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---
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
1. Enter the battery and trip parameters.
2. Click **Submit**.
3. Read the safety classification and explanation.
4. 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
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