Popular GitHub Repositories for Charging Stations

Chargym simulates the operation of an electric vehicle charging station (EVCS) considering random EV arrivals and departures within a day. This is a generalised environment for charging/discharging EVs under various disturbances (weather conditions, pricing models, stochastic arrival-departure EV times and stochastic Battery State of Charge (BOC) at arrival). This is an open source OpenAI Gym environment for the implementation of Reinforcement Learning (RL), Rule-based approaches (RB) and Intelligent Control (IC).

This project implements Q-Learning to find the optimal policy for charging and discharging electric vehicles in a V2G scheme under conditions of uncertain commitment of EV owners. The problem is modelled as a multi-objective multi-agent cooperative game. Project is part of fulfillment criteria for ECE 730 course at the University of Alberta.

In these notebooks the entire research and implementation process carried out for the construction of various machine learning models based on neural networks that are capable of predicting levels of solar radiation is captured given a set of historical data taken by meteorological stations.

A Comparative Study of Multi-Objective and Neuroevolutionary-based Reinforcement Learning Algorithms for Optimizing Electric Vehicle Charging and Load Management

This is the repo for my master thesis: Exploring Reinforcement Learning Solutions for EV-Aware Optimal Power Flow under Uncertainty

?? ? ? A project based in Autonomous and Intelligent Agents. This project was built using Java, JADE (JAVA Agent DEvelopment Framework) and Rapid Miner Studio. The scenario chosen for this project was to combat fires with the use of flying and terrestrial autonomous and intelligent vehicles, like trucks and airplanes. In this scenario we have, as agents, the trucks, airplanes and the headquarters (responsible for coordinating the airplanes and trucks). And also, as an environment, the fires and the water supply stations (rivers, seas, lagoons, among others). Airplanes and trucks would have limited fuel and water supply capacity.

Automate docking of robots into their charging stations using machine learning.

The EV Smart Charging Bot is a Telegram-based assistant that helps EV owners find the most cost-effective and eco-friendly charging times by analyzing real-time electricity prices and emissions. It leverages machine learning and natural language processing for personalized, intelligent recommendations.

A working proof-of-concept for drones that recharge via ambient energy and wireless checkpoints—no cables, no downtime. IX-T demonstrates sustainable autonomy through physics-backed hardware, intelligent pathing, and real-world feasibility. Built to inspire replication and progress.

This project is an AGV (Automated Guided Vehicle) path planning simulator using Pygame. Users can click on a location to set different path types (Turning, Idle, Normal, Charging), place an AGV, and move it along selected paths. The simulation runs on a clean map instead of a grid.

Desktop application showing the complete CDMX metro network and calculates the shortest route between stations with customer-server architecture

An End-to-End Machine Learning project where I predict demand of bikes at citibike stations at hourly level.

AI-powered support system for EV charging stations with LangGraph orchestration, multi-provider LLM support, and voice interface through VAPI integration for phone calling. This system allows users to check station status, reboot charging stations, and get assistance through text or voice interactions.

Smart n8n workflow for EV battery tracking with real-time voice alerts and nearby charging station suggestions.

An AI-driven Smart Mobility solution for India, providing EV trip planning, on-route charging stops, and CO2 emission savings calculations.