Vehicle Dynamics: Automated Aero Optimizer Algorithm

This paper outlines the mathematical framework for the GTEC Aero Optimizer. Unlike standard static mapping, this algorithm acts as an automated Lap Time Simulator (LTS), dynamically scanning telemetry to diagnose aerodynamic instability and prescribing precise, whole-number setup adjustments.

Phase 1: Instability Event Detection (The Triggers)

The algorithm scans the telemetry array to isolate specific moments of grip loss. We detect these events by looking for mathematical anomalies in tire thermodynamics and lateral acceleration.

Condition A: Sudden Grip Loss (Friction Circle Exceeded)

\[ \sqrt{G_{lat}^2 + G_{long}^2} < G_{max} \quad \text{AND} \quad \left| \frac{d(\text{Steering})}{dt} \right| > \text{Threshold} \]

Condition B: Thermal Spike

\[ \frac{d(T_{surface})}{dt} > T_{critical\_rate} \]

If the driver adds steering input but lateral G-force drops or remains flat, the tire has exceeded its slip angle peak. If this coincides with a rapid spike in surface temperature, an Instability Event is flagged.

Phase 2: Aerodynamic Correlation (The Diagnosis)

Once an event is flagged, the algorithm analyzes a 100-meter window prior to the event to determine if the slip was caused by mechanical failure or an aerodynamic platform shift (e.g., massive pitch under braking).

Aero Balance Shift Rate:

\[ \Delta AB = \left| \frac{d}{dt} \left( \frac{F_{aero\_front}}{F_{aero\_total}} \right) \right| \]

If \(\Delta AB\) is exceptionally high during the lead-up to the slip event, we confirm the root cause: The aerodynamic Center of Pressure (CoP) moved too aggressively, starving one axle of vertical load.

Phase 3: Survival Load & Downforce Deficit

To cure the instability, we must calculate the exact amount of downforce the slipping tire needed to survive the corner. By utilizing the tire's coefficient of friction (\(\mu\)), we can reverse-engineer the required vertical load (\(F_{z, req}\)).

Required Vertical Load:

\[ F_{z, req} = \frac{Mass \cdot \sqrt{G_{lat}^2 + G_{long}^2}}{\mu} \]

Downforce Deficit:

\[ \Delta F_{z} = F_{z, req} - F_{z, actual} \]

The Deficit (\(\Delta F_z\)) represents the missing downforce (in Newtons) that caused the car to break traction.

Phase 4: Wing Click Translation & Global Aggregation

Because iRacing hides exact lift coefficients, we utilize an Empirical Sensitivity Multiplier. We map the Downforce Deficit into "Wing Clicks" based on the velocity of the car at the moment of instability.

Required Clicks for Event \(i\):

\[ Clicks_i = \frac{\Delta F_{z, i}}{\Delta F_{click}(v_i)} \]

Where \(\Delta F_{click}(v_i)\) is the empirically derived downforce added per wing click at that specific speed.

Finally, the algorithm aggregates all \(N\) detected events across the entire stint to find the global optimum setup change, preventing a fix in Turn 1 from ruining the car in Turn 8.

Optimal Setup Adjustment:

\[ \text{Recommended Clicks} = \text{Round}\left( \frac{1}{N} \sum_{i=1}^{N} Clicks_i \right) \]

Generated by GTEC Analyst for LibreOffice/Word compatibility. Designed for native iRacing (.ibt) telemetry architecture.