Open Source Drag Racing Physics Engine

The Physics of Faster

First-principles physics simulation for quarter-mile drag racing. Predict ET, optimize builds, and understand what actually moves the needle on the strip.

Built for the Indian drag racing community. Validated on real bikes at Aamby Valley, MMRT, and beyond.

Live Quarter-Mile Simulator

Real physics, running in the cloud. Pick a bike, adjust your setup, get your ET in under a second.

Live Quarter-Mile Simulator

First-principles RK4 physics · 15 sub-models · 1 ms timestep · updates live as you adjust

Validated on Real Data

Our 15-submodel physics engine is tested against real drag racing telemetry and dyno data.

Suzuki GSX-R 1000 K5

1000cc Superbike

Target ET

9.97s

Simulated ET

10.04s

±0.07s (0.7%)

Yamaha YZF-R1 4C8

1000cc Superbike

Target ET

10.2–10.4s

Simulated ET

~10.3s

In-range ✓

Suzuki Hayabusa Gen1

1300cc Hyperbike

Target ET

10.1–10.7s

Simulated ET

In range

Validated ✓

15 Physics Sub-Models

Engine & Drivetrain

  • 3D engine torque curves (Willans friction model)
  • Forced induction — turbo, supercharger, nitrous
  • Gear shifting and clutch engagement dynamics
  • Chain drive losses and sprocket ratios

Aerodynamics & Grip

  • Drag coefficient and frontal area per-model
  • Tire slip dynamics (Pacejka + thermal model)
  • Weight transfer and traction limits
  • Rider CoG shift and wheelie physics

Environment & Setup

  • Air density, altitude and temperature correction
  • Rolling resistance and surface grip multipliers
  • Staging, reaction time, two-step launch control
  • Wind and live weather effects

Integration & Validation

  • RK4 fixed-step integrator at 1 ms timestep
  • Adaptive step-size solver (RK45)
  • 559+ passing test cases
  • Validated against real GPS and ECU telemetry

Curated Bike Library

111

Bikes

17 manufacturers incl. KTM, Bajaj, TVS, RE

69

Tires

Pacejka + thermal model, 15 brands

70

Parts

Sprockets, exhaust, ECU flash, nitrous

12

Venues

5 Indian + 7 international strips

Run Your Own Simulation

Use the live simulator above, or install the CLI for full analysis — calibrate against your own Dragy GPS runs, import ECU logs, and predict parts ROI.

CLI & Python API

Full simulation from your terminal. Import Dragy GPS, dyno curves, and Woolich ECU logs for calibration.

pip install motoquant

REST API

POST /api/simulate with a bike config and get full time-series v(t), RPM, gear, and ET.

api.motoquant.in/docs