Vehicle Tradespace Analysis
Please enjoy the 2-minute summary gallery below, or scroll further to explore my work in greater detail
In addition, click the Adobe icon below to view or download my design report submission for the 2020 Formula SAE California Competition:
This entry will look different from the rest on this website, because it summarizes a group contribution project that I led. The scope of this project is much larger than the others, and the amount of detail presented is scaled down accordingly. Ultimately, this project encompasses the design ideology behind my last Clemson car, Tiger22, and is the best reflection of the vision I pursued for this team. This page will cover portions of the project that I specifically contributed to alongside portions that I simply oversaw, and I will be clear in distinguishing between the two.
This project resulted from two key objectives of my tenure as Chief Engineer. The first was to shape the team design ideology towards cohesive subsystem integration above individual subsystem optimization. For two years, I laid the foundation of this vision, investing in the simulation and modelling capacity of the team. The result was an expanded library of design tools, which we used to help quantify the effects of subsystem interactions. The final step needed was to combine these tools to re-orient design focus back to the full vehicle scope.
My second objective was to strengthen our influence and value to the community through ambitious collaborative projects with local companies and university groups. I was able to combine these goals when I met Dr. Chris Paredis, the BMW Endowed Chair of Systems Integration at the Clemson University International Center for Automotive Research (CU-ICAR). We shared a similar vision to increase the ties between Clemson's satellite graduate engineering campus and undergraduate students on the main campus.
To meet these goals, we launched a project to develop a full-vehicle tradespace analysis, using the Clemson FSAE vehicle as a case study. This was the final piece I needed to enact my team design vision. I was given $48,000 to assemble a research team for Summer 2019 at CU-ICAR, with full agency to drive the scope and vision of the project. While there, we worked closely with Dr. Paredis, as well as many of his peers and students, who provided advice and guidance throughout the project. The end product was used as the basis of development for the 2020 Clemson FSAE competition car, which was designed from a clean-slate.
The first goal of the project was to define the project objective. Many subsystem design priorities can act in contrast to each other. For example, the powertrain subsystem gains reliability from increased cooling airflow, which in turn can come at the expense of aerodynamic package performance. This defines vehicle design as a multi-objective optimization function, where it can be difficult to weigh the importance of each objective. To reduce the complexity of the problem, we simplified to a single objective: maximize the points scored in dynamic events at the Formula SAE Michigan competition. However, pure performance capacity is not enough to predict competition results, as drive-ability and reliability requirements can be equally critical. To address these requirements while maintaining the single objective strategy, we decided to define constraints that satisfy the criteria while limiting the optimization process to feasible solutions. Where applicable, supplementary simulations could be carried out alongside the optimization to further interrogate top design solutions.
The next step was to determine the scope and complexity to explore. This began with outlining critical systems affecting vehicle performance, and the parameters necessary to describe their behavior. From there, we discussed the most sensitive interactions between these systems, and the parameters necessary to quantify their effects. Starting at the most stratified, we worked to consolidate subsystems whenever possible, in order to manage the scope of the project. The final breakdown is summarized below, with four final subsystems that are joined together via a global "vehicle architecture":
Breakdown of primary vehicle subsystems and critical parameters
Our team decided to build the central tradespace project in ModeFRONTIER, a program specifically designed to carry out multi-objective optimization problems. ModeFRONTIER enables users to link several programs together, such as MATLAB and Solidworks, in a centralized environment, automating the transfer of data between them. From there users can lay out the data flow, and implement various available design exploration and optimization schemes. The team employs a wide range of models, from general MATLAB codes and Excel spreadsheets to specialized CFD and powertrain software. ModeFRONTIER allowed us to link these design tools together, so that changes in one subsystem can automatically propagate to the rest. In addition, ModeFrontier contains several visualization and post-processing tools, which we used extensively to analyze optimization results.
Example of a ModeFRONTIER workflow for a carbon monocoque design exploration, followed by a symbolic representation.
Initially, we struggled to set the scope of the project within a single optimization problem. This was a balance between detail and computational time, and we wanted to strike the right compromise between full vehicle trade offs and allowing for meaningful subsystem development as well. We ultimately decided to break the optimization problem down into four separate levels, named "Optimization Loops", each progressing up the ladder of abstraction. The first loop was the simplest and most abstract, exploring the effects of vehicle dimensions and weight characteristics on global vehicle performance: