Antonio Faba

Orcid: 0000-0002-4059-9869

According to our database1, Antonio Faba authored at least 12 papers between 2016 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of five.

Timeline

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Bibliography

2024
Hysteresis Modelling in Additively Manufactured FeSi Magnetic Components for Electrical Machines and Drives.
IEEE Trans. Ind. Electron., March, 2024

Design procedures for series-series wpt systems: A comparative analysis.
Comput. Electr. Eng., 2024

Novel Pulsed WPT System With Data Transfer Capability for Condition Monitoring of Industrial Rotating Equipment.
IEEE Access, 2024

2023
Experimental Measurements and Numerical Computations of a Ferromagnetic Core Made by Means of Additive Manufacturing.
Proceedings of the 20th IEEE International Conference on Smart Technologies, 2023

2021
Protection From Indirect Lightning Effects for Power Converters in Avionic Environment: Modeling and Experimental Validation.
IEEE Trans. Ind. Electron., 2021

Improved Spice Simulation of Dynamic Core Losses for Ferrites With Nonuniform Field and Its Experimental Validation.
IEEE Trans. Ind. Electron., 2021

2019
Time domain modelling of soft ferrite inductors for power converters applications.
Proceedings of the 26th IEEE International Conference on Electronics, Circuits and Systems, 2019

2018
Robust Lightning Indirect Effect Protection in Avionic Diagnostics: Combining Inductive Blocking Devices With Metal Oxide Varistors.
IEEE Trans. Ind. Electron., 2018

2017
Computer Modeling of Nickel-Iron Alloy in Power Electronics Applications.
IEEE Trans. Ind. Electron., 2017

Lightning indirect effect protection in Avionic Environment.
Proceedings of the 3rd IEEE International Forum on Research and Technologies for Society and Industry, 2017

2016
Performances prediction of inductive blocking devices for the mitigation of the lightning indirect effects.
Proceedings of the 2nd IEEE International Forum on Research and Technologies for Society and Industry Leveraging a better tomorrow, 2016

Moving vector hysteron model identification based on neural network inversion.
Proceedings of the 2nd IEEE International Forum on Research and Technologies for Society and Industry Leveraging a better tomorrow, 2016


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