A Python lap simulation and vehicle-analysis tool for FSAE EV design work. I rebuilt the core simulation in Python around a clearer module structure (vehicle, track, solver, drag, scoring).
What I built
Three lap sim tiers at different fidelity levels so the question dictates the tool: a point-mass solver for parameter sweeps (~50 ms per lap, used for sensitivity work), a 7DOF model for yaw dynamics, and an OpenLAP Python rewrite at MATLAB parity with MF5.2 tires. For the OpenLAP port I rejected automated transpilation. The pipeline runs all four FSAE dynamic events (acceleration, skidpad, autocross, endurance).
Making the model believable
I built a track-quality audit that identifies which event tracks are usable and which are misleading before they get fed into a study. Aero and tire parameters were calibrated against known references.
What the tool enabled
The pipeline supported parameter sensitivity sweeps for gear ratio and vehicle-mass studies, event-level performance comparisons, and power-limiting and endurance energy work. The gear ratio decision drew its lap-time argument from this sim.