Galetzka, Armin ; Loukrezis, Dimitrios ; De Gersem, Herbert (2024)
Data‐driven model‐free modified nodal analysis circuit solver.
In: International Journal of Numerical Modelling : Electronic Networks, Devices and Fields, 2024, 37 (2)
doi: 10.26083/tuprints-00027181
Article, Secondary publication, Publisher's Version
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Item Type: | Article |
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Type of entry: | Secondary publication |
Title: | Data‐driven model‐free modified nodal analysis circuit solver |
Language: | English |
Date: | 4 June 2024 |
Place of Publication: | Darmstadt |
Year of primary publication: | March 2024 |
Place of primary publication: | Chichester |
Publisher: | John Wiley & Sons |
Journal or Publication Title: | International Journal of Numerical Modelling : Electronic Networks, Devices and Fields |
Volume of the journal: | 37 |
Issue Number: | 2 |
Collation: | 16 Seiten |
DOI: | 10.26083/tuprints-00027181 |
Corresponding Links: | |
Origin: | Secondary publication DeepGreen |
Abstract: | This work introduces a novel data‐driven model‐free modified nodal analysis (MNA) circuit solver. The solver is capable of handling circuit problems featuring elements for which solely measurement data are available. Rather than utilizing hard‐coded phenomenological model representations, the data‐driven MNA solver reformulates the circuit problem such that the solution is found by minimizing the distance between circuit states that fulfill Kirchhoff's laws, and states belonging to the measurement data. In this way, the formerly inevitable demand for model representations is eliminated, thus avoiding the introduction of related modeling errors and uncertainties. The proposed solver is applied to linear and nonlinear RC‐circuits and to a half‐wave rectifier. |
Uncontrolled Keywords: | circuit simulation, data‐driven computing, model‐free solver, modified nodal analysis |
Identification Number: | Artikel-ID: e3205 |
Status: | Publisher's Version |
URN: | urn:nbn:de:tuda-tuprints-271810 |
Classification DDC: | 600 Technology, medicine, applied sciences > 621.3 Electrical engineering, electronics |
Divisions: | 18 Department of Electrical Engineering and Information Technology > Institute for Accelerator Science and Electromagnetic Fields Exzellenzinitiative > Graduate Schools > Graduate School of Computational Engineering (CE) |
Date Deposited: | 04 Jun 2024 12:28 |
Last Modified: | 18 Sep 2024 06:52 |
SWORD Depositor: | Deep Green |
URI: | https://tuprints.ulb.tu-darmstadt.de/id/eprint/27181 |
PPN: | 518869504 |
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