Abstract

Partial element equivalent circuit (PEEC) model has attracted great interests to overcome challenges in the power integrity analysis. However, the increasing miniaturization in electronics makes the uncertainty effect an ever more central issue to accurately estimate the inductance in the power distribution networks (PDNs) of high-speed PCBs. In this paper, we propose a stochastic partial inductance modeling approach to quantify the stochastic inductance. Specifically, the deterministic partial inductance is re-formulated using the polynomial chaos expansion. Following the Galerkin projection and polynomial orthogonality, stochastic partial inductance is represented by polynomial bases, which significantly reduces the complexity of the system and leads to considerable speed-up compared to the standard Monte Carlo sampling. The stochastic partial inductance model allows product designers to predict the most crucial statistical geometry-related inductance and inspect the dissimilarity between the models and the real world. Foreseeing these results and differences is the first step to create more robust PDNs designs in the minuscule and high-speed PCBs.

Department(s)

Electrical and Computer Engineering

Keywords and Phrases

decoupling capacitor (decap) connection pads; partial element equivalent circuit (PEEC); polynomial chaos expansion (PCE); power integrity (PI); stochastic partial inductance; uncertainty quantification

International Standard Book Number (ISBN)

978-172814261-6

Document Type

Article - Conference proceedings

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2024 Institute of Electrical and Electronics Engineers, All rights reserved.

Publication Date

01 Oct 2019

Download

Full Text Link

Share

 
COinS