Canopy
Lap simulation, set-up studies and model correlation, now automated with AI.
Barcelona, Spain
Motorsport Engineer & Software Developer.
Master's in Motorsport EngineeringMBA
Motorsport engineering taught me to understand the car and the driver, and software development gave me a way to build the tools a team needs rather than wait for someone else to make them. What ties the two together is the structure my master's degrees gave me for the people, the processes and the priorities behind the work, and it is in combining all three that I try to do this job as well as it can be done.
Experience
Chief Engineer at RPM in the FIA Formula Regional European Championship. Before that, race and performance engineer from Formula Renault 3.5 to FIA F3, and five years as Head of Sim Racing Engineering at Williams Esports.
Vision
Every part connected to the next.
Simulations and simulator sessions with the driver before every event.
What the driver does and what the car can deliver, worked on as one.
What comes out when driving and vehicle dynamics work together.
Every run broken down: what the car did, what the driver did, and why.
Simulation models correlated with the real car, so every prediction gets closer.
Everything connected, in a loop that starts again at every event.
Toolkit
The software behind the work, from the simulator to the pit wall.
Lap simulation, set-up studies and model correlation, now automated with AI.
Logged data from the car, analysed run by run and channel by channel.
Vehicle dynamics models, calculations and custom analysis.
Design and engineering analysis to support technical decisions.
Engineering tools, data processing and complete apps like π One.
Automating simulation work and building software faster.
Built for motorsport
Much of a race team's daily work still happens across separate tools. π One brings the utilities a team relies on into one app, to cover the gaps that cost time at every event. Designed and coded by Javier, and built to work for any team.
Set-ups, run plans, tyres, ballast and session sheets for every car, in one place.
The championship timing feed collected around the clock, cleaned and stored lap by lap.
Lap data turned into automatic, corner-by-corner coaching notes for each driver.
Telemetry shared live between the simulator and the engineers.
Canopy simulation tools, suspension calculations and a data bridge from Canopy to WinTAX.
Every session kept, comparable and ready to replay.
Travel coordination and event timetables for the whole team.
An AI assistant for the championship regulations.
Everything unified in one app. Coded by Javier, with AI to build faster.
Simulation and correlation
I built the integration that lets AI run simulations on Canopy autonomously, adjusting and correlating vehicle models automatically.
AI launches the simulation in Canopy and lines the simulated lap up against the real one: speed trace, lap time and the difference between them, metre by metre.
The model is checked against what the car really did. Aero load matches, but the g-g diagram shows the model carrying more lateral grip than the car.
The tyre's Magic Formula parameters are tuned automatically, iteration by iteration, until the lateral force curve fits the measured data.
| Parameter | Value | Change |
|---|
The adjusted model runs again. The error in the slow corner disappears, and the simulated lap now follows the real car.
Illustrative data, not team telemetry
Leadership
Good results come from teams that know how they work. Leading RPM's engineering since the team's first day, and groups of up to 15 engineers at Williams Esports, has shaped how I do it.
Shared processes and methods for the whole department, so an event runs the same way whichever engineer is on the car and nothing depends on one person's memory.
Four years teaching vehicle dynamics showed me that people perform when they understand the reasons behind a decision, so I explain the physics before I hand over the task.
Every technical decision, on and off track, has one owner. Everyone knows who decides, who gets asked and when, and the team moves faster for it.
When a task costs the team time at every event, I build the tool that takes it away, so the engineers spend their weekend on engineering.
Drivers
From rookies stepping into single-seaters to Formula 1 and IndyCar.
Teo Martín · Formula V8 3.5 · 2017
Now: five-time IndyCar champion
DR Formula · FRECA · 2021
Now: Formula 1, Audi
Pons Racing · Formula Renault 3.5 · 2015
Former Formula 1 driver
Teo Martín · Formula V8 3.5 · 2016
W Series race winner
DR Formula · FRECA · 2021
Went on to FIA Formula 3
RPM · FRECA · 2022–2023
Went on to FIA Formula 3
RPM · FRECA · 2023
Now: LMP2, European Le Mans Series
Career
Race programmes, sim racing and teaching, often running at the same time.
Background
Mechanical engineering and motorsport engineering, four years teaching vehicle dynamics, and an MBA for the management side of the job.
Barcelona, Spain
Open to conversations about race engineer and chief engineer roles.