Tire load

Forces on rigid bodies can be considered at center of mass.
Imagine a car as a cube with unity coefficient of friction between bottom and pavement.
- a lateral force of 1G at center of mass would just begin to tip it
- but real cars with lower grip can get at least one wheel in the air
with less than 1G grip and lateral G, because not rigid bodies,
despite center of gravity being lower than half of track width.
- we want to approximate cars in sims at limits - lateral Gs can fully unload inside tires
- longitudinal Gs are less likely to fully unload front or rear tires (no wheelies)
- AccelerationSway goes positive for left turns
- AccelerationSurge goes positive for braking
Emperically, SimHub negative AccelerationHeave peaks near -25;
100 would correspond to +4G or 5G including gravity.

proxyL() as used for tire squeal volume is non linear,
but actual weight transfer should be more nearly linear,
being leverage to pivot center of gravity w.r.t more loaded tires.
Front right corner gets more load for both positive roll and pitch,
with front-rear transfer probably about 2/3 left-right; wheelbase > track,
but actual coefficients want calibration e.g. by multiple regression:

Load_fr ~ 25 + AccelerationHeave + frp * OrientationPitch + frr * OrientationRoll
Load_fl ~ 25 + AccelerationHeave + flp * OrientationPitch + flr * OrientationRoll
Load_rr ~ 25 + AccelerationHeave + rrp * OrientationPitch + rrr * OrientationRoll
Load_rl ~ 25 + AccelerationHeave + rlp * OrientationPitch + rlr * OrientationRoll

Assetto Corsa wheel load telemetry correlates well with suspension displacement
SimHub also has WheelLoad properties in ACC, but always 0...
Use AC to test wheel load proxies.
By observation, wheel suspension travel mostly follows wheel load.
AccelerationHeave + 25 approximates average load
sum (average) of suspension travel should also correlate with average load or heave
ratio of per-wheel travel / sum applied to AccelerationHeave + 25 should approximate loads..

Load modulates grip,
which enables velocity changes (surge and sway)

With actual roll and pitch influenced by center of gravity,
suspension geometry, spring and damper rates,
their correlations with suspension travels (and tire loads)
want calibrating for each vehicle.

Calibration wants multiple regression,
which will benefit from some graphical visualization.
With data available for 3D samples,
a color coded (Heat map) point cloud

- heave should correlate directly with total (4 corner) wheel load (suspension displacement)
- differences among wheel loads correlated with pitch and roll changes,
but their influence is car specific (center of gravity, roll centers, spring and damper rates
- apply multiple regression, using games with wheel load telemetry to validate regression model
- this will yield best least squares fits for 3D (heave, pitch and roll change) coefficients
- since heave directly correlates with G force, use it to calibrate pitch and roll effects
- Start by capturing and visualizing 3D point cloud of wheel loads (one corner at a time)
vs heave, changes in pitch and roll
- color code those points based on load (or suspension displacement)

Here is a web-based color coding 3D scatter plot visualizer

maintained by blekenbleu