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The objective of this paper focused on the modeling of an adaptive energy absorbing steering column which is the first phase of a study to develop a modeling methodology for an advanced steering wheel and column assembly. Early steering column designs often consisted of a simple long steel rod connecting the steering wheel to the steering gear box. In frontal collisions, a single-piece design steering column would often be displaced toward the driver as a result of front-end crush. Over time, engineers recognized the need to reduce the chance that a steering column would be displaced toward the driver in a frontal crash. As a result, collapsible, detachable, and other energy absorbing steering columns emerged as safer steering column designs. The safety-enhanced construction of the steering columns, whether collapsible, detachable, or other types, absorb rather than transfer frontal impact energy.

This paper presents the final phase of a study to develop the modeling methodology for an advanced steering assembly with a safety-enhanced steering wheel and an adaptive energy absorbing steering column. For passenger cars built before the 1960s, the steering column was designed to control vehicle direction with a simple rigid rod. In severe frontal crashes, this type of design would often be displaced rearward toward the driver due to front-end crush of the vehicle. Consequently, collapsible, detachable, and other energy absorbing steering columns emerged to address this type of kinematics. These safety-enhanced steering columns allow frontal impact energy to be absorbed by collapsing or breaking the steering columns, thus reducing the potential for rearward column movement in severe crashes. Recently, more advanced steering column designs have been developed that can adapt to different crash conditions including crash severity, occupant mass/size, seat position, and seatbelt usage.

Three computational gas and fluid dynamic methods, CV/UP (Control Volume/Uniform Pressure), CPM (Corpuscular Particle Method), and ALE (Arbitrary Lagrangian and Eulerian), were investigated in this research in an attempt to predict the responses of side crash pressure sensors. Acceleration-based crash sensors have been used extensively in the automotive industry to determine the restraint system firing time in the event of a vehicle crash. The prediction of acceleration-based crash pulses by using computer simulations has been very challenging due to the high frequency and noisy responses obtained from the sensors, especially those installed in crush 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 crash applications.

To evaluate vehicle crash performance in the early design stages, a reliable fracture model is needed in crash simulations to predict material fracture initiation and propagation. In this paper, a generalized incremental stress state dependent damage model (GISSMO) in LS-DYNA® was calibrated and validated for a 780-MPa third generation advanced high strength steels (AHSS), namely 780 XG3TM steel that combines high strength and ductility. The fracture locus of the 780 XG3TM steel was experimentally characterized under various stress states including uniaxial tension, shear, plane strain and equi-biaxial stretch conditions. A process to calibrate the parameters in the GISSMO model was developed and successfully applied to the 780 XG3TM steel using the fracture test data for these stress states.

Advanced high strength steels (AHSS) have been widely accepted as a material of choice in the automotive industry to balance overall vehicle weight and stringent vehicle crash test performance targets. Combined with efficient use of geometry and load paths through shape and topology optimization, AHSS has enabled vehicle manufacturers to obtain the highest possible ratings in safety evaluations by the Insurance Institute for Highway Safety (IIHS) and the National Highway Traffic Safety Administration (NHTSA). In this study, vehicle CAE side impact models were used to evaluate three side impact crash test conditions (IIHS side impact, NHTSA LINCAP and FMVSS 214 side pole) and the IIHS roof strength test condition and to identify several key components affecting the side impact test performance. HyperStudy® optimization software and LS-DYNA® nonlinear finite element software were utilized for shape and gauge optimization.

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.

The modeling of plastic fuel tank systems for crash safety applications has been very challenging. The major challenges include the prediction of fuel sloshing in high speed impact conditions, the modeling of multilayer thermoplastic fuel tanks with post-forming (non-uniform) material properties, and the modeling of tank straps with pre-tensions. Extensive studies can be found in the literature to improve the prediction of fuel sloshing. However, little research had been conducted to model the post-forming fuel tank and to address the tension between the fuel tank and the tank straps for crash safety simulations. Hoping to help improve the modeling of fuel systems, the authors made the first attempt to tackle these major challenges all at once in this study by dividing the modeling of the fuel tank into eight stages. An ALE (Arbitrary Lagrangian-Eulerian) method was adopted to simulate the interaction between the fuel and the tank.

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.

Explicit method is commonly used in crashworthiness analysis due to its capability to solve highly non-linear problems without numerous iterations and convergence problems. However, the time step for explicit methods is limited by the time that the physical wave crosses the element. Therefore, to avoid large amount of CPU time, the explicit method is usually used for non-linear dynamic problems with a short period of simulation duration. For problems under quasi-static loading conditions at pre-crash and post-crash, implicit method could be more efficient than explicit methods because the required computation time is much shorter. Due to the recent advance of crash codes, which allows both implicit and explicit computations to be performed in the same code, crash engineers are able to use explicit computation for crash simulation as well as implicit computation for some of the pre-crash quasi-static loading or post-crash spring back simulations.

Because of their excellent crash energy absorption capacity, dual phase (DP) steels are gradually replacing conventional High Strength Low Alloy (HSLA) steels for critical crash components in order to meet the more stringent vehicle crash safety regulations. To achieve optimal axial and bending crush performance using DP steels for crash components designed for crash energy absorption and/or intrusion resistance applications, the cross sections need to be optimized. Correlated crush simulation models were employed for the cross-section study. The models were developed using non-linear finite element code LS-DYNA and correlated to dynamic and quasi-static axial and bending crush tests on hexagonal and octagonal cross-sections made of DP590 steel. Several design concepts were proposed, the axial and bending crush performance in DP780 and DP980 were compared, and the potential mass savings were discussed.

Macroscopic constitutive behaviors of aluminum 5052-H38 honeycombs under dynamic inclined loads with respect to the out-of-plane direction are investigated by experiments. The results of the dynamic crush tests indicate that as the impact velocity increases, the normal crush strength increases and the shear strength remains nearly the same for a fixed ratio of the normal to shear displacement rate. The experimental results suggest that the macroscopic yield surface of the honeycomb specimens as a function of the impact velocity under the given dynamic inclined loads is not governed by the isotropic hardening rule of the classical plasticity theory. As the impact velocity increases, the shape of the macroscopic yield surface changes, or more specifically, the curvature of the yield surface increases near the pure compression state.

The forming effects along with strain rate, actual material properties and weld effects have been found to be very critical for accurate prediction of crash responses especially the prediction of local deformation. As a result, crash safety engineers started to consider these factors in crash models to improve the accuracy of CAE prediction and reduce prototype testing. The techniques needed to incorporate forming simulation results, including thickness change, residual stresses and strains, in crash models have been studied extensively and are well known in automotive CAE community. However, a challenge constantly faced by crash safety engineers is the availability of forming simulation results, which are usually supplied by groups conducting forming simulations. The forming simulation results can be obtained by either using incremental codes with actual stamping processes or one-step codes with final product information as a simplified approach.

Spot welding is the primary joining method used for the construction of the automotive body structure made of steel. A major challenge in the crash simulation today is the lack of a simple yet reliable modeling approach to characterize spot weld separation. In this paper, an attempt has been made to develop a spot weld modeling methodology to characterize spot weld separation in crash simulation. A generalized two-node spring element with 6 DOF at each node is used to characterize the spot weld nugget. To represent the connection of the nugget with the surrounding plates, tied contacts are defined between the spring element nodes and the shell elements of the plate. Three general separation criteria are proposed for the spot weld that include the effects of speed and coupled loading conditions. The separation criteria are implemented into a commercially available explicit finite element code.

The authors have proposed a new formulation to characterize the mechanical properties of spot welds under dynamic loadings including separation. In this paper, the authors primarily discuss a systematic procedure to determine the parameters of the proposed spot weld model from test data using a Design of Experiment (DOE) approach and statistical analyses. All analysis pertaining to the spot weld modeling under impact loading has been performed using RADIOSS, a commercially available explicit FE crash solver. In this study, the spot weld connection was modeled using a two-node beam-type spring element with 6 DOF at each node, and the sheet metal was modeled using a four-node shell element. The main objective was to develop a spot weld modeling methodology that is accurate and robust enough to be used in a full vehicle model which is composed of hundreds of different parts and will be crashed under different test conditions.

For a body-on-frame (BOF) vehicle, the frame is the major structural subsystem to absorb the impact energy in a frontal vehicle impact. It is also a major contributor to energy absorption in rear impact events as well. Thus, the accuracy of the finite element frame model has significant influence on the quality of the BOF vehicle impact predictability. This study presents the latest development of the frame modeling methodology on the simulation of BOF vehicle impact performance. The development is divided into subsystem (frame sled test) and full system (full vehicle test). This paper presents the first phase, subsystem testing and modeling, of the frame modeling development. Based on the major deformation modes in frontal impact, the frame is cut into several sections and put on the sled to conduct various tests. The success of the sled test highly depends on whether the sled results can replicate the deformation modes in the full vehicle.

This study focuses on the modeling of a frame in a body-on-frame (BOF) vehicle to improve the prediction of vehicle response in crashes. The study is divided into three phases - component (frame material modeling), subsystem (frame sled test) and full system (full vehicle test). In the component level, we investigate the available strain rate data, the performance of various material models in crash codes and the effect of the strain rate in crash simulation. In the subsystem phase, we incorporate the strain rate modeling and expand the scope to include both the forming and the welding effects in the subsystem CAE model to improve the correlation between CAE and test. Finally the improved frame modeling methodology with strain rate, forming and welding effects is adopted in full vehicle model. It is found that the proposed frame modeling methodology is crucial to improve the pulse prediction of a full vehicle in crashes.

This paper presents an investigation into the behavior of spot-welded steel connections based on a DOE approach. This work is a part of spot-weld modeling methodology development work being performed at Ford. Control factors such as material, coating, gage size, and noise factors such as loading direction (angle), and speed are considered in this study. Different levels of each variable are included to cover a wide range of practical applications. The test methodology used to generate the responses for the spot-weld coupons have been discussed in a companion paper [1]. From the force-displacement curves obtained from the test, the responses such as peak force, displacement at peak force, and rupture displacement are identified. These responses are then statistically analyzed to identify the relative importance and effect of the design factors. Finally, response surface models are developed to determine responses across different levels of each variable.