System-level design decisions in Formula SAE (FSAE) vehicles drive all downstream subsystem designs, yet these decisions are often based on historical precedent or anecdotal evidence rather than rigorous analysis. This work presents a simulation-driven methodology to support data-informed decisions early in the design process, specifically examining how overall vehicle parameters—such as engine power, vehicle mass, aerodynamic drag and lift, wheelbase, and track width—influence performance in a representative FSAE endurance scenario.
Two types of lap-time simulation tools were used in this study: OpenLAP, a point-mass simulator, and ChassisSim, a transient 3D vehicle dynamics simulator that incorporates suspension geometry, yaw response, weight transfer, and steering effects. Initial simulations with OpenLAP were used to rapidly identify trends and guide early design decisions, while ChassisSim was used for detailed sensitivity analyses and to validate system-level trade-offs in a more realistic dynamic context.
Sensitivity results from ChassisSim revealed that vehicle mass and tire grip have the strongest influence on lap time, followed by geometric and aerodynamic parameters. While increases in engine power do contribute to faster lap times, the results indicate that performance gains are more effectively achieved by reducing vehicle mass and optimizing grip. These findings suggest that lightweight, high power-to-weight ratio powertrains that minimally compromise tire grip should be favored over maximizing engine output alone.
This work provides FSAE teams with a replicable framework for powertrain and chassis-level optimization through simulation. The approach not only enables teams to make more informed design decisions but also helps quantify trade-offs that directly affect dynamic performance, contributing to more competitive and efficient vehicle architectures. Further, this approach can be used for other applications, including commercial vehicles or aircraft, focusing on overall system parameter effects on performance criteria relative to the mobility designer.