In this paper, we present a new effective methodology to build stochastic macromodels for the time-domain analysis of generic linear multiport systems. The proposed technique allows one to calculate a stable and passive polynomial chaos (PC)-based macromodel of a system under stochastic variations. The Galerkin projections method and a PC-based model of the system scattering parameters are used along with the Vector Fitting algorithm, leading to an accurate and efficient description of the system variability features. The proposed technique results to be very versatile and, thus, is well suited to be applied to many different and complex modern electrical systems (e.g., interconnections and filters). The accuracy and computational efficiency of the proposed technique are verified through comparison with the standard Monte Carlo analysis for two pertinent numerical examples, showing a maximum simulation speedup of 765 times.

Polynomial Chaos-Based Macromodeling of General Linear Multiport Systems for Time-Domain Analysis

ANTONINI, GIULIO
2017-01-01

Abstract

In this paper, we present a new effective methodology to build stochastic macromodels for the time-domain analysis of generic linear multiport systems. The proposed technique allows one to calculate a stable and passive polynomial chaos (PC)-based macromodel of a system under stochastic variations. The Galerkin projections method and a PC-based model of the system scattering parameters are used along with the Vector Fitting algorithm, leading to an accurate and efficient description of the system variability features. The proposed technique results to be very versatile and, thus, is well suited to be applied to many different and complex modern electrical systems (e.g., interconnections and filters). The accuracy and computational efficiency of the proposed technique are verified through comparison with the standard Monte Carlo analysis for two pertinent numerical examples, showing a maximum simulation speedup of 765 times.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11697/116746
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