Telemetry

This project is part of telemetry subsystem. It's goal is to store CAN data inside a database. Project is intended to be used from CLI. Database of choice for storage is InfluxDB.

Variants

Telemetry subsystems are designed to be modular in order, so it is easier to switch between variants. Each variant was developed to overcome specific race conditions and track environments.

RF

Transmission over RF using xBee was developed for BWSC 2023. It was designed to transmit data between the solar car and an escort vehicle. Transmission is done via 802.15.4 standard, which is specifically created for low power power applications. List of components:

• Nucleo STM32F103
• Digi xBee 3 802.15.4

Note 1: Current bandwidth is set to 230400bps. It is possible to increase it to 1Mbps, but at the cost of a higher power efficiency and an increase of error rate in transmission.

Note 2: Current power consumption is 0.1Wh.

Note 3: Data is received as an USART bytestream.

LTE

For iLumen European Solar Challange 2024, we developed transmission over LTE. Circuit Zolder has sufficient GSM coverage to efficiently use LTE. Binary data is transmitted from an antena located on the solar car to a server via UDP socket. List of components:

• Nucleo STM32F103
• itbrainpower u-GSM
• Digi xBee 3 Low-Power LTE

Note 1: Current bandwidth is set to 230400bps.

Note 2: Current power consumption is 0.66Wh.

Note 3: Data is received as bytes in UDP packets.

Note 4: A functional SIM card with data roaming is required.

HTTP (discontinued)

This variant was developed in an Plug'n Play style. List of components:

• Kvaser Ethercan HS
• Loco5AC

EDIT: This variant has a very large power consumption. Further development is not planned.

Note 1: Bandwidth is dynamically set by Loco5AC. Maximum throughput is 4Gbps.

Note 2: Current power consumption is 7Wh.

Note 3: Data is received in HTTP frames.

Getting started

Prerequisites:

1. Install Python 3.12
2. (Optional) Install Winows Subsytem Linux (WSL) on your host machine.
3. (Optional) Install docker.
4. (Optional) Install usbipd on your host machine.
5. (Optional) Install usbip on the WSL:

   sudo apt upgrade
   sudo apt install -y linux-tools-virtual hwdata usbip
   

Installation (Pip)

1. Clone this repository:

   git clone https://github.com/VorobiovM/telemetry_rx
   cd telemetry_rx
   

2. Create a Python virtual environment:

   python -m venv .venv
   

3. Activate Python virtual environment:
   • PowerShell: .\.venv\Scripts\Activate.ps1
   • CMD: .\.venv\Scripts\activate.bat
   • Bash: source ./.venv/bin/activate
4. Download project dependencies:

   pip install .
   

5. Run main script:

   python telemetry_rx/__main__.py --help
   

Usage

This applcation is designed to run from a command line. It expects to have a working connection to an InfluxDB server and a CAN database file (DBC). CAN database file is located in the telemetry_rx/config folder. To pass the file path use --dbc flag. To establish a connection to the Influx server, you must provide following options:

--influx-url <STR>
--influx-org <STR>
--influx-token <STR>
--influx-bucket <STR>

Note 1: InfluxDB parameters can be passed as environment variables (INFLUX_URL, INFLUX_ORG, INFLUX_TOKEN, INFLUX_BUCKET).

Note 2: InfluxDB API token must contain write permissions. It is also possible to pass token in a file using --influx-token-file <PATH>.

Listen to live traffic:

Telemetry application can collect CAN traffic coming from the solar car over USB or UDP connection. This is done via listen command. Specific connection adapter can be chosen by passing --adapter flag.

• To listen to USB traffic specify COM port via --address flag.
• To bind to a UDP server specify its address via --address flag.

Example to start USB server on COM1:

python telemetry_rx/__main__.py --dbc telemetry_rx/config/Solis-EV4.dbc listen --adapter USB --address COM1

Example to start UDP server on all interfaces:

python telemetry_rx/__main__.py --dbc telemetry_rx/config/Solis-EV4.dbc listen --adapter UDP --address 0.0.0.0

Parse offline data:

Telemetry application can also load offline data recorded to an SD card. This is done via parse command. Path to directory with offline measurements must be passed in --path flag.

Example:

python telemetry_rx/__main__.py --dbc <PATH_TO_DBC> parse --path <PATH_TO_DIR>