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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.

A dynamic component test methodology using a door sub-system was developed to simulate the outside door handle/latch responses (accelerations and deformations) as in a full-vehicle NHTSA FMVSS 214 side impact test. The test methodology consists of a door sub-system (with door inner components) which is allowed to pivot by means of a hinge at the top of the door. The lateral structural load path affecting the door/rocker response was accounted and simulated (obtained from full-vehicle FE analysis) in this methodology by means of an energy absorbing material (Aluminum honeycomb) of predetermined stiffness. A bullet sled simulating the Moving Deformable Barrier (MDB) surface and stiffness at the same relative location to the door/rocker (as in full-vehicle test) strikes the stationary hinged door at an initial velocity of approx. 30 mph (longitudinal component of crab cart velocity of 33.5 mph).

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.

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.