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CAE capabilities have long been used for performing static and dynamic structural analysis during the seat design process. More recently, the soft parts of the seat including foams, trim and suspension have also been modeled with CAE. The purpose of this modeling is to better understand the physical phenomena which are involved in the sitting process, to enhance seat design knowledge, and to replace as much physical testing during the design process with virtual, CAE testing. This paper presents the first part of a multi-phased, both experimental and numerical project. The aim of this first stage is to assess the capabilities of a CAE methodology to predict FMVSS 202a backset. Based on CAD data, a finite element mesh of the seat was built. The mechanical behavior of all parts was characterized through experiments on material samples.

A fast and fully automated, Cartesian cell dominated projected mesh generation tool, that does not require a water-tight surface mesh and can handle dirty geometry without the need for CAD clean-up, is ideal for generating the fluid (air) domain mesh in the underhood region of an automobile. For simulating radiation and conduction though, it may be essential to model the solid material of the underhood components as well. Thus a multi-domain mesh is required. This paper presents an approach in which a projected mesh generation tool (CFD-VisCART) creates the fluid mesh and communicates with a conventional grid generator (CFD-GEOM), which in turn creates the solid component mesh. This approach thus tries to combine the benefits of the two vastly varying grid generation algorithms and allows the user to achieve a very short turnaround time for the underhood mesh.

The most time-consuming step in an external aerodynamics or underhood CFD process is that of generating a usable mesh from CAD data. Conventional mesh generators require a water-tight surface mesh before they can generate the volume mesh. Typical CAD surface data available for mesh generation is far from satisfactory for volume mesh creation: no node-to-node matching between mating parts, minute gaps, overlapping surfaces, overlapping parts, etc. To clean up this kind of data to a level that can be used for volume mesh creation requires a lot of manual work that could take a couple of weeks or more to accomplish. This paper presents a fast and fully automated, Cartesian cell dominated projected mesh generation algorithm used in CFD-VisCART that eliminates the need for CAD data cleaning, thus shaving off weeks worth of time off the design cycle.

To develop future electrical and autonomous cars, it is important to virtually test the car in real driving circumstances, including on wet road or under heavy rain conditions. It is especially critical to check that no water prevents the sensors of the driving assistance systems or autonomous cars from working properly, that water intrusion does not disturb electrical equipment, and that the driver’s visibility remains good under rain condition. ESI Group has introduced the Finite Point Method (FPM) in Virtual Performance Solution (VPS) as a CFD mesh free module in order to simulate the interaction of water with the car structure. It was initially specialized for tank sloshing and water drain applications for car closures and is now extended to other application fields. The objective is to enable a holistic prediction of the car behavior under realistic driving conditions, using a virtual car prototype.

Occupant head impact simulations on automotive instrument panels (IP) are routinely performed as part of an integrated design process during the course of IP development. Based on the requirements (F/CMVSS, ECE), head impact zones on the IP are first established, which are then used to determine the various “hit” locations to be tested/analyzed. Once critical impact locations are identified, CAE simulations performed which is a repetitive process that involves computing impact angles, positioning the rigid head form with an assigned initial velocity and defining suitable contacts within the finite element model. A commercially available CAE process automation tool was used to automate these steps and generate a head impact simulation model. Once the input model is checked for errors by the automated process, it can be submitted to a solver without any user intervention for analysis and report generation.

Electric vehicles are becoming a rapid growing part of the automotive scene. Batteries are considered as one of the most important and challenging components in the development of electric vehicles. The mechanical performance of the battery module is of great interest and the crashworthiness analysis of the battery module is always a critical design aspect. In crash and other severe events, the battery module is subject to impact loads from different directions. The module is designed with a capability to be deformed and collapsed in a controlled manner to mitigate safety critical damage to battery cells inside the module. In the design process, it is necessary to consider the distribution of the impact loads during the crash to minimize the local damage. In this paper, a finite element model is developed and used as an efficient simulation tool to analyze the dynamic behavior of a generic battery module upon crushing and shocking.

This paper presents an integrated simulation process which has been performed in order to assess the riding comfort performance of a vehicle seat system virtually. Present methods of seat comfort design rely on the extensive testing of numerous hardware prototypes. In order to overcome the limitations of this expensive and time-consuming process, and to fasten innovation, simulation-based design has to be used to predict the seat comfort performance very early in the seat design process, leading to a drastic reduction in the number of physical prototypes. The accurate prediction of the seat transfer function by numerical simulation requires a complete simulation chain, which takes into account the successive stages determining the final seat behaviour when submitted to vibrations. First the manufacturing stresses inside the cushion, resulting from the trimming process, are computed.