Balanced Truncation Model Reduction for 3D Linear Magneto-Quasistatic Field Problems

Johanna Kerler-Back () and Tatjana Stykel ()
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Johanna Kerler-Back: ESG Elektroniksystem- und Logistik-GmbH
Tatjana Stykel: Universität Augsburg, Institut für Mathematik

A chapter in Realization and Model Reduction of Dynamical Systems, 2022, pp 273-297 from Springer

Abstract: Abstract We consider linear magneto-quasistatic field equations which arise in simulation of low-frequency electromagnetic devices coupled to electrical circuits. A finite element discretization of such equations on 3D domains leads to a singular system of differential-algebraic equations. First, we study the structural properties of such a system and present a new regularization approach based on projecting out the singular state components. Furthermore, we consider a Lyapunov-based balanced truncation model reduction method which preserves stability and passivity. By making use of the underlying structure of the problem, we develop an efficient model reduction algorithm. Numerical experiments demonstrate its performance on a test example.

Keywords: Magneto-quasistatic equations; Differential-algebraic equations; Matrix pencils; Model order reduction; Balanced truncation; Stability; Passivity (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-030-95157-3_15

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DOI: 10.1007/978-3-030-95157-3_15

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