This presentation was made at the NAFEMS Americas "Creating the Next Generation Vehicle" held on the 14th of November in Troy.

The automotive engineering community is now confronting the largest technology transformation since its inception. This includes the electrification of powertrains for more efficient consumption and cleaner emissions, the reinvention of the battery with fast wireless charging capabilities and finally the advent of a fully autonomous vehicle. Compounding to these technology changes, the automotive companies design verification process is moving away from a major reliance on physical testing to almost a full virtual simulation product verification process.

The automotive engineering community is now confronting the largest technology transformation since its inception. This includes the electrification of powertrains for more efficient consumption and cleaner emissions, the reinvention of the battery with fast wireless charging capabilities and finally the advent of a fully autonomous vehicle. Compounding to these technology changes, the automotive companies design verification process is moving away from a major reliance on physical testing to almost a full virtual simulation product verification process.

Resource Abstract

An automotive sheet metal structure, like a body in white, has to satisfy crashworthiness, NVH, and durability design requirements that can normally be achieved by increasing gauges of sheet parts. Such an enlargement yields a heavier structure and, consequently, higher production cost and future negative deviation from fuel economy and emissions targets.



Automotive companies use different multi-disciplinary trade-off and optimization tools to meet the design requirements, together with business and environmental objectives by reducing the structural weight. Geometry shape parameters and sheet metal gauges are used at the initial conceptual stage of the vehicle design process while only gauges are used at the final design stage. The optimization procedure has to be able to trade-off between different disciplines, objectives, and constrains, and produce acceptable optimization results in a few days or weeks. One of the most widely used optimization procedures includes direct crash, NVH, and durability simulations within Design of Experiments (DOE) tasks, approximation models generation, approximations-based optimization, and further results validation with direct simulations. This method works well for models with relatively small number of design variables due to natural limitations of the parametric optimization methods and the accuracy of the approximation models that usually deteriorates with increasing of the number of input parameters. On the other hand, non-parametric gauge optimization that derives benefit from topology optimization ideas can easily tackle sheet-metal structures made of many parts, retain accuracy of direct simulations, and simultaneously handle several load cases. However, the results of the non-parametric gauge optimization depend on the initial design shape and gauge values as the method is sensitivities driven.



The work presented herein describes and evaluates a novel optimization procedure that blends parametric and non-parametric methods available in Dassault Systèmes’ commercial software suite: Isight, TOSCA, and SFE. The procedure utilizes SFE CONCEPT technology for the structural shape modifications and finite element (FE) models generation within Isight DOE tasks and further non-parametric optimization using TOSCA Sizing methods starting from the SFE-made FE models. As such, the procedure is able to optimize gauge values of big sheet-metal structures with multiple initial designs and use of only direct simulation tools without accuracy loss due to approximations. Additional conventional approximation-based optimization steps can reduce the weight even further.