Research database

ENTWINED - Enhanced Neural real-time digital TWIN for Electrical Drives

Duration:
24 months (2023 - 2025)
Principal investigator(s):
Project type:
Nationally funded research - PRIN
Funding body:
MINISTERO (Ministero dell'Università e della Ricerca)
Project identification number:
2022WNX4H2
PoliTo role:
Partner

Abstract

The Enhanced Neural real-time digital TWIN for Electrical Drives (ENTWINED) research project aims at developing an innovative control methodology of electrical drives and power converters based on the Digital Twin (DT) able to provides several advanced control functions, such as health monitoring, estimation of uncertainty parameters, predictive maintenance, fault detection and management. The principle of operation of ENTWINED is shown in Figure A10.1. The real-time digital model receives data from the physical system, like operating environments, functionalities, working conditions, sensor data, and so on, through communication interfaces or protocols. The real-time digital model processes these data, using also Machine learning and/or Artificial intelligence (ML/AI), to update itself in real-time and send some control commands to provide optimization and decision support for physical systems. By continuously monitoring the components in real-time, it is possible to act with a different strategy (e.g. preventive maintenance) in the event of sudden stress for the component that would lead to sudden breakage. In addition, in the perspective of pervasive use of wide bandgap power devices (Sic and Gan), the proposed approach allows operating at much higher voltages, frequencies, and temperatures than conventional. Indeed, machine learning is a very powerful tool to recognize patterns in data (e.g. anomalies) and to detect (diagnosis) and prevent (prognosis) machine faults. In this sense, periodic component checks can be avoided or reduced in frequency, which is a great advantage especially in offshore wind farms where the distance is one of the major costs. The ENTWINED methodology will be implemented and applied to a real case such as the wind offshore applications, providing the great advantage of reducing the periodic maintenance of the power conversion system. Thanks to this, periodic power converter component checks can be avoided or reduced in frequency, which is a great advantage especially in wind offshore applications where distances represent one of the major costs. The ENTWINED method can be easily applied to other sectors, such as automotive, aerospace, railway, naval, marine sectors, where the gradual evolution from hydro-pneumatic to electrical disposition of power has placed stringent requirements on the reliability of power electronic components power conversion system. The proposed project received many expressions of interests from main producers of the power modules, such as Semikron, and main companies of real-time simulator like the Hardware-In-the-Loop (HIL) producers, such as OPAL RT, Typhon and National Instruments.

People involved

Departments

Partners

  • C.N.R. - CONSIGLIO NAZIONALE DELLE RICERCHE
  • POLITECNICO DI TORINO
  • POLITECNICO DI TORINO
  • UNIVERSITA' DEGLI STUDI ROMA TRE - Coordinator

Keywords

ERC sectors

PE7_2 - Electrical engineering: power components and/or systems
PE7_3 - Simulation engineering and modelling

Sustainable Development Goals

Obiettivo 12. Garantire modelli sostenibili di produzione e di consumo

Budget

Total cost: € 246,395.00
Total contribution: € 199,900.00
PoliTo total cost: € 86,495.00
PoliTo contribution: € 60,000.00