VOLTMIND - Smart EV Charging Controller

VOLTMIND is an advanced AI controller designed to manage electric vehicle (EV) charging infrastructure efficiently. Operating as the central intelligence of the system, it orchestrates communication between the vehicle agents, the scheduling algorithms, and a large language model (Claude), ensuring optimal charging distribution based on user priority, target state of charge, and total grid capacity.

Core Architecture

The system is constructed with three primary modules:

• Vehicle Agent: Represents an individual EV connected to the system. It tracks the current battery level (State of Charge or SoC), user tier (Standard, Priority, Emergency), and the time remaining until departure.
• Scheduler Agent: Uses mathematical approximations to evaluate the collective charging requests of all connected vehicles and allocates power sequentially to prevent the grid from exceeding its maximum threshold.
• Parent AI Controller (VOLTMIND): Leverages Anthropic's Claude to dynamically reassess the schedule alongside sudden emergency overrides, ensuring real-time decision-making for load balancing and system resilience.

Features

• Dynamic Load Balancing: Monitors load continuously to keep the total system draw strictly below the available capacity, automatically throttling lower-priority sessions.
• AI-Driven Reallocation: Feeds live connection data and proposed schedules to the language model to generate robust risk assessments and precise actionable directives.
• Emergency Overrides: Supports immediate re-prioritization of vehicles, enabling ambulances or medical response units to charge at maximum capacity regardless of current grid stress.
• Dashboard Interface: Includes a sleek, modern, and highly responsive web frontend with dark-mode styling. The dashboard visualizes real-time metrics, active sessions, grid utilization arcs, and AI analytics in a single control panel.
• Fast API Backend: The core logic connects to a performant FastAPI server which acts as the intermediary between the frontend interface and the AI engine.

Installation and Execution

1. Ensure Python 3 is installed.
2. Install the required dependencies:

   pip install fastapi uvicorn anthropic python-dotenv

3. Set your Anthropic API key as an environment variable (or within the .env file) for live intelligent decision-making.
4. Run the robust FastAPI server locally:

   python -m uvicorn voltmind:app --reload --port 8000

5. Open dashboard.html in your web browser to interact with the system interface.

Technical Highlights

The implementation avoids bulky frameworks for the interface by relying on native HTML5, modern vanilla CSS with grid/flexbox layouts, and Javascript for asynchronous fetching of JSON endpoints. The Python logic applies strict type hinting, robust fallback mechanisms (defaulting to heuristic-based rule sets if the API goes offline), and clean object-oriented encapsulation for the individual agents.