Spaces:
Sleeping
A newer version of the Gradio SDK is available:
6.2.0
title: Range Safe Mode Prototype
emoji: 😻
colorFrom: red
colorTo: green
sdk: gradio
sdk_version: 5.49.1
app_file: app.py
pinned: false
license: mit
short_description: Range safety calculator simulating realistic EV behaviour
Range Safe Mode Prototype
Overview
Range Safe Mode is an early functional prototype developed for Project 2 in
Design and Deployment of AI/ML Systems.
The prototype helps EV drivers quickly determine whether they have enough battery
to safely complete a trip using a simple Safe / Marginal / Unsafe indicator.
This prototype is designed to test user understanding of multi factor energy
prediction not to provide exact real world accuracy.
What the Prototype Does
The system estimates trip energy using:
- Distance (km)
- Elevation gain (m)
- Average speed (km/h)
- Temperature (°C)
Then compares the required energy against:
- Available battery (kWh)
- Reserve buffer (kWh)
The output includes:
- SAFE TO PROCEED
- MARGINALLY SAFE
- CHARGING REQUIRED
A short explanation and a confidence bar are also provided.
Why the Margin Threshold is 5 kWh
A 5 kWh safety margin was chosen for the prototype because:
- Most EVs consume 0.15–0.22 kWh per km, so 5 kWh = ~25–30 km buffer.
- It accounts for unexpected factors: sudden speed changes, weather shifts, detours.
- Many OEMs recommend keeping a 5-10% buffer for battery health and uncertainty.
- It prevents a route from being labeled “safe” when the margin is razor thin.
This number is not meant to be exact, it is a reasonable, user-friendly buffer
for a prototype that communicates the idea of confidence vs. risk.
How to Use
- Enter the battery and trip parameters.
- Click Submit.
- Read the safety classification and explanation.
- Adjust inputs to test different scenarios.
Limitations
This prototype does not include:
- Real map routing
- Live elevation APIs
- Weather or traffic data
- Battery aging / degradation
- Regenerative braking
- Real EV calibration
Energy estimates are simulation-based and meant for conceptual testing only.
Tech Stack
- Python
- Gradio UI
- Lightweight simulated EV energy model
Future Extensions
- Integrate elevation API (OpenElevation)
- Add visual "range bubble" map overlay
- Recommend fallback chargers
- Combine with team features (queue prediction, congestion forecasting)
Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference