A smart routing solution for electric vehicles (EVs) that ensures optimal travel planning across a road network with charging stations, while minimizing range anxiety and maximizing user satisfaction based on customizable preferences.
Electric vehicles face a unique set of challenges:
- Limited range between charges (range anxiety)
- Sparse and varied distribution of charging stations
- Need for customized planning based on:
- Vehicle model & battery capacity
- Initial charge level
- User preferences (e.g., minimal detours, maximum energy efficiency)
Existing navigation systems often overlook these critical EV-specific factors, leading to suboptimal routing decisions.
We propose a dynamic EV routing algorithm that:
- Adapts to vehicle specifications (battery size, consumption rate)
- Customizes routes based on:
- Current battery level
- User-defined source and destination
- Optimizes charging stops, ensuring:
- No overcharging or undercharging
- Balanced energy usage across the route
- Uses a pair-wise User Preference Matrix, allowing users to prioritize:
- Energy Efficiency
- Detour Minimization
- Safety Thresholds (e.g., minimum battery % between stops)
- Refueling Frequency
- Graph-based representation of road networks with:
- Roads
- Junctions
- Charging stations
- Optimal path calculation that:
- Prevents EV from running out of charge
- Maintains battery health
- Honors user-specific travel preferences
- Real-time simulation of routing with visualization
📽️ Proof of Concept (POC) video showcases:
- Interactive frontend with source/destination inputs
- Custom vehicle & battery input
- Dynamic route calculation
- Visualization of graph traversal and charging logic
- Preference matrix configuration in real-time
Check out the frontend implementation here:
🔗 EV Routing Frontend