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

Finite element analysis has been an important part of vehicle product design. Currently in the industry multiple models of same components/assemblies are built to perform different analyses for example NVH, non-linear strength (permanent set) and fatigue. Most of the times multiple solvers are used for these different attribute models. Any design change which needs evaluation of all analyses results would then need inefficient, time-consuming and complex conversions. Additionally, the optimization process using multiple models becomes complex due to the need for synchronization of parameters, as well as need to run multiple models.



To overcome these challenges, an efficient work-flow is illustrated using a single pre-processor and a single solver. A single finite element model has been built with all the three subcases, i.e. NVH, nonlinear strength (permanent set) and fatigue, in the same model as different load-cases. This makes analysis and iteration process streamlined and efficient as no model conversion is involved. Further optimization with the required set of responses and constraints is performed.



This work-flow is demonstrated using an automotive cradle assembly, which has a set of functional requirements for dynamic stiffness, permanent set and fatigue. A finite element model is built with the load cases for NVH, non-linear strength (permanent set) and fatigue. The baseline design is evaluated for the functional requirements and found to be meeting the fatigue needs but failing for the dynamic stiffness and the permanent set criteria. Optimization is performed with thickness of the sheet metal components as design variables with constraints on damage, permanent set and the dynamic stiffness targets. The optimizer suggests an optimum design which not only meets all the performance targets but also has mass savings of 3 Kgs i.e. 6%.