OpenPyPony 🐎

Open-source automotive telemetry system for track day data logging

OpenPyPony is a low-cost, professional-grade data acquisition system built for the 2014 Ford Mustang GT "Ciara". This CircuitPython prototype validates hardware and software architecture before porting to C/C++ for production use.

Goals

• OpenSource, MIT Licsense
• Commodity hardware
• Competitive with Commercial Solutions

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Project Status: Alpha v0.1

Current Features:

• ✅ 3-axis accelerometer (LIS3DH) @ ~10Hz
• ✅ Live OLED display (128x64 SSD1306)
• ✅ SD card data logging (CSV format)
• ✅ WiFi Access Point (192.168.4.1)
• ✅ Web-based telemetry interface
• ✅ State machine task scheduler
• ✅ Buffered SD writes for performance

Planned:

• ⏳ Bluetooth OBD-II integration
• ⏳ Advanced web UI with gauges

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Hardware

Bill of Materials

• BOM File

Pinout

• Wiring table
• PICO_GPIO_TABLE File

Power Consumption

• Baseline (Accel + OLED): 20mA @ 5V
• + GPS (ATGM336H): ~140mA @ 5V (0.7W)
• + ESP-01: ~170mA @ 5V (0.8W)
• + GPS (ATGM336H) + ESP-01: ~210mA @ 5V (1.0W)

Battery Life: 8+ hours on 2000mAh USB battery pack

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Software Architecture

State Machine Scheduler

Cooperative multitasking system with independent task scheduling:

Task                 Interval    Purpose
────────────────────────────────────────────────────
Accelerometer        100ms       Read LIS3DH sensor
Display              200ms       Update OLED
SD Logger            100ms       Buffer & flush data
Status               1000ms      Console updates

Data Flow

┌─────────────┐
│   Sensors   │  (Accel, GPS, OBD-II)
└──────┬──────┘
       │
       ▼
┌─────────────┐
│ data_buffer │  (Shared dictionary)
└──────┬──────┘
       │
       ├─────────────► OLED Display (5Hz)
       ├─────────────► Web Interface (JSON API)
       └─────────────► SD Card Logger (buffered)

File Structure

OpenPyPony/
├── circuitpython        # Main Logger
│   ├── code.py		         # Main for startup
│   ├── accelerometer.py     # Accelerometer Class
│   ├── config.py            # Configurtion Class
│   ├── gps.py               # GPS Class
│   ├── hardware_setup.py    # Base Hardware Configuration Class
│   ├── neopixel_handler.py  # NeoPixel Class
│   ├── oled.py              # OLed Class
│   ├── rtc_handler.py       # RTC Class
│   ├── sdcard.py            # SD Card/Storage Class
│   ├── serial_com.py        # Serial Communications Class
│   ├── utils.py             # Utilites Class
│   └── esp-client	         # Arduino ESP-01s Webserver
├── hardware             # SCAD, and STLs
│   └── fixture.scad         # Fixture, to mount boards on
└── docs                 # Documentation
    ├── BOM.md               # Bill of Materials
    ├── WIRING.md	         # How to wire it
    └── PICO_GPIO_TABLE.md   # Table of how the GPIOs are used

Data Format

CSV Log Files: /sd/session_{value}.csv

# Driver: John
# VIN: 1ZVBP8AM5E5123456
# Start: 785
timestamp,gx,gy,gz,g_total,lat,lon,alt,speed,sats,hdop
785,-0.03,-0.01,1.05,1.05,0,0,0.0,0.0,0,0.0
785,-0.02,-0.0,1.04,1.04,0,0,0.0,0.0,0,1.4

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Getting Started

Prerequisites

• CircuitPython 10.x on Raspberry Pi Pico 2W
• Required libraries (place in lib/) CircuitPython Libraries:
  • adafruit_lis3dh
  • adafruit_gps
  • adafruit_displayio_ssd1306
  • adafruit_display_text
  • adafruit_bitmap_font
  • adafruit_displayio_ssd1306
  • neopixel
  • sdcardio (built-in)

