BikeControl

Ride a Van Rysel D100 smart trainer without Zwift. Load a GPX route or a synthetic waveform profile, and the app drives the trainer's resistance to match — recording power, speed and distance as you go.

See REQUIREMENTS.md for the full specification.

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Status

Component	State
crates/core — physics, profiles, GPX import, ride engine	Implemented, 103 tests
crates/ble — FTMS client for the D100	Implemented, 96 tests. Not yet wired into the app
crates/fit — FIT activity encoder	Implemented, 106 tests. Not yet wired into the app
crates/probe — hardware discovery CLI	Works against the real trainer
src-tauri + ui — desktop app	Runs on a mock rider, not the real trainer

The GUI and the trainer are both working, but not yet connected to each other — the app ticks a synthetic rider while probe talks to the real hardware. Joining them is the next step.

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Prerequisites

• Rust (built with 1.92) and cargo-tauri: cargo install tauri-cli --version '^2'
• Node 20+ and npm
• Linux: webkit2gtk-4.1, libsoup-3.0, and a running Bluetooth stack (BlueZ)

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Running the app

Standalone binary (recommended)

Embeds the frontend, so there is no dev server and nothing to go wrong:

cd src-tauri
cargo tauri build --debug --no-bundle
cd ..
./target/debug/bikecontrol-app

Open straight onto a running ride with the sample GPX loaded:

BIKECONTROL_DEMO=1 ./target/debug/bikecontrol-app

Development mode (hot reload)

cd ui && npm install     # required once — skipping this is what causes a black window
cd ../src-tauri
cargo tauri dev

If the window is black and says "Could not connect to localhost: Connection refused", the Vite dev server is not running. Either npm install was never run in ui/, or something killed the server. Use the standalone binary above, which has no dev server at all.

Keyboard

Key	Action
↑ / ↓	Gradient up/down (Shift for coarse steps)
0	Reset gradient trim to zero
Space	Pause / resume
M	Cycle control mode
L	Mark lap
P	Profile picker
[ / ]	Adjust target power or resistance
?	Help overlay

Every shortcut is mirrored by an on-screen control.

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Talking to the trainer

The probe CLI is for hardware discovery and diagnosis — it speaks to the trainer directly, independently of the app.

cargo build -p bikecontrol-probe

./target/debug/probe scan                        # find fitness machines
./target/debug/probe scan --all --secs 20        # every peripheral
./target/debug/probe inspect --name VANRYSEL     # services, characteristics, capabilities
./target/debug/probe monitor --name VANRYSEL     # live telemetry: raw hex + decoded
./target/debug/probe set --name VANRYSEL sim=4.0 # apply a target, then auto-reset

set accepts gradient=<pct>, sim=<pct>, resistance=<level> or power=<watts>, and always finishes by zeroing the gradient, dropping resistance to minimum and issuing Reset + Stop — including on Ctrl-C.

The trainer only advertises once awake. Spin the cranks for a few seconds first, or scans will find nothing.

What this trainer reports

Confirmed against the hardware:

VANRYSEL-HT-2876   DECATHLON, model 355194, firmware 0.108
  Fitness Machine Service (0x1826)
  Zwift custom service     (00000001-19ca-4651-86e5-fa29dcdd09d1)

  Accepts:  SetIndoorBikeSimulationParameters (0x11)   <-- use this for gradient
            SetTargetResistanceLevel (0x04)   range 0..100 step 1
            SetTargetPower (0x05)             range 50..600 W
  Rejects:  SetTargetInclination (0x03)       not advertised
  Notifies: Indoor Bike Data at 4 Hz

Note SetTargetInclination (0x03) is not supported, and its range characteristic reports only 0–6% with no negatives — so simulation mode is the only usable path for gradient.

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Profiles

Two kinds of ride, both in the same YAML format — see profiles/:

File	What it does
sine-overunders.yaml	Warm-up ramp, then sinusoidal power over-unders
hill-repeats.yaml	Distance-based terrain loop, repeats indefinitely
sawtooth-gradient.yaml	Gradient sawtooth, distance-based
square-resistance.yaml	Raw resistance intervals, bypassing physics

Blocks are constant, ramp, wave (sine/square/triangle/sawtooth), segments or terrain, each driving the gradient, resistance or power channel over an extent measured in seconds or metres:

name: Sine over-unders
blocks:
  - { type: ramp, channel: power, from: 100.0, to: 200.0, extent: { seconds: 600.0 } }
  - type: wave
    channel: power
    shape: sine
    midpoint: 240.0
    amplitude: 40.0
    period: { seconds: 120.0 }
    repeats: 8.0
looping: false

GPX files are imported directly — testdata/sample-climb.gpx is a 3 km climb with realistic GPS elevation noise. Raw GPS elevation is far too noisy to differentiate into gradients, so import resamples, smooths and clamps before the trainer ever sees a number.

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Development

cargo test --workspace          # 300+ tests
cargo clippy --workspace --all-targets
cd ui && npm run check          # svelte-check

The workspace is deliberately layered so most of it is testable without hardware:

crates/core     physics, profiles, GPX, ride state machine — no I/O at all
crates/ble      FTMS client; protocol logic is pure functions over bytes
crates/fit      FIT encoder; round-trip tested against an independent parser
crates/probe    hardware CLI
src-tauri       Tauri shell — owns the ride loop
ui              Svelte 5 + uPlot — renders snapshots, issues intents

crates/core/src/types.rs is the shared contract between all of them. Change it deliberately.

The app selects its data source by Cargo feature: mock-ride (default) drives a synthetic rider; real-session wraps the real ride engine and needs a live telemetry source.