Andrea Zilio

Andrea Zilio (Student Member, IEEE) received the B.S. and M.S. (with honors) degrees in mechatronics engineering from the University of Padova, Vicenza, Italy, in 2018 and 2020, respectively.

He is currently working toward the Ph.D. degree in Mechatronics at the Department of Management and Engineering (DTG).

His research interests are oriented to the applications of artificial intelligence in power electronics for dynamic black-box modeling and optimization of power converters.

Publications

On the Design of NARX-ANNs for the Black-Box Modeling of Power Electronic Converters
- Andrea Zilio, Filippo Dalla Zuanna, Davide Biadene, Tommaso Caldognetto, Paolo Mattavelli
- 2023 IEEE Energy Conversion Congress and Exposition (ECCE) (29 Oct.-2 Nov. 2023)
- doi: 10.1109/ECCE53617.2023.10362162
A Multiport Converter for Flexible Active Balancing in Li-Ion Batteries
- Andrea Zilio, Davide Fogagnolo, Ezio Gallo, Davide Biadene, Paolo Mattavelli
- IEEE Transactions on Industrial Electronics (July 2024)
- doi: 10.1109/TIE.2023.3314869
Lifetime Prediction in Power Semiconductor Devices: A Comparative study between Analytical Modeling and Artificial Neural Network
- Alessandro Vaccaro, Andrea Zilio, Paolo Magnone
- 2023 IEEE Applied Power Electronics Conference and Exposition (APEC) (19-23 March 2023)
- doi: 10.1109/APEC43580.2023.10131380
Modeling Non-Linearities of Power Electronic Converters Using Artificial Neural Networks
- Andrea Zilio, Davide Biadene, Tommaso Caldognetto, Paolo Mattavelli
- 2023 IEEE Applied Power Electronics Conference and Exposition (APEC) (19-23 March 2023)
- doi: 10.1109/APEC43580.2023.10131637
Optimization Approaches for RMS Current Reduction of Triple Active Bridge Converters
- Ahmed A. Ibrahim, Andrea Zilio, Davide Biadene, Tommaso Caldognetto, Paolo Mattavelli
- 2023 IEEE Conference on Power Electronics and Renewable Energy (CPERE) (19-21 Feb. 2023)
- doi: 10.1109/CPERE56564.2023.10119543
Black-Box Large-Signal Average Modeling of DC-DC Converters Using NARX-ANNs
- Andrea Zilio, Davide Biadene, Tommaso Caldognetto, Paolo Mattavelli
- IEEE Access (2023)
- doi: 10.1109/ACCESS.2023.3271731
Optimal Modulation of Triple Active Bridge Converters by an Artificial-Neural- Network Approach
- Ahmed A. Ibrahim, Andrea Zilio, Tarek Younis, Davide Biadene, Tommaso Caldognetto, Paolo Mattavelli
- IEEE Transactions on Industrial Electronics (March 2024)
- doi: 10.1109/TIE.2023.3270529
Artificial Neural Networks Approach for Reduced RMS Currents in Triple Active Bridge Converters
- Ahmed A. Ibrahim, Andrea Zilio, Tarek Younis, Davide Biadene, Tommaso Caldognetto, Paolo Mattavelli
- IECON 2022 – 48th Annual Conference of the IEEE Industrial Electronics Society (17-20 Oct. 2022)
- doi: 10.1109/IECON49645.2022.9968804
Predicting Lifetime of Semiconductor Power Devices Under Power Cycling Stress Using Artificial Neural Network
- Alessandro Vaccaro, Paolo Magnone, Andrea Zilio, Paolo Mattavelli
- IEEE Journal of Emerging and Selected Topics in Power Electronics (Dec. 2023)
- doi: 10.1109/JESTPE.2022.3194189
A flexible Multi-Active Half-Bridge converter for active balancing of series-connected Li-Ion cells
- Andrea Zilio, Paolo Mattavelli
- IECON 2021 – 47th Annual Conference of the IEEE Industrial Electronics Society (13-16 Oct. 2021)
- doi: 10.1109/IECON48115.2021.9589854
An experimental validation of the adoption of dc-dc converters for the impedance measurement in Li-Ion batteries
- Andrea Zilio, Paolo Mattavelli
- 2021 IEEE International Conference on Environment and Electrical Engineering and 2021 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe) (7-10 Sept. 2021)
- doi: 10.1109/EEEIC/ICPSEurope51590.2021.9584622