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Passive macromodeling via mode-revealing transformation

Abstract

Direct application of model extraction methods to tabulated admittance data often gives a model which can suffer in accuracy when applied with high-impedance terminations. The problem is relevant in situations where the admittance matrix has a large eigenvalue ratio since the small eigenvalues are likely to become corrupted. We show a modeling procedure which alleviates the accuracy problem by introducing a mode-revealing transformation which is derived from the admittance eigenvector matrix. The transformed admittance matrix is subjected to model extraction and passivity enforcement by standard techniques, leading to a model which captures the full modal information of the transformed matrix and hence that of the original matrix. Finally, the model is transformed back to the original domain. © Copyright 2012 IEEE - All rights reserved

Category

Academic chapter/article/Conference paper

Language

English

Author(s)

Affiliation

  • SINTEF Energy Research / Energisystemer

Year

2012

Publisher

IEEE Press

Book

2012 IEEE 16th Workshop on Signal and Power Integrity, May 13-16, 2012

ISBN

978-1-4673-1504-3

Page(s)

61 - 64

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