Formula Student Data Analysis

Context: FSAE & LHR Combustion

Longhorn Racing Combustion is UT Austin's Formula SAE combustion team. My work there has mostly been on simulation and data tasks that help the team compare design tradeoffs with something more defensible than "this probably feels faster."

Related public repo: limited-slip differential model ↗

Simulation: Lap Time Sensitivity

The plot above is a lap-time sensitivity study we used to reason about broad setup and design tradeoffs.

• What it varies: coefficient of drag, added vehicle mass, and the resulting simulated lap time.
• Why it matters: aero can improve cornering performance, but it usually brings both drag and weight penalties.
• What we learned: under some event assumptions, extra mass hurt enough that lightweighting mattered more than chasing a more aggressive aero package.

Data Engineering & Pipeline Development

Outside the headline plots, a lot of the work was quieter data cleanup and tooling so the simulation stack was easier for the team to use and trust.

• Damper curve processing: I wrote code to clean and interpolate shock dyno force-velocity data so it could be used more directly in vehicle simulations.
• Dyno and ECU data handling: I also worked on parsing and organizing Haltech logs so engine data was easier to inspect and reuse.

Technologies Used