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Simplified load path models (SLMs) of the body in white (BIW) are an important tool in the body structure design process providing a highly flexible, idealized concept model to explore the design space through load path evaluation, material selection, and section optimization with rapid turnaround. In partnership with Altair Engineering, the C123 process was used to create and optimize SLMs for BIW models at FCA US LLC. These models help structures engineers to develop efficient load paths, sections, and joints for improved NVH as ultra-high-strength steels enable thinner gauges throughout the body structure. A few key differences in the SLM modeling method are contrasted to previous simplified BIW modeling methods. One such example is the parameterization of cross sections through response surface models rather than using contemporary finite element descriptions of arbitrary cross sections.

During the course of automobile Instrument Panel (IP) design development, the occupant head impact CAE simulation on IP are routinely performed to validate FMVSS201 requirements. Based on FMVSS201 requirements, the potential head impact zones on the IP are first identified. Then, the head impact zones are used to locate the various target points that must be impacted on IP. Once the critical target locations on IP are chosen, there are several computational steps that are required to calculate impact angles and head form (HF) center of rotation in reference to target points. Then, CAE engineer performs a repetitive process that involves positioning each individual HF with proper impact angle, assigning initial velocity to HF, and defining surface contacts within the finite element model (FEM). To simplify these lengthy manual steps, a commercially available software HyperMesh® CAE software tool is used to automate these steps. The automation scripting tool is based on TCL programming.

“Digital Prototype” simulations have been used at DaimlerChrysler to achieve vehicle level NVH objectives. The effectiveness of these simulations to guide the design when faced with vehicle parameter uncertainties is discussed. These uncertainties include, but are not limited to, material properties, material gauges, damping, structural geometry, loads, boundary conditions and weld integrity. Manufacturing and assembly processes introduce variations in the nominal values of these parameters resulting in a scatter of vehicle level NVH simulation responses. An example of a high frequency NVH concern will be studied and modified to arrive at robust design guidance when faced with uncertainty. The validity of a “deterministic digital prototype” simulation model and its relevant role as a “trend predictor” rather than “absolute predictor” tool in guiding the design is also discussed.

A process to achieve vehicle system level NVH objectives using CAE simulation tools is discussed. Issues of modeling methodology, already covered adequately in the literature, are less emphasized so that the paper can focus on the application of a process that encompasses objective setting, design synthesis, and performance achievement using simulation predictions. A reference simulation model establishes correlation levels and modeling methods that are applied to future predictions. The new model, called a “Digital Mule”, is an early new product “design intent” simulation used to arrive at subsystem goals to meet the vehicle level NVH objectives. Subsystem goals are established at discrete noise paths where structure borne noise enters the body subsystem. The process also includes setting limits on the excitation sources, such as suspension and powertrain.