full vehicle testing where vehicle accelerations were measured during actual rim gouging events and static testing of side forces exerted by wheels mounted on a moving test fixture. The data analyzed in this paper clearly shows that forces created by rim gouges on pavement can be thousands of Newtons and can contribute to vehicle rollover.

This paper describes (1) the findings from the implementation of a component test methodology for body, engine and transmission mounts [1, 2 and 3], and (2) the associated CAE model development and mount design robustness enhancement. A series of component tests on light truck body, engine and transmission mounts have been conducted to not only obtain their characteristics as inputs for crashworthiness analysis, but also drive mount design direction for frontal impacts.

The front rail plays an important role in the performance of body-on-frame (BOF) vehicles in frontal crashes. New developments in materials and forming technology have led to the exploration of different configurations to improve crash performance. This paper presents the initial stages of an ongoing study to investigate the effects of the cross section of steel columns on crash performance in automotive applications. Because accurate prediction of the performance of these rails can help reduce the amount of physical crash testing necessary, the focus of this paper is on appropriate testing and modeling procedures for different rail configurations. In the first part of this paper, the Finite Element Analysis (FEA) methodology is presented with respect to correlation with real world tests. The effects of various parameters are described, along with the optimum configuration for model correlation.

Hydroformed components are replacing stamped parts in automotive frames and front end and roof structures to improve the crash performance of vehicles. Due to the increasing application of hydroformed components, a better understanding of the crash behavior of these parts is necessary to improve the correlation between full-vehicle crash tests and FEM analysis. Accurately predicting the performance of hydroformed components will reduce the amount of physical crash testing necessary to develop the new components and new vehicles as well as reduce cycle time. Virgin material properties are commonly used in FEM analysis of hydroformed components, which leads to erroneous prediction of the full-vehicle crash response. Changes in gauge and material properties during the hydroforming process are intuitive and can be reasonably predicted by using forming simulations. The effects of the forming process have been investigated in the FEA models that are created for crash analyses.

The front end module technology is a system developed to make the interface with vehicle body in accordance with costumer requirements. This modular system also has characteristics to reinforce the structure (chassis, main rails, shotguns), respecting its robustness (tolerances of the body) in accordance with NVH performance. The decision of having a FEM design made by steel and plastic was taken due to NVH specification, impact and safety requirements. Other items were either considered such as: fixation on the body of the vehicle, constraints between bumper beam and engine cooling module. Simulation tools including: durability test (static and dynamic) and modal F.E.A analysis, CAE system, crash test performance, aerodynamics required to insure results desired results.

The optimization method and CAE analysis have been widely used in structure design for crash safety. Combining the CAE analysis and optimization approach, vehicle structure design for crash can be implemented more efficiently. One of the recent safety desirables in structure design is to reduce vehicle pitch and drop. At frontal impact tests with unbelted occupants, the interaction between occupant's head and interior header/sun visor, which is caused by excessive vehicle pitch and drop, is not desired in vehicle crash development. In order to comply with the federal frontal crash requirements for unbelted occupant, it is necessary to manage the vehicle pitch and drop by improving structure design. In this paper, a systematic process of CAE analysis with optimization approach is applied for discovering the major structural components affecting vehicle pitch and drop.

In vehicle safety engineering, it is important to determine the severity of occupant injury during a crash. Computer simulations are widely used to study how occupants move in a crash, what they collide during the crash and thus how they are injured. The vehicle motion is typically defined for the occupant simulation by specifying a crash pulse. Many computer models used to analyze occupant kinematics do not calculate both vehicle motion and occupant motion at the same time. This paper presents a framework of response surface methodology for the crash pulse prediction and vehicle structure design optimization. The process is composed of running simulation at DOE sampling data points, generating surrogate models (response surface models), performing sensitivity analysis and structure design optimization for time history data (e.g., crash pulse).

The objective of this study was to analyze available anthropomorphic test device (ATD) responses from KARCO rear impact tests and to evaluate an injury predictive model based on crash severity and occupant weight presented by Saczalski et al. (2004). The KARCO tests were carried out with various seat designs. Biomechanical responses were evaluated in speed ranges of 7-12, 13-17, 18-23 and 24-34 mph. For this analysis, all tests with matching yielding and stiff seats and matching occupant size and weight were analyzed for cases without 2nd row occupant interaction. Overall, the test data shows that conventional yielding seats provide a high degree of safety for small to large adult occupants in rear crashes; this data is also consistent with good field performance as found in NASS-CDS. Saczalski et al.'s (2004) predictive model of occupant injury is not correct as there are numerous cases from NASS-CDS that show no or minor injury in the region where serious injury is predicted.

At the Tenth ESV Conference, MVMA reported on the development of a component side impact test device developed for MVMA by MGA Research Corporation. Since that time, the test device has been modified by MGA to improve its biofidelity. Testing has shown that the modified device better meets the force-time corridors derived by MVMA from cadaver drop test data. The improved test device was used to test twelve 1985 Ford LTD doors at speeds of 25.7 and 37 km/h. The interior door surfaces were trimmed with either thin fiber board or foam padding identical to doors in vehicles tested by MVMA using NHTSA's full-vehicle test procedure. The tests showed that the MVMA device is simple to set up and run, is highly repeatable and easily discriminates between the unpadded and padded doors. A major issue for future research and development is how to select a priori a component test device impact speed which can account for differences in car size and side structure stiffness.

In the past twenty years, the explicit finite element method has been successfully employed for crash simulation. At present, crashworthiness analysis is still basically a calibration based engineering practice, but not a fully predictive process. The increasing expectations and requirements on CAE are even more challenging. To develop a predictive and reliable CAE tool, it is important to investigate the root causes that affect the numerical accuracy and the availability of the analytical method. Some of the challenging issues are discussed here from both theoretical and engineering aspects, such as convergence of explicit finite element method, locking-free shell element, analysis of material rupture, and modeling of spot weld.

This paper summarizes the rationale used to specify the geometric, inertial and impact response requirements for a small adult female dummy and a large adult male dummy with impact biofidelity and measurement capacity comparable to the Hybrid III dummy, the most advanced midsize adult male dummy. Body segment lengths and weights for these two dummies were based on the latest anthropometry studies for the extremes of the U.S.A. adult population. Other characteristic body segment dimensions were calculated from geometric and mass scaling relationships that assured that each body segment had the same mass density as the corresponding body segment of the Hybrid III dummy. The biomechanical impact response requirements for the head, neck, chest and knee of the Hybrid III dummy were scaled to give corresponding biomechanical impact response requirements for each dummy.