Welcome to F97.BE!
Python, Photons, and Predictions.
Wallbox
We currently own two electric vehicles, a Renault Zoe R135 since 2020 and a Tesla Model Y Long Range since 2023. In addition, I drive a Skoda Elroq 85 as my company car, which I received this year.
To monitor and manage charging across these vehicles, I replaced the previous Wallbox Home Assistant integration with a suite of self-developed Python programs. This custom system provides far greater flexibility and control over data collection, processing, and visualization.
The backend periodically polls the wall-mounted charger, processes the retrieved data, and stores it both in structured JSON format and in a local SQL server for archival and analysis. For the frontend, I use modern JavaScript libraries to render responsive, interactive charts directly in the browser. These dashboards refresh automatically at regular intervals to ensure up-to-date insights.
The entire system operates autonomously on a Raspberry Pi, making it lightweight, energy-efficient, and fully independent of any cloud services. All raw data remains within my secure environment behind a hardened firewall, where processing and storage are fully isolated from external networks. External access is strictly unidirectional: only sanitized and structured JSON payloads are transmitted outward through the firewall to a public-facing web server. This design follows data diode principles, ensuring that internal systems cannot be reached or queried from outside. The architecture aligns with best practices for critical infrastructure security and supports compliance with industry standards.
One dashboard, offering detailed real-time and historical statistics, is available here, our full charging history here