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teslamate-abrp

A slightly convoluted way of getting your vehicle data from TeslaMate to A Better Route Planner.

TeslaMate: MQTT to ABRP

A bridge to send your Tesla vehicle data from TeslaMate to A Better Route Planner (ABRP).

Features

Automatically sends MQTT TeslaMate data to A Better Route Planner
Variable (and configurable) update rates based on vehicle state (driving, charging, parked)
Secure MQTT options for authentication and (MQTT)TLS encryption
Support for Docker secrets management
Optional location anonymization
Alpha (bleeding-edge) image is available at fetzu/teslamate-abrp:alpha
Beta (pre-release) image is available at fetzu/teslamate-abrp:beta

Setup Guide

Prerequisites

A working TeslaMate instance with MQTT enabled
An ABRP user token
Docker (recommended) or Python 3.x environment

Getting an ABRP User Token

Log in to the ABRP web app or mobile app
Navigate to Settings (burger menu)
Under “Plan settings” tap/click the cog wheel of your car
Select “Edit connection”
Select “Link” in the “Generic” box under In-car live data
Token will be displayed
Save this token securely - you’ll need it to configure teslamate-abrp

Option 1: Docker Setup (Recommended)

Add the teslamate-abrp service to your existing TeslaMate docker-compose.yml:

ABRP:
  container_name: TeslaMate_ABRP
  image: fetzu/teslamate-abrp:latest
  restart: always
  environment:
    - MQTT_SERVER=mosquitto
    - USER_TOKEN=your-abrp-user-token
    - CAR_NUMBER=1
    # Optional parameters (see Configuration section)
    # - CAR_MODEL=tesla:m3:20:bt37:heatpump
    # - MQTT_USERNAME=username
    # - MQTT_PASSWORD=password
    # - MQTT_PORT=1883
    # - MQTT_TLS=True
    # - STATUS_TOPIC=teslamate-abrp
    # - SKIP_LOCATION=True
    # - TM2ABRP_DEBUG=True
    # - REFRESH_RATE_DRIVING=2.5
    # - REFRESH_RATE_CHARGING=6
    # - REFRESH_RATE_PARKED=30

Deploy the service:

docker-compose pull ABRP
docker-compose up -d ABRP

Option 2: Using Docker with Secrets (More Secure)

For improved security, use Docker secrets to manage sensitive information:

version: '3'
services:
  ABRP:
    container_name: TeslaMate_ABRP
    image: fetzu/teslamate-abrp:latest
    restart: always
    environment:
      - MQTT_SERVER=mosquitto
      - CAR_NUMBER=1
      - MQTT_USERNAME=username
      - MQTT_TLS=True
      - MQTT_PORT=8883
    secrets:
      - USER_TOKEN
      - MQTT_PASSWORD

secrets:
  USER_TOKEN:
    file: ./path/to/abrp-token.txt
  MQTT_PASSWORD:
    file: ./path/to/mqtt-password.txt

Option 3: Running as a Python Script

Clone the repository:

git clone https://github.com/fetzu/teslamate-abrp.git
cd teslamate-abrp

Install dependencies:
```
pip install -r requirements.txt
```

Run the script:

python teslamate_mqtt2abrp.py USER_TOKEN 1 mqtt-server-address

Configuration

Essential Parameters

Parameter	Description	Default	Required
USER_TOKEN	Your ABRP user token	-	Yes
CAR_NUMBER	TeslaMate car number	1	No
MQTT_SERVER	MQTT server address	-	Yes

Optional Parameters

Parameter	Description	Default	Required
CAR_MODEL	ABRP car model identifier	Auto-detected	No
MQTT_PORT	MQTT server port	1883	No
MQTT_USERNAME	MQTT username	-	No
MQTT_PASSWORD	MQTT password	-	No
MQTT_TLS	Use TLS for MQTT connection	False	No
MQTT_VERIFY_CERT	Verify the broker’s TLS certificate (only applies with MQTT_TLS). CLI: `--verify-cert`/`--no-verify-cert`. Invalid values fall back to enabled	True	No
STATUS_TOPIC	Topic to publish status messages	-	No
SKIP_LOCATION	Don’t send location data to ABRP	False	No
TM2ABRP_DEBUG	Enable debug logging	False	No
REFRESH_RATE_DRIVING	Update interval (seconds) while driving; fractional values allowed, min 1	2.5	No
REFRESH_RATE_CHARGING	Update interval (seconds) while charging	6	No
REFRESH_RATE_PARKED	Update interval (seconds) while parked/asleep	30	No
ABRP_API_KEY	Override the shared ABRP application key (env var or Docker secret). Not a per-user secret	Built-in	No

Car Model Identification

For optimal route planning, it’s recommended to manually specify your car model using the CAR_MODEL parameter. Get the correct identifier from:

https://api.iternio.com/1/tlm/get_carmodels_list

Examples:

Tesla Model 3 Long Range with Heat Pump: tesla:m3:20:bt37:heatpump
Tesla Model Y Performance: tesla:my:19:bt37:perf
Tesla Model S 100D: s100d

Troubleshooting

Check logs for connection issues:
```
docker-compose logs ABRP
```

Verify MQTT connectivity:

docker-compose exec ABRP python -c "import paho.mqtt.client as mqtt; client = mqtt.Client(); client.connect('mosquitto', 1883); print('Connected successfully')"

Common issues:
- MQTT server not reachable
- Incorrect MQTT credentials
- Invalid ABRP token
- Wrong TeslaMate car number

Advanced Usage

Customizing Update Frequencies

The application uses different update rates (in seconds) based on car state, with these defaults:

Driving: every 2.5 seconds (REFRESH_RATE_DRIVING)
Charging: every 6 seconds (REFRESH_RATE_CHARGING)
Parked/Asleep: every 30 seconds (REFRESH_RATE_PARKED)

ABRP recommends a telemetry point roughly every 5 seconds and advises against intervals longer than 30 seconds, so the defaults stay within that window. Faster driving updates (e.g. REFRESH_RATE_DRIVING=1) are supported but, per ABRP, don’t materially improve its predictions. Rates may be fractional (e.g. 2.5) but must be at least 1 second; out-of-range or invalid values fall back to the default.

These can be customized via environment variables or the equivalent CLI options (--refresh-driving, --refresh-charging, --refresh-parked). Any value left unset falls back to the default above. Values must be whole positive seconds; invalid values are ignored (with a warning) and the default is used instead.

For example, to make driving updates less aggressive:

environment:
  - REFRESH_RATE_DRIVING=5

Credits

Based on letienne’s original code, with improvements by various contributors (see commit history).

License

Licensed under the MIT license.