Suspension Analyzer - Real-Time Vehicle Suspension Testing App

A professional Android application for testing and analyzing vehicle suspension performance using phone sensors with real-time 3D visualization.

Features

Core Functionality

• Real-Time 3D Car Visualization - 3D wireframe car model that moves with phone orientation
• Live G-Force Monitoring - Track lateral, longitudinal, and vertical G-forces
• Peak G-Force Tracking - Records maximum G-forces during test runs
• Sensor Calibration - Calibrate accelerometer and gyroscope for accurate readings
• Database Storage - SQLite database for vehicle profiles and test runs
• Backend API Integration - Upload test data to server for benchmarking

What's Working Now

✅ Real-time sensor data collection (accelerometer, gyroscope, magnetometer, barometer) ✅ Kalman filtering for smooth orientation tracking ✅ 3D car model with pitch, roll, yaw visualization ✅ Live G-force display with color coding ✅ Peak G-force tracking during tests ✅ Sensor calibration system ✅ Clean architecture with Room database

Project Structure

EvansApp/
├── app/
│   ├── build.gradle.kts              # App dependencies and config
│   └── src/main/
│       ├── java/com/suspension/analyzer/
│       │   ├── MainActivity.kt        # Main UI controller
│       │   ├── sensors/
│       │   │   └── SensorDataManager.kt    # Sensor fusion & data collection
│       │   ├── data/
│       │   │   └── Database.kt        # Room database schema
│       │   ├── test/
│       │   │   └── TestProtocolManager.kt  # Test protocol validation
│       │   ├── network/
│       │   │   └── NetworkClient.kt   # Backend API client
│       │   └── ui/
│       │       └── CarVisualization.kt     # 3D car renderer
│       ├── res/
│       │   ├── layout/
│       │   │   └── activity_main.xml  # Main UI layout
│       │   └── values/
│       │       ├── strings.xml
│       │       ├── colors.xml
│       │       └── themes.xml
│       └── AndroidManifest.xml
├── backend_api.py                     # Flask backend API
├── build.gradle.kts                   # Project-level build config
├── settings.gradle.kts                # Gradle settings
└── gradle.properties                  # Gradle properties

Requirements

Hardware

• Android device with:
  • Accelerometer (required)
  • Gyroscope (required)
  • Magnetometer (optional)
  • Barometer (optional)
  • Camera (for road surface photos)
  • GPS (for location data)

Software

• Android Studio Hedgehog (2023.1.1) or newer
• Android SDK 26+ (minimum)
• Android SDK 34 (target)
• Kotlin 1.9.0+
• Gradle 8.1.0+

Installation

1. Clone/Open Project

cd /Users/chadsteele/Desktop/EvansApp

2. Open in Android Studio

• File → Open → Select EvansApp folder
• Android Studio will automatically sync Gradle dependencies

3. Build the Project

./gradlew build

4. Run on Device

• Connect Android device via USB (with Developer Mode enabled)
• Click "Run" in Android Studio
• OR use command line:

./gradlew installDebug

Usage

First Time Setup

1. Launch the app
2. Grant sensor and location permissions when prompted
3. IMPORTANT: Calibrate sensors before first use:
   • Place phone on flat, stable surface
   • Click "Calibrate" button
   • Wait for calibration to complete

Running a Test

1. Mount phone securely in vehicle (dashboard or windshield mount recommended)
2. Click "Start Test" button
3. Drive the test scenario (acceleration, cornering, etc.)
4. Observe real-time 3D car orientation and G-forces
5. Click "Stop Test" when complete
6. View peak G-force results

Understanding the Display

3D Car Model

• Shows real-time orientation of your phone (and vehicle)
• Pitch: Forward/backward tilt
• Roll: Left/right tilt
• Yaw: Rotation around vertical axis

G-Force Readings

• Lateral G: Side-to-side forces (cornering)
• Longitudinal G: Forward/backward forces (acceleration/braking)
• Vertical G: Up/down forces (bumps, jumps)
• Total G: Combined magnitude

Color Coding

• Green: < 1.0 G (normal driving)
• Yellow: 1.0 - 1.5 G (spirited driving)
• Red: > 1.5 G (aggressive driving)

Backend Setup (Optional)

The app can upload test data to a backend server for benchmarking.

Running the Backend

cd /Users/chadsteele/Desktop/EvansApp
pip install -r requirements.txt
python backend_api.py

Backend will run on http://localhost:5000

Backend Endpoints

• POST /api/v1/vehicles - Register vehicle
• POST /api/v1/test-runs/submit - Submit test data
• GET /api/v1/benchmarks/compare - Get benchmark comparison
• GET /api/v1/health - Health check

Technical Details

Sensor Fusion

The app uses a Kalman filter to fuse accelerometer and gyroscope data for accurate orientation tracking:

• Process noise: 0.02
• Measurement noise: 0.01
• Update rate: ~100Hz

Coordinate System

• X-axis: Device width (left/right)
• Y-axis: Device height (up/down)
• Z-axis: Device depth (forward/back)

G-Force Calculations

lateralG = sqrt(accelX² + accelZ²) / 9.81
longitudinalG = accelY / 9.81
verticalG = accelZ / 9.81
totalG = sqrt(accelX² + accelY² + accelZ²) / 9.81

Troubleshooting

Sensors Not Working

• Ensure device has required sensors (check Settings → About Phone → Sensors)
• Grant all permissions (Location, Camera)
• Restart app

Drift in Orientation

• Recalibrate sensors (phone must be completely still)
• Check for magnetic interference (remove from metal surfaces)

Inaccurate G-Force Readings

• Calibrate before each session
• Ensure phone is rigidly mounted (no vibration)
• Avoid touching phone during test

Future Enhancements

Planned features for future versions:

• OBD-II integration for speed/RPM data
• Multiple standardized test protocols
• Photo capture of road conditions
• GPS speed tracking
• Test protocol compliance scoring
• Vehicle profile management UI
• Export test data to CSV/JSON
• Cloud sync and crowdsourced benchmarking
• Advanced analytics and graphs

Architecture

Design Patterns

• MVVM: Separation of UI and business logic
• Repository Pattern: Clean data access layer
• Singleton: Database instance management
• Observer Pattern: Sensor data callbacks

Key Components

• SensorDataManager: Hardware sensor interface with Kalman filtering
• CarVisualization: Custom View with 3D projection math
• Database: Room ORM for local persistence
• NetworkClient: Retrofit-based API client

License

Proprietary - Evans Suspension Testing Application

Credits

Developed for automotive suspension analysis and benchmarking.

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Quick Start Checklist

• Open project in Android Studio
• Sync Gradle dependencies
• Connect Android device
• Build and install app
• Grant permissions
• Calibrate sensors
• Mount phone in vehicle
• Run first test!

For issues or questions, check the troubleshooting section above.