Beitrag in einem Tagungsband
Machine learning for grey box modelling of electrical components for circuit- and emc-simulation
Details zur Publikation
Autor(inn)en: | Roche, J.; Friebe, J.; Niggemann, O. |
Herausgeber: | PCIM |
Verlag: | VDE Verlag GmbH |
Verlagsort / Veröffentlichungsort: | Germany |
Publikationsjahr: | 2020 |
Seitenbereich: | 1208-1216 |
Buchtitel: | PCIM Europe digital days 2020 |
Titel der Buchreihe: | PCIM Europe Conference Proceedings |
ISBN: | 9783800752454 |
Zusammenfassung, Abstract
Models of electrical components are needed for the simulation of electrical circuits. Typically a function based on currents and voltages is the main result of these simulations. Based on the currents and voltages the EMC can be evaluated and improved systematically. Unfortunately sufficient simulation models are often not available especially when it comes to EMC behavior. Grey box learning is a promising approach to fill this gap. The development of a modelling concept is the focus of this paper.
Models of electrical components are needed for the simulation of electrical circuits. Typically a function based on currents and voltages is the main result of these simulations. Based on the currents and voltages the EMC can be evaluated and improved systematically. Unfortunately sufficient simulation models are often not available especially when it comes to EMC behavior. Grey box learning is a promising approach to fill this gap. The development of a modelling concept is the focus of this paper.
