F1 Car Stability Optimization Tool Using Telemetry Data Analysis (Focus: Ride Height & Suspension Behavior)

This paper has presented the system design and implementation of an integrated F1 Car Stability Optimization Platform built natively in Python to track ride height and suspension behaviors through data patterns. By replacing tedious manual trace scanning with automated rolling standard deviations and peak-detection threshold heuristics, the platform converts complex waveforms into direct, scannable engineering diagnostics. The IVDM layer visually locks numeric data deviations onto a 3D wireframe layout, generating an interactive communication tool that coordinates engineering metrics across track teams. The codebase achieved a complete pass verification rate across all ten functional test targets, while handling large data files of 100+ records in 4.6 seconds. The platform operates successfully as a client-side decision-support workbench, proving that highly intuitive, responsive automotive intelligence tools can be deployed efficiently without expensive industrial backend infrastructures.

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