Aprilia Engineer Optimizes MotoGP Bike Control Strategies
Elena De Cia, who leads control strategies and support data models at Aprilia Racing, explains how telemetry and sensor data guide race-weekend engineering decisions in MotoGP. She details adjustments to traction control, engine braking and torque delivery, the use of preconfigured strategy sets and machine learning for pattern detection, and the sport's gradual increase in female engineers at circuits such as Chang International Circuit, Thailand.
Key Points
- 1Leads development of control strategies using telemetry to tune traction, engine braking and torque delivery.
- 2Prepares multiple pre-race strategy sets because bikes cannot receive new software during races.
- 3Uses machine learning for large-scale pattern detection while relying on engineer judgment for interpretation.
Scoring Rationale
Provides practical engineering insights from a direct interview; limited novelty and single-source reporting reduce broader impact.
Sources
Public references used for this report.
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