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R-PODID

Reliable powerdown for industrial drives

Duration:
09/2023 – 08/2026
Coordinator:
University of Bologna
Acronym:
R-PODID
Project Name:
Reliable powerdown for industrial drives
Project No.:
KDT JU 101112338
Call:
HORIZON-KDT-JU-2022-2-RIA
Web:
linkedin.com/company/r-podid/

About project

The pioneering EU research project R-PODID started on the 1st of September 2023. This KDT JU co-funded project aims to develop an automated, cloudless, short-term fault-prediction for electric drives, power modules, and power devices, that can be integrated into power converters.

R-PODID OBJECTIVES:

  • Methodology for fault-prediction model generation from sparse training sets or system simulation
  • Power electronics with integrated support for embedded AI
  • 24 h fault-prediction for Gallium Nitride (GaN) and Silicon Carbide (SiC) based power converters
  • 24 h fault-prediction and fault mitigation for electric drives
  • Sensors for reliability prediction in power modules.

Supported by 33 partners, R-PODID innovations are implemented into the power modules and applied in the four use cases for conveyor belts, industrial lighting, automotive traction inverters, and a heavy-duty testbed.
IMA will contribute with the design of Identity management (IDM) for industrial sensor networks as Key management for the secure operation of the Industrial IoT (IIoT), increasing the resilience of the IIoT network by implementing appropriate communication protocols and implementing secure physical access to terminals / “edge” devices.
IMA aims to exploit R-PODIT outcomes in demonstrator installed in WITTE Automotive production site in Nejdek, CZ. The demonstrator will comprize sensor secured network including sensor data acquisition. Follow up data mining will be used to demonstare AI based SW for power converter management.


 

ACKNOWLEDGMENT: R-PODID receives funding within the Key Digital Technologies Joint Undertaking (KDT JU) – the Public-Private Partnership for research, development and innovation under Horizon Europe – and National Authorities of Italy, Turkey, Portugal, The Netherlands, Czech Republic, Latvia, Greece, Germany, Austria, and Romania under grant agreement n° 101112338.
Disclaimer: Funded by the European Union. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or the granting authority. Neither the European Union nor the granting authority can be held responsible for them.

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