Stochastic Modelling of Power Electronic Converters under Uncertainties

Erjon Ballukja; Karol Niewiadomski; Angel Pena-Quintal; David W. P. Thomas; Sharmila  Sumsurooah; Mark Sumner

doi:10.1109/EMCSI39492.2022.9889372

Stochastic Modelling of Power Electronic Converters under Uncertainties

Erjon Ballukja
, Karol Niewiadomski
, Angel Pena-Quintal
, David W. P. Thomas
, Sharmila Sumsurooah
, Mark Sumner

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

2 Downloads (Pure)

Abstract

The aim of this paper is to explore the usage of different sampling schemes in order to build a sparse Polynomial Chaos (PC) model for prediction of the oscillation frequency and its corresponding magnitude of the output voltage in a half-bridge buck converter. The 22 parasitic elements of this converter are modelled as random variables following a uniform distribution. As a result, from the considered sampling schemes, an Latin Hypercube Sampling (LHS) and Sobol’ sequences are determined to be the best in prediction of the magnitude, both with respect to accuracy and computational time needed for the creation of the model. The introduced accuracy measure, namely the a posteriori error, shows that the PC model approximates the oscillation frequency well. However, from a visual comparison with a model obtained from 8000 Monte Carlo samples, it can be seen that the PC model is not able to handle such a complex relationship properly.

Original language	English
Title of host publication	2022 IEEE International Symposium on Electromagnetic Compatibility & Signal/Power Integrity (EMCSI)
Publisher	IEEE
Pages	232-237
Number of pages	6
ISBN (Electronic)	978-1-6654-0928-5, 978-1-6654-0929-2
ISBN (Print)	978-1-6654-0930-8
DOIs	https://doi.org/10.1109/EMCSI39492.2022.9889372
Publication status	Published - 26 Sept 2022
Externally published	Yes
Event	IEEE International Symposium On Electromagnetic Compatibility, Signal & Power Integrity, EMC+SIPI 2022 - Spokane Convention Center, Spokane, United States Duration: 1 Aug 2022 → 5 Aug 2022

Conference

Conference	IEEE International Symposium On Electromagnetic Compatibility, Signal & Power Integrity, EMC+SIPI 2022
Abbreviated title	EMC+SIPI 2022
Country/Territory	United States
City	Spokane
Period	1/08/22 → 5/08/22

Keywords

Computational Modelling
Electromagnetic Compatibility
Halton Sequences
Monte Carlo
Latin Hypercube Sampling
Parasitic elements
Sobol' Sequences
Sparse Polynomial Chaos

Access to Document

10.1109/EMCSI39492.2022.9889372

https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9889372

Cite this

@inproceedings{0e7357601648440ab7fdf3a686d5ffac,

title = "Stochastic Modelling of Power Electronic Converters under Uncertainties",

abstract = "The aim of this paper is to explore the usage of different sampling schemes in order to build a sparse Polynomial Chaos (PC) model for prediction of the oscillation frequency and its corresponding magnitude of the output voltage in a half-bridge buck converter. The 22 parasitic elements of this converter are modelled as random variables following a uniform distribution. As a result, from the considered sampling schemes, an Latin Hypercube Sampling (LHS) and Sobol{\textquoteright} sequences are determined to be the best in prediction of the magnitude, both with respect to accuracy and computational time needed for the creation of the model. The introduced accuracy measure, namely the a posteriori error, shows that the PC model approximates the oscillation frequency well. However, from a visual comparison with a model obtained from 8000 Monte Carlo samples, it can be seen that the PC model is not able to handle such a complex relationship properly.",

keywords = "Computational Modelling, Electromagnetic Compatibility, Halton Sequences, Monte Carlo, Latin Hypercube Sampling, Parasitic elements, Sobol' Sequences, Sparse Polynomial Chaos",

author = "Erjon Ballukja and Karol Niewiadomski and Angel Pena-Quintal and Thomas, \{David W. P.\} and Sharmila Sumsurooah and Mark Sumner",

note = "Funding Information: This project research is funded by the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No. 812391 and No. 812753 Funding Information: This project research is funded by the European Union{\textquoteright}s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No. 812391 and No. 812753. Publisher Copyright: {\textcopyright} 2022 IEEE.; IEEE International Symposium On Electromagnetic Compatibility, Signal \& Power Integrity, EMC+SIPI 2022, EMC+SIPI 2022 ; Conference date: 01-08-2022 Through 05-08-2022",

year = "2022",

month = sep,

day = "26",

doi = "10.1109/EMCSI39492.2022.9889372",

language = "English",

isbn = "978-1-6654-0930-8",

pages = "232--237",

booktitle = "2022 IEEE International Symposium on Electromagnetic Compatibility \& Signal/Power Integrity (EMCSI)",

publisher = "IEEE",

address = "United States",

}

Ballukja, E, Niewiadomski, K, Pena-Quintal, A, Thomas, DWP, Sumsurooah, S & Sumner, M 2022, Stochastic Modelling of Power Electronic Converters under Uncertainties. in 2022 IEEE International Symposium on Electromagnetic Compatibility & Signal/Power Integrity (EMCSI). IEEE, pp. 232-237, IEEE International Symposium On Electromagnetic Compatibility, Signal & Power Integrity, EMC+SIPI 2022, Spokane, Washington, United States, 1/08/22. https://doi.org/10.1109/EMCSI39492.2022.9889372

Stochastic Modelling of Power Electronic Converters under Uncertainties. / Ballukja, Erjon; Niewiadomski, Karol; Pena-Quintal, Angel et al.
2022 IEEE International Symposium on Electromagnetic Compatibility & Signal/Power Integrity (EMCSI). IEEE, 2022. p. 232-237.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

TY - GEN

T1 - Stochastic Modelling of Power Electronic Converters under Uncertainties

AU - Ballukja, Erjon

AU - Niewiadomski, Karol

AU - Pena-Quintal, Angel

AU - Thomas, David W. P.

AU - Sumsurooah, Sharmila

AU - Sumner, Mark

N1 - Funding Information: This project research is funded by the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No. 812391 and No. 812753 Funding Information: This project research is funded by the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No. 812391 and No. 812753. Publisher Copyright: © 2022 IEEE.

PY - 2022/9/26

Y1 - 2022/9/26

N2 - The aim of this paper is to explore the usage of different sampling schemes in order to build a sparse Polynomial Chaos (PC) model for prediction of the oscillation frequency and its corresponding magnitude of the output voltage in a half-bridge buck converter. The 22 parasitic elements of this converter are modelled as random variables following a uniform distribution. As a result, from the considered sampling schemes, an Latin Hypercube Sampling (LHS) and Sobol’ sequences are determined to be the best in prediction of the magnitude, both with respect to accuracy and computational time needed for the creation of the model. The introduced accuracy measure, namely the a posteriori error, shows that the PC model approximates the oscillation frequency well. However, from a visual comparison with a model obtained from 8000 Monte Carlo samples, it can be seen that the PC model is not able to handle such a complex relationship properly.

AB - The aim of this paper is to explore the usage of different sampling schemes in order to build a sparse Polynomial Chaos (PC) model for prediction of the oscillation frequency and its corresponding magnitude of the output voltage in a half-bridge buck converter. The 22 parasitic elements of this converter are modelled as random variables following a uniform distribution. As a result, from the considered sampling schemes, an Latin Hypercube Sampling (LHS) and Sobol’ sequences are determined to be the best in prediction of the magnitude, both with respect to accuracy and computational time needed for the creation of the model. The introduced accuracy measure, namely the a posteriori error, shows that the PC model approximates the oscillation frequency well. However, from a