Installation

1. Flash CircuitPython 10.x to Pico 2W
2. Copy files to CIRCUITPY drive:

   logger_refactor/*.py

3. Install required libraries in lib/
4. Insert formatted SD card (FAT32)
5. Reboot - system starts automatically

Usage

1. Power on - System initializes and starts logging
2. Connect to WiFi: SSID OpenPonyLogger, password mustanggt
3. Open browser: Navigate to http://192.168.4.1
4. View live data - Telemetry updates in real-time
5. Stop logging - Press Ctrl+C in serial console

Web Interface

Access at http://192.168.4.1 when connected to OpenPonyLogger WiFi:

• Live G-Force Display - Real-time accelerometer readings
• System Status - Uptime, memory, connection info
• API Endpoints:
  • /api/live - Current telemetry (JSON)
  • /api/status - System information (JSON)

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Performance

Measured Performance (CircuitPython Alpha):

• Accelerometer sampling: ~10Hz
• Display update: 5Hz
• SD card logging: ~10Hz (buffered, 50 samples)
• Web server: Responsive <100ms
• Total power: 62mA @ 5V

Target Performance (C/C++ Production):

• Accelerometer: 100Hz (10x faster)
• GPS: 10Hz
• OBD-II: 1-5Hz
• Dual-core: Core 0 = acquisition, Core 1 = storage/WiFi

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Development Roadmap

Phase 1: Hardware Validation (Current - CircuitPython)

• LIS3DH Accelerometer
• OLED Display
• SD Card Logging
• GPS Module
• WiFi AP + Web Server via esp-01s
• Bluetooth OBD-II (optional)

Phase 2: Integration & Testing

• Complete sensor fusion
• Extended stress testing
• Power consumption optimization
• Web UI enhancement

Phase 3: Production (C/C++ Port)

• Dual-core architecture (RP2350)
• DMA for UART/SPI
• Hardware interrupts
• GPS PPS timing (Requires Hardware Interrupts)
• Lock-free ring buffers
• Optimized for 100Hz+ sampling

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Vehicle Installation (Future)

Target Vehicle: 2014 Ford Mustang GT (S197) "Ciara"

Power Source: 12V from OBD-II port → LM2596 buck converter → 5V
Mounting: Center console, velcro-mounted enclosure
Accelerometer Position: Near vehicle center of gravity
GPS Antenna: Clear sky view (windshield mount)

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Design Philosophy

"Foundation First" - Inspired by Carroll Shelby

1. Validate in CircuitPython - Fast iteration, prove concepts
2. Measure real performance - Know actual achievable sample rates
3. Find hardware issues early - I2C conflicts, power, pinouts
4. Port to C with confidence - One clean port, not debugging hardware AND code

Cost Target: <$100 (vs $400-800 commercial units)

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Technical Details

Why CircuitPython First?

✅ Rapid prototyping (no compile/flash cycle)
✅ Rich library ecosystem (Adafruit)
✅ Easy hardware debugging
✅ Validate architecture before C port

Why Port to C/C++?

✅ 10-100x performance improvement
✅ Dual-core utilization (RP2350)
✅ DMA and hardware interrupts
✅ Sub-millisecond timing precision
✅ Professional-grade data acquisition

Communication Protocols

• I2C: LIS3DH accelerometer, OLED display
• SPI: SD card storage
• UART: GPS module (NMEA sentences)
• WiFi: Access Point + HTTP server
• Bluetooth LE: OBD-II (future)

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Contributing

This is a personal project for the 2014 Mustang GT "Ciara", but contributions welcome:

• Hardware improvements
• Code optimization
• Additional sensor support
• Post-processing tools
• Documentation improvements
• Vehicle-specific integrations

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License

MIT License - See LICENSE file

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Acknowledgments

• Adafruit - CircuitPython and hardware libraries
• Raspberry Pi Foundation - Pico 2W platform
• Carroll Shelby - "Foundation first" philosophy
• Mustang community - Inspiration and support

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Contact

Project Lead: John Orthoefer
Repository: https://github.com/John-MustangGT/OpenPyPony
Target Vehicle: 2014 Ford Mustang GT "Ciara"

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Status: Active Development | Version: 0.1.0-alpha | Last Updated: December 2024