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Reliable Energy and Cost Efficient Traction system for Railway

Deliverables

Executive Summary of D1.4 - Demonstrators experimental and simulation results analysis

Executive summary of the confidential deliverables D14

Assessment of cosmic ray capability of SiC MOSFETS as a function of design voltage and compared to Si high voltage devices

A report based on simulation studies and experimental verification A model will be provided that describes the dependency of cosmic ray failure rate on bias level

Decision method to select the best AI analytics for effective smart maintenance

This deliverable will detail the decision model developed to help PdM analysts select the optimal portfolio of AI methods for the available KID

Development of PHM algorithms

Details on the developed algorithms and a demonstrator of the PHM solutions developed

Experimental validation of next generation dynamic WPT infrastructures

A report describing the main results gather from the experimental tests carried out in a smallscale prototype where the key challenges aspects will be evaluated

PdM economic KPI: quantitative modelling and analysis

This deliverable will detail the mathematical models developed to estimate the economic benefit of PdM for different business scenarios

Executive Summary of D1.2 - Preliminary feasibility study & performance benchmark

Executive summary of the confidential deliverables D12

Design of a full scale WPT architecture for actual city profiles

A report summarizing the main design criteria for a fullscale WPT architecture for actual city profiles

Development of Transfer Learning algorithms

This deliverable will detail the outcomes of the developed algorithms

Separation and modelling of different threshold voltage shift mechanisms

A report based on experimental studies on discrete devices traction power modules describing the observed mechanisms and providing a separation of reversible threshold voltage shift and irreversible degradation effects

Definition of quantitative metrics for assessing the performance of PdM for train traction systems

This deliverable will define the metrics to be used to evaluate the performance of PHM and PdM for train traction systems

States of the art review & KPI

A report based on public scientific and technical data containing the necessary information regarding the topics enumerated in the tasks that will guide projects developments and choices including the final studied electronic and thermal device and the KPI for the project

Publications

Generative Adversarial Networks With AdaBoost Ensemble Learning for Anomaly Detection in High-Speed Train Automatic Doors

Author(s): M. Xu, P. Baraldi, X. Lu and E. Zio
Published in: IEEE Transactions on Intelligent Transportation Systems, vol. 23, no. 12, 2022, Page(s) pp. 23408- 23421
Publisher: IEEE Transactions on Intelligent Transportation Systems, vol. 23, no. 12
DOI: 10.1109/tits.2022.3203871

Humidity Robustness of 3.3kV SiC-MOSFETs for Traction Applications – Compared to Standard Silicon IGBTs in Identical Packages

Author(s): Michael Hanf, Jan-Hendrik Peters, Felix Hoffmann, Nando Kaminski University of Bremen, IALB, Otto-Hahn-Allee
Published in: Materials Science Forum (Volume 1092), 2023, Page(s) pp.171-177
Publisher: University of Bremen, Materials Science Forum

Deep Multi-adversarial Conditional Domain Adaptation Networks for Fault Diagnostics of Industrial Equipment

Author(s): B. Wang, P. Baraldi and E. Zio,
Published in: 2022
Publisher: IEEE Transactions on Industrial Informatics
DOI: 10.1109/tii.2022.3222400

Measurement and analysis of body diode stress of 3.3 kV SiC-MOSFETs with intrinsic body diode and embedded SBD

Author(s): Geon-Hee Lee1,*, Jang-kwon Lim2, Sang-Mo Koo1, Mietek Bakowski
Published in: 2023, Page(s) pp.55-59
Publisher: ICSCRM2022, published in Materials Science Forum, Volume 1091

From the Measurement of COSS–VDS Characteristic to the Estimation of the Channel Current in Medium Voltage SiC MOSFET Power Modules

Author(s): J. Rąbkowski, M. Zdanowski, R. Kopacz, F. Gonzalez-Hernando, I. Villar and U. Larrañaga
Published in: IEEE Transactions on Instrumentation and Measurement, Issue Art no. 9003210, 2023, Page(s) vol. 72, pp. 1-10, ISSN 0018-9456
Publisher: Institute of Electrical and Electronics Engineers
DOI: 10.1109/tim.2023.3291788

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