Why it matters
Without AI, inconsistent setup decisions lead to degraded balance, unpredictable aero performance, excessive wear from improper ride height, and increased risk of scrutineering failures or noncompliance during events.
From design to safety
Design
AI-guided ride height concepting
AI analyzes suspension envelopes, aero balance, and regulatory constraints to propose initial ride height targets, pushrod lengths, shim ranges, and tolerances; simulations include mass distribution and bump stop behavior across track profiles.
- front ride height sensor
- rear ride height sensor
- pushrod length adjuster
- shim stack
Build
Build-safe setup data and validation
Data build creates setup sheets, recording tolerances, shim sequences, and unit conventions; rig tests validate clearance, sensor calibrations, actuator ranges, and cross-check with aero balance targets.
- setup sheet document
- front ride height sensor
- rear ride height sensor
- shim stack
Operation
Live optimization during runs
Cumulative telemetry feeds real-time ride height, pushrod deflection, damper states, and steering feedback to adjust targets per stint, wind, and surface condition; decisions logged for post-session review.
- setup sheet document
- front ride height sensor
- rear ride height sensor
- pushrod length adjuster
Maintenance
Lifespan tracking and updates
Change logs track ride height settings, shim usage, pushrod wear, and sensor drift; maintenance planning aligns with lifed parts, inspection intervals, and spares; trend analysis guides replacement timing.
- change log records
- shim stack
- pushrod length adjuster
Safety
Safety-compliant parameter governance
All changes require sign-off by the series technical director and scrutineers; log audits ensure compliance with homologation, parc ferme rules, and emergency override procedures.
- setup sheet document
- change log records
- front ride height sensor
Part by part
- 1
front ride height sensor
- Watch for
- drift between loom readings and mechanical reference caused by sensor misalignment or mounting damage
- AI action
- flag deviation from baseline; trigger inspection and recalibration request; record sensor health in maintenance log
- 2
rear ride height sensor
- Watch for
- non-linear sensor response indicating mounting looseness or cable abrasion
- AI action
- raise alert to maintenance and propose re-calibration steps; append condition notes to change log
- 3
pushrod length adjuster
- Watch for
- excess play or mis-set length causing incorrect bump/rebound ratio
- AI action
- recommend length change within allowed range and log as setup revision; verify with rig test results
- 4
shim stack
- Watch for
- shim wear or stack misalignment that alters effective suspension height
- AI action
- update setup sheet with new shim order and verify clearance in rig test; capture shim count in inventory system
- 5
setup sheet document
- Watch for
- missing fields or inconsistent unit conventions
- AI action
- auto-fill standard sections and archive versioned sheets for traceability; enforce validation rules before release
- 6
change log records
- Watch for
- unauthorized change or missing approval trail
- AI action
- prompt for sign-off before applying to vehicle and update audit trail; mark critical changes as high priority
Worked example
Catching a shim misalignment before a practice
Illustrative scenario with sample data.
A team notices small discrepancies in front ride height during pre-practice checks; AI cross-references current setup, sensor data, and ramp tests to detect a potential shim stack shift.
Signal in
stn_id: P1, ride_height_front: 62.3 mm, ride_height_rear: 60.1 mm, pushrod_len_front: 215.4 mm, shim_thickness_front: 0.25 mm, sensor_front_status: OK, sensor_rear_status: OK, last_change: 2026-11-02
System out
alert_type: ride_height_anomaly, recommended_action: perform immediate rig test and verify shim integrity, target_front: 62.0 mm, proposed_changes: reduce shim by 0.25 mm, log_id: SHIM-2026-11-08-01
Human sign-off: Technical director reviews alert, approves shim adjustment and rig-test plan; race engineer schedules practice run with updated setup.
How to roll it out
Phase 1
Weeks 1 to 4
Baseline data capture and calibration; initial AI models learn standard ride height targets per track; data lineage established for setup sheets.
Phase 2
Weeks 5 to 8
Integrate with live telemetry; quantity and unit harmonization across sheets and logs; cross-check with wind tunnel and CFD notes.
Phase 3
Weeks 9 to 12
Full governance and scrutineering-ready change control; sign-off templates in place; audit trails linked to parc ferme and homologation records.
Where people stay in charge
- All ride height and shim changes must be approved by the technical director or series scrutineers before on-track use.
- No changes may be applied without a verifiable, signed change log entry and a corresponding rig-test confirmation.
- Critical safety changes require immediate override procedures and containment until verification by the responsible engineer.
Questions owners and crews ask
What is the purpose of AI in ride height and setup sheets?
AI correlates sensor data with suspension models to propose safe, track-appropriate ride height targets, pushrod lengths, and shim selections while maintaining log integrity and compliance.
Who must approve changes before they are used on track?
The technical director or series scrutineers must sign off changes; all modifications are recorded in the change log and setup sheets.
How often should ride height be recalibrated during a race weekend?
Recalibration occurs after major track changes, after incidents, or when sensor drift exceeds predefined thresholds; all recalibrations require sign-off and logging.
What records are kept for audit and scrutineering?
Versioned setup sheets, change logs, sensor calibration records, and rig-test results are maintained for each event and homologation cycle.