This presentation was made at NAFEMS Americas Seminar "Engineering Analysis & Simulation in the Automotive Industry: Creating the Next Generation Vehicle Accurate Modelling for Tomorrow's Technologies".

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 challenges to the automotive engineers are enormous and require a significant increase in the upfront use of numerical simulation capabilities, methods and processes such they’re able to efficiently design, manufacture and deliver these very innovative technologies to the market in greater speeds than ever before.

Resource Abstract

As companies seek to decrease cost and time to market for their products, high quality simulation has become a critical component in the early design phase. Simulation controlled through an optimization algorithm can make better use of computational resources by autonomously and intelligently guiding the engineer to solutions that meet their objectives and constraints and reveal greater understanding across the breadth of their design space. However, in many cases, multiple objectives exist and are often in conflict with each other making it difficult to determine a single optimized solution. Multi-objective optimization can be an effective strategy to solve these problems.



Much like performance metrics, product manufacturing cost is highly influenced by early design decisions and including an understanding of it during this phase provides a key opportunity to shape the product for cost effectiveness while design and manufacturing processes are still malleable. However, engineering design and simulation is often conducted well before product costing, limiting the scope of affordable design changes that can be made once costing analysis has been completed. Integrating feature based product cost models with physics-based simulation in an optimization loop provides an opportunity to drive engineering design from the cost perspective while meeting the same performance requirements.



In this presentation, we will share a multi-objective optimization for a chassis component. Evaluating both Noise, Vibration, and Harshness (NVH) performance and part cost simultaneously, the optimization will seek a solution that is both affordable and high-performing. We will present a method of integration between the part design parameters, NVH simulation, and manufacturing cost models to yield a system of optimized solutions for a cost effective part. The results of the analysis will be presented, showing a spectrum of solutions across multiple objectives from which one or more final designs could be selected.