AI based battery state-of-health-aware management operating system for micro e-mobility, e-fleet mission planning and energy back-up
Description
This project proposes the development of an innovative operating system to intelligently manage the state of charge, discharge, and health of high-efficiency batteries used in electromobility (electric vehicles, drones, etc.) and energy storage applications. The operating system’s core features include ubiquity (ability to operate across diverse battery hardware and management systems), multilevel optimization capabilities (optimizing battery cells, modules, packs, and banks in a distributed manner), and enabling interoperability between heterogeneous battery ecosystems.
The operating system will integrate low-level battery devices with high-level management algorithms and strategies for applications like microgrids, vehicle fleets, storage banks, and other distributed energy systems. It will have modules for device connectivity, task administration, optimization, control, distributed management, parameter estimation, and intelligent battery management.
Principal Researcher : Gonzalo Díaz. Participating Researchers: Jorge Silva, Alvaro Egaña, Marcos Orchard, Alejandro Ehrenfeld, Felipe Navarro, Francisco Carter, Camilo Ramirez.
Fund/Partner: Fondef Tecnologías Avanzadas 2024