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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.

Polymeric foams are known to be sensitive to strain rate under dynamic loads. Mechanical characterization of such materials would not thus be complete without capturing the effect of strain rate on their stress-strain behaviors. Consistent data on the dynamic behavior of foam is also necessary for designing energy-absorbing countermeasures based on foam such as for vehicle occupant safety protection. Strain rates of the order of 100-500 s−1 are quite common in such design applications; strain rates of this range cannot be obtained with an ordinary UTM (universal testing machine) and a special test set-up is usually needed. In the current study, a unique approach has been suggested according to which quasi-static tests at low strain rates and low velocity drop tests at medium strain rates are utilized to arrive at an empirical relation between initial peak stress and logarithm of strain rate for a rigid closed-cell PU foam.

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.

Hat-sections, single and double, made of steel are frequently encountered in automotive body structural components. These components play a significant role in terms of impact energy absorption during vehicle crashes thereby protecting occupants of vehicles from severe injury. However, with the need for higher fuel economy and for compliance to stringent emission norms, auto manufacturers are looking for means to continually reduce vehicle body weight either by employing lighter materials like aluminum and fiber-reinforced plastics, or by using higher strength steel with reduced gages, or by combinations of these approaches. Unlike steel hat-sections which have been extensively reported in published literature, the axial crushing behavior of hat-sections made of fiber-reinforced composites may not have been adequately probed.

Natural fiber-reinforced composites are currently gaining increasing attention as potential substitutes to pervasive synthetic fiber-reinforced composites, particularly glass fiber-reinforced plastics (GFRP). The advantages of the former category of composites include (a) being conducive to occupational health and safety during fabrication of parts as well as handling as compared to GFRP, (b) economy especially when compared to carbon fiber-reinforced composites (CFRC), (c) biodegradability of fibers, and (d) aesthetic appeal. Jute fibers are especially relevant in this context as jute fabric has a consistent supply base with reliable mechanical properties. Recent studies have shown that components such as tubes and plates made of jute-polyester (JP) composites can have competitive performance under impact loading when compared with similar GFRP-based structures.

Accident statistics have shown that older and obese occupants are less adaptable to existing vehicle occupant restraint systems than ordinary middle-aged male occupants, and tend to have higher injury risk in vehicle crashes. However, the current research on injury mechanism of aging and obese occupants in vehicle frontal impacts is scarce. This paper focuses on the optimization design method of occupant restraint system parameters for specific body type characteristics. Three parameters, namely the force limit value of the force limiter in the seat belt, pretensioner preload of the seat belt and the proportionality coefficient of mass flow rate of the inflator were used for optimization. The objective was to minimize the injury risk probability subjected to constraints of occupant injury indicator values for various body regions as specified in US-NCAP frontal impact tests requirements.

Upper interior head impact safety is an important consideration in vehicle design and is covered under FMVSS 201. This standard generally requires that HIC(d) should not exceed 1000 when a legitimate target in the upper interior of a vehicle is impacted with a featureless Hybrid III headform at a velocity of 15 mph (6.7 m/s). As HIC and therefore HIC(d) is based on translational deceleration experienced at the CG of a test headform, its applicability is often doubted in protection against injury that can be caused due to rotational acceleration of head during impact. A study is carried out here using an improved lumped parameter model (LPM) representing headform impact for cases in which moderate to significant headform rotation may be present primarily due to the geometric configuration of targets.

Hat sections, single and double, made of steel are frequently encountered in automotive body structural components such as front rails, B-Pillar, and rockers of unitized-body cars. These components can play a significant role in terms of impact energy absorption during collisions thereby protecting occupants of vehicles from severe injury. Modern vehicle safety design relies heavily on computer-aided engineering particularly in the form of explicit finite element analysis tools such as LS-DYNA for virtual assessment of crash performance of a vehicle body structure. There is a great need for the analysis-based predictions to yield close correlation with test results which in turn requires well-proven modeling procedures for nonlinear material modeling with strain rate dependence, effective representation of spot welds, sufficiently refined finite element mesh, etc.

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.

Multidisciplinary Design Optimization (MDO) is of great significance in the lean design of vehicles. The present work is concerned with the objective of cross-functional optimization (i.e. MDO) of automotive body. For simplicity, the main goal adopted here is minimizing the weight of the body meeting NVH and crash safety targets. The stated goal can be achieved following either of two different ways: classic response surface method (RSM) and practical MDO methodology espoused recently. Even though RSM seems to be able to find a design point which satisfies the constraints, the problem is with the time associated with running such CAE algorithms that can provide a single optimal solution for multi-disciplinary areas such as NVH and crash safety.

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.

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.

The current paper presents improvements of a previous single-degree-of-freedom lumped parameter model with a nonlinear spring that could be used for preliminary design of headform impact safety countermeasures for normal impact with negligible headform rotation. The unloading taking place along the elastic path has been dispensed with and a parabolic unloading path may yield more realistic force-deformation and deceleration-time behaviors when compared with test results. The effects of the modified unloading behavior on HIC(d) are illustrated with examples. Additionally, a new velocity-dependent yield force criterion is adopted for the spring element to represent strain rate sensitive countermeasures. It is observed that inclusion of strain rate effect can either increase or decrease predicted HIC(d) when compared with using only quasi-static yield force.

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.

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.

Crash safety is a changing area in which safety requirements are updated or added from time to time. A relatively recent federal safety requirement is the amended FMVSS 201 rule for upper interior head impact. The automotive crash safety engineer faces many challenges in designing for this safety criterion. In the current study, it is shown how finite element-based simulation can be used as an effective tool in the design of lightweight headform impact protection countermeasures, supplemented with selective laboratory testing. Additionally, judicious employment of component finite element models and laboratory tests before a new countermeasure concept is deployed in a full vehicle environment leads to robustness and efficiency in product development.

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.

It is recognized that there is a dearth of studies that provide a comprehensive understanding of vehicle-occupant system dynamics for various road conditions, sitting occupancies and vehicle velocities. In the current work, an in-house-developed 50 degree-of-freedom (DOF) multi-occupant vehicle model is employed to obtain the vehicle and occupant biodynamic responses for various cases of vehicle velocities and road roughness. The model is solved using MATLAB scripts and library functions. Random road profiles of Classes A, B, C and D are generated based on PSDs (Power Spectral Densities) of spatial and angular frequencies given in the manual ISO 8608. A study is then performed on vehicle and occupant dynamic responses for various combinations of sitting occupancies, velocities and road profiles. The results obtained underscore the need for considering sitting occupancies in addition to velocity and road profile for assessment of ride comfort for a vehicle.