I2M Chrome: .dat format support and GPS-derived lean angle

I2M Chrome devices (Lite, Plus 2, Pro 2, DataLog Pro) are among the most popular track day loggers for motorcycles. Their native .dat format is a file containing all raw session data: GPS, analog sensors, RPM, date, rider name.

Brake Point now supports direct import of these files — no intermediate software required.

The challenge: no IMU, no lean angle?

I2M Chrome devices have no Inertial Measurement Unit (IMU). No gyroscope, no built-in accelerometer. They only have a 10 Hz GPS receiver and 8 analog inputs.

But lean angle is essential in motorcycle telemetry — it reveals corner confidence, transition phases, and how much margin you have before dragging a knee (or an elbow).

Rather than giving up, we implemented a GPS-derived lean angle calculation based on cornering physics.

The physics: steady-state cornering equilibrium

A motorcycle in a steady-state turn must lean to balance two forces:

• Gravity: F_g = m × g (vertical, downward)
• Centripetal force: F_c = m × v² / R (horizontal, toward turn center)

For the resultant to pass through the tire contact patch, equilibrium requires:

tan(θ) = v² / (R × g)

Therefore:

θ = atan(v² / (R × g))

This is the steady-state lean equation — a standard result in motorcycle dynamics (Cossalter, Motorcycle Dynamics, 2006).

Noting that lateral acceleration a_lat = v² / R, we get the simplified form:

θ = atan(a_lat / g)

From GPS to lean angle: 4 steps

We don’t have a lateral acceleration sensor, but we can derive it from GPS:

1. Heading (direction of travel)

From consecutive GPS points (lat, lon):

dlat = lat[i+1] - lat[i]
dlon = (lon[i+1] - lon[i]) × cos(lat[i])
heading = atan2(dlon, dlat)

The cos(lat) factor corrects for the convergence of meridians.

2. Yaw rate (rate of turn)

yaw_rate = Δheading / Δt   (rad/s)

With ±180° discontinuity unwrapping via atan2(sin(Δh), cos(Δh)).

3. Lateral acceleration

a_lat = v × yaw_rate   (m/s²)

This is mathematically equivalent to v² / R since yaw_rate = v / R for circular motion.

4. Lean angle

lean = atan(a_lat / g) × (180 / π)   → degrees

Signal processing

10 Hz GPS has inherent noise (±2-3 m CEP). Taking two successive derivatives (heading → yaw rate) amplifies this noise significantly. We apply:

• Smoothing: 5-sample moving average (0.5 s at 10 Hz) — a compromise between responsiveness and stability
• Clamping: ±65° — the physical limit for track motorcycles (MotoGP riders reach ~62-64° in extreme cases)

Validation

Against a demo session at Circuito de Jerez (2014):

Measurement	Value
Max left lean	-53° to -61° (fast laps)
Max right lean	+56° to +61° (fast laps)
High-speed corners	Curva Lorenzo, Dry Sac (55-60° expected on a sportbike)

These values are consistent with what you’d expect from a sportbike at track pace on these corners.

Limitations

1. Transitional lean: During rapid direction changes (chicanes), the steady-state assumption breaks down. The actual lean leads the GPS-derived value.
2. Rider position: A rider hanging off the bike reduces the actual lean needed. The GPS-derived lean reflects the equivalent lean for centripetal balance, not the physical frame angle.
3. Low speed: Below ~30 km/h, GPS position noise dominates and the derived lean angle is unreliable.
4. Camber: Track banking is not accounted for. A banked corner requires less lean than calculated.

Extracted data

I2M DAT support is experimental — here’s the summary:

Data	Source	Frequency
GPS position	Native GPS	10 Hz
GPS speed	Native GPS	10 Hz
Engine RPM	RPM sensor	100 Hz
Throttle (%)	Analog input	100 Hz
Brake (%)	Analog input	100 Hz
Lean angle (motorcycle)	GPS-derived	10 Hz
Rider name	Metadata	—

How to import

1. Download the session from your I2M device via I2M DaS
2. Go to app.brakepoint.io
3. Click Import a session and select your .dat file

See the full import guide for more details.

Your I2M device isn’t a Chrome? The .dat format is specific to Chrome and DataLog Pro devices. If you use a different I2M model, contact us — we may be able to support your format.