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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.

An assessment tool was developed for rollover CAE signals evaluation to assess primarily the qualities of CAE generated sensor waveforms. This is a key tool to be used to assess CAE results as to whether they can be used for algorithm calibration and identify areas for further improvement of sensor. Currently, the method is developed using error estimates on mean, peak and standard deviation. More metrics, if necessary, can be added to the assessment tool in the future. This method has been applied to various simulated signals for laboratory-based rollover test modes with rigid-body-based MADYDO models.

Numerical analyses frequently accompany experimental investigations that study injury biomechanics and improvements in automotive safety. Limited by computational speed, earlier mathematical models tended to simplify the system under study so that a set of differential equations could be written and solved. Advances in computing technology and analysis software have enabled the development of many sophisticated models that have the potential to provide a more comprehensive understanding of human impact response, injury mechanisms, and tolerance. In this article, 50 years of publications on numerical modeling published in the Stapp Car Crash Conference Proceedings and Journal were reviewed. These models were based on: (a) author-developed equations and software, (b) public and commercially available programs to solve rigid body dynamic models (such as MVMA2D, CAL3D or ATB, and MADYMO), and (c) finite element models.

Full vehicle dynamic crash tests are commonly used in the development of rollover detection sensors, algorithms and occupant protection systems. However, many published studies have utilized component level rollover test fixtures for rollover related occupant kinematics studies and restraint system evaluation and development. A majority of these fixtures attempted to replicate only the rotational motion that occurs during the free flight phase of a typical full vehicle rollover crash test. In this paper, a description of the methods used to design a new dynamic component rollover test device is presented. A brief summary of several existing rollover component test methods is included. The new system described in this paper is capable of replicating the transfer of lateral energy into rotational vehicle motion that is present in many tripped laboratory based rollover crash tests.

State of the art electronic restraint systems rely on the acceleration measured during a vehicle crash for deployment decisions. The acceleration signal is analyzed with different criteria, among which the velocity change is a dominant criterion in almost any existing crash detection algorithm. Sensors in the front crush zone have recently been added to help develop restraint systems that comply with the new FMVSS208 and EuroNCAP regulations. Front crash sensors are usually evaluated for their velocity change during a crash and typically play a key role in the deployment decision. CAE based FEA analysis has recently been used to generate signals at the sensor module locations in crash simulations to provide supplemental information for crash sensing algorithm development and calibration. This paper presents an initial effort in developing a velocity-based crash detection algorithm, that allows broad use of CAE generated velocity time histories for system calibration.

This paper describes (1) the development of a component test methodology for testing a cooling module including radiator, condenser and trans. cooler, and (2) the associated CAE model development. A series of light truck/SUV cooling module component tests were conducted to obtain their characteristics as inputs for frontal impact and sensor modeling development. First, the cooling module component CAE sub-model was developed using soft springs along with fine-mesh sheet metal shell elements. Second, simulated sub-model results were correlated fairly well with the test data. Third, this component CAE sub-model was then incorporated into a full vehicle CAE model that was used for frontal impact (NCAP) and sensor development. Results indicated that the proposed test method for cooling module components provided consistent data and the results from cooling module sub-model can be incorporated into the full vehicle CAE model for improving the quality and accuracy of CAE models.

CAE has played a key role in development of the rollover safety technology by reducing the required number of prototypes. CAE-led Design Of Experiments (DOE) studies have helped in developing the process to minimize the number of CAE runs and to optimize use of the prototypes. This paper demonstrates the use of CAE/DOE for the design and optimization of rollover vehicle prototypes and also investigates effects of various factors in the selection of vehicle configuration for rollover sensor calibration testing. The process described herein has been successfully applied to vehicle programs. Modeling and analysis guidelines are also presented for CAE engineers to help in optimizing vehicle prototypes at program level.

The effect of epoxy-based structural foam on strength, stiffness, and energy absorption of foam filled structural components is investigated and implemented to formulate design guide-lines that can be used in enhancing weight reduction and engineering functions of systems. An experimental approach is first utilized to identify design variables such as foam density, gage, and foam layer thickness, that are needed to enhance the weight/ performance ratio of structural hat-section components. A CAE approach using non-linear, large deformation finite element analysis is used to model the hat-section components. An acceptance level of confidence in the CAE analytical tools is then established based on comparisons of results between the two approaches. Upon that, the CAE analytical tools are deployed in a sensitivity study to quantify the crush/crash characteristics of foam-filled hat-section components with respect to the changes in the afore mentioned design variables.

Head Impact Criterion (HIC) numbers obtained from interior head impact testing with the NHTSA-designed Free Motion Headform (FMH) are influenced by many variables. The high level of variability experienced in the NHTSA-proposed Interior Head Impact Test presents a challenge to today's automotive engineers. Primary contributors to HIC variability include (1) impact speed, (2) headform calibration performance, (3) design/build part variation, and (4) target point impact accuracy. This study shows that controlling these variables during testing can improve test data repeatability and reproducibility, as well as reduce design and testing time.

This paper describes the development of a three-dimensional lumped-mass structure and dummy model to study barrier-to-car side impacts. The test procedures utilized to develop model input data are also described. The model results are compared to crash test results from a series of six barrier-to-car crash tests. Sensitivity analysis using the validated model show the necessity to account for dynamic structural rate effects when using quasi-statically measured vehicle crush data.