Search Results

Advanced High Strength Steels (AHSS) have been implemented in the automotive industry to balance the requirements for vehicle crash safety, emissions, and fuel economy. With lower ductility compared to conventional steels, the fracture behavior of AHSS components has to be considered in vehicle crash simulations to achieve a reliable crashworthiness prediction. Without considering the fracture behavior, component fracture cannot be predicted and subsequently the crash energy absorbed by the fractured component can be over-estimated. In full vehicle simulations, failure to predict component fracture sometimes leads to less predicted intrusion. In this paper, the feasibility of using computer simulations in predicting fracture during crash deformation is studied.

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 achieve optimal axial and bending crush performance using dual phase steels for components designed for crash energy absorption and/or intrusion resistance applications, the cross sections of the components need to be optimized. In this study, Altair HyperMorph™ and HyperStudy® optimization software were used in defining the shape design variables and the optimization problem setup, and non-linear finite element code LS-DYNA® software was used in crush simulations. Correlated crash simulation models were utilized and the square cross-section was selected as the baseline. The optimized cross-sections for bending and axial crush performance resulted in significant mass and cost savings, particularly with the application of dual phase steels.

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.

There are a wide variety of approaches to model the automotive seat and occupant interaction. This paper traces the studies conducted for simulating the occupant to seat interaction in frontal and/or rear crash events. Starting with an initial MADYMO model, a MADYMO-LS/DYNA coupled model was developed. Subsequently, a full Finite Element Analysis model using LS/DYNA was studied. The main objective of the studies was to improve the accuracy and efficiency of CAE models for predicting the dummy kinematics and structural deformations at the restraint attachment locations in laboratory tests. The occupant and seat interaction was identified as one of the important factors that needed to be accurately simulated. Quasi-static and dynamic component tests were conducted to obtain the foam properties that were input into the model. Foam specimens and the test setup are discussed. Different material models in LS/DYNA were evaluated for simulating automotive seat foam.

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.

This paper reports the latest development of methodologies for testing and CAE modeling of the automobile mounts. The objective of this study is to provide dynamic mount properties for product evaluation and CAE modeling guideline for crashworthiness simulations. The methodology is divided into component, subsystem and full system levels. The study at the component level is to extract the dynamic parameters of mounts, such as stiffness and damping coefficient, based on the component tests. Furthermore, such parameters are employed to investigate the interaction between mount and connecting structures at the subsystem level. A robust connection mechanism from mount to surrounding structures is also developed during this process. Finally, the results from full vehicle system tests are compared with the CAE simulations to verify the methodology at the component and subsystem levels. A robust component test methodology is the first key element of this study.

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.

The objective of this study is to verify the performance of a target vehicle model in vehicle-to-vehicle impact applications. In some vehicle-to-vehicle tests, the target vehicle stays the same and the bullet vehicle changes from test to test depending on the programs under evaluation. To obtain reasonable crash pulse predictions in vehicle-to-vehicle impacts, it was decided to develop an accurate and robust target vehicle model first. The development of the target vehicle model was divided into two phases, rigid barrier and vehicle-to-vehicle impacts. Twelve rigid barrier tests, including full rigid barriers, angular rigid barriers, offset rigid barriers, and fixed rigid poles were adopted in the first phase of the study to calibrate the target vehicle model. The results of the study have been reported [1]. This paper focuses on the verification of vehicle-to-vehicle impacts.

The objective of this study is to develop a target vehicle model for vehicle-to-vehicle impact applications. In order to provide reasonable predictions for crash pulses in vehicle-to-vehicle impacts, an accurate and robust target vehicle model was developed first. An ideal target vehicle model should be able to provide reasonable results when hit by different bullet vehicles at different impact speeds and under different impact conditions. This was achieved by calibrating the target vehicle model against different vehicle crash tests, which include full rigid barriers, angular rigid barriers, offset rigid barriers, and fixed rigid poles. Twelve rigid barrier tests were adopted in this study to calibrate the target vehicle model. During the calibration process, some of the vehicle structures were examined and remodeled carefully for their properties and mesh quality.

Vehicle pitch and drop has become an important subject to crash analysis due to the recent FMVSS208 requirements for unbelted occupant. During frontal impact, the excessive header drop due to significant vehicle pitch and drop can induce the contact between occupant's head and sun visor. To avoid this issue, structure design for reducing vehicle pitch and drop is essential to crash safety. Historically, CAE simulation has been used in structure design during vehicle development process. Therefore, the quality of CAE modeling for replicating vehicle pitch and drop at physical test is crucial for assisting the structure design. In this paper, the most effective components in CAE model to vehicle pitch and drop have been identified and ranked by using the results of the sensitivity study. Hence the model quality can be emphasized on those major components including front horn, kick-down of front frame, body structure at upper load path, and body mounts.

The frame rail has an impact on the crash performance of body-on-frame (BOF) and uni-body vehicles. Recent developments in materials and forming technology have prompted research into improving the energy absorption and deformation mode of the frame rail design. It is worthwhile from a timing and cost standpoint to predict the behavior of the front rail in a crash situation through finite element techniques. This study focuses on improving the correlation of the frame component Finite Element model to physical test data through sensitivity analysis. The first part of the study concentrated on predicting and improving the performance of the front rail in a frontal crash [1]. However, frame rails in an offset crash or side crash undergo a large amount of bending. This paper discusses appropriate modeling and testing procedures for front rails in a bending situation.

Spot weld is the primary joining method to assemble the automotive body structure. In any crash events some separation of spot-welds can be expected. However, if this happens in critical areas of the vehicle it can potentially affect the integrity of the structure. It will be beneficial to identify such issues through CAE simulation before prototypes are built and tested. This paper reports a spot weld modeling methodology to characterize spot weld separation and its application in full vehicle crash simulation. A generalized two-node spring element with 6 DOF at each node is used to model the spot weld. Separation of spot welds is modeled using three alternative rupture criteria defined in terms of peak force, displacement and energy. Component level crash tests are conducted using VIA sled at various impact speeds to determine mean crush load and identify possible separation of welds.

The objective of this study is to evaluate the influence of the hydro-forming process and the effect of strain rate on crash performance and develop a modeling approach to improve the accuracy of crash prediction. Work hardening, thinning and strain rate effects are investigated in both component and full vehicle analyses to understand their sensitivities. Gages measured and material properties tested from post-formed tubes are compared with hydro-forming simulation results to confirm accuracy of the modeling methodology proposed in the paper. Front crash simulation using strain rate and forming effects are correlated with the test data for both component and full vehicle analyses and conclusion has been drawn from this comparison.

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.

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.

Strain rate effects have been identified as one of the most critical factors for the modeling of vehicle components in many previous investigations. The strain rate data available to the authors have been processed to obtain the input decks of a required material law in prior investigations. With the application of strain rate modeling, the strain rate database needs to be expanded. In order to continuously improve the safety CAE quality and efficiency, especially the prediction of a vehicle's pulse in a crash event, the effort has been made to include more strain rate data and extend the material database for safety CAE applications. In this study, strain rate data provided by Ispat Inland Inc. for AISI/DOE Technology Roadmap Program are processed. The material processed in this study include HSS590-CR, 440W-GA, BH300-GI, HSLA350-GI, DP600-HR, TRIP590-EG, TRIP600-CR, TRIP780-CR.