CERN Accelerating science

Article
Title Automatic Frequency-Domain Modelling of Superconducting Magnets and its Usability to Model General Inductors
Author(s) Wolstrup, Anders Frem (Denmark, Tech. U.) ; Ravaioli, Emmanuele (CERN) ; Zsurzsan, Tiberiu Gabriel (Denmark, Tech. U.) ; Zhang, Zhe (Denmark, Tech. U.)
Publication 2021
Number of pages 7
In: IEEE Conf. ECCEAsia 2021 (2021) 1312-1318
In: 12th Energy Conversion Congress & Exposition, Online, 24 - 27 May 2021, pp.1312-1318
DOI 10.1109/ECCE-Asia49820.2021.9478990
Subject category Accelerators and Storage Rings
Abstract This paper focuses on the development of a Python dataclass and SWAN notebooks allowing for automatic generation of PSPICE© of the Large Hydron Collider (LHC) superconducting electromagnets and circuits installed at CERN. The models consist of inductors, resistors and capacitors, as well as RL-loops, modelling the behaviour of the magnets and circuits, including eddy-current effects. The dataclass can accommodate several types of magnets, and allows for custom fitting to measurements. Furthermore, the dataclass produces three different models for each magnet or circuit. The models differ in complexity trading computation time for accuracy. One of the circuit models was validated by experimental data. The dataclass was used to generate models of 37 LHC magnets and 63 circuits, as a part of the STEAM LHC circuit model library. The automatic functionality of the library provides an easy and quick way to both add and maintain the models in the library. Finally, the dataclass’ usability in regards to general inductors is assessed.
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