Research Projects
KI4BoardNet
Next-generation distributed, continuously learning onboard power management system
Start: 12/2022
End: 11/2025
KI4BoardNet explores new concepts for resource-optimized, continuously learning, distributed power management systems. This includes methods for developing application-specific system-on-a-chip (SoC) architectures for hardware-assisted, accelerated execution of machine learning algorithms. For this purpose, a generator-based design process for RISC-V systems will be adapted to allow for flexible SoC architecture configuration and optimization.
Role of the FZI
Regarding the generated SoC platform, different adopted model architectures for AI-supported energy consumption prediction and their integration into a distributed onboard network load management will be researched. The project will also examine novel algorithms based on auction theory for resource efficiency and economical use of available energy within the board network. An important aspect of the planned system is its ability to learn continuously and thus continuously adapt to various usage scenarios.
In addition to voltage stabilization in future board networks; the research results will enable the implementation of new adaptive AI applications.
Contact person
Vice Division Manager
Division: Intelligent Systems and Production Engineering
Headquarters Karlsruhe
Research focus
Applied Artificial Intelligence
AI from research to practice: We promote applied AI for business and small and medium-sized enterprises, integrating technology with law and ethics.
Mobility and Logistics
Autonomous shuttles, intelligent logistics, and software-defined vehicles: We use IT to create the connected, safe, and sustainable mobility and logistics solutions of tomorrow.
Funding notice:
The KI4BoardNet project is funded by the Ministry of Research, Technology and Space.
Project partners: