Route Optimization for Charge-Constrained EV

Overview

This project tackles the critical issue of route optimization for electric vehicles (EVs) constrained by limited battery capacity. The algorithm is implemented on the California road network, incorporating Tesla Superchargers to ensure efficient and seamless travel.

GitHub Repository:

Charge-Constrained Route Optimization


Motivation

Electric vehicles (EVs) face unique challenges due to limited battery ranges compared to traditional combustion vehicles. When planning a road trip, especially over long distances, strategic routing through EV charging stations becomes essential to avoid being stranded. This project focuses on finding the shortest path for a charge-constrained EV, ensuring optimal stops at charging stations along the route.


Project Description

This project solves the problem of determining the most efficient route for an EV, factoring in charging constraints. By implementing a shortest-path algorithm with charge constraints, we optimize the route for reaching the destination while halting at charging points in the most efficient way possible.


Project Structure


🛠️ Tech Stack


📸 Screenshots

Geopandas Visualization

Route Visualization with Geopandas

Folium Visualization

Folium Route Visualization Optimal route with charging stations

California Road Network

Interactive UI - California Network

Toy Network

Interactive UI - Toy Network User-friendly interface for route planning


Detailed Code and Analysis

For a detailed analysis and code execution on a section of the California map, visit my GitHub Repository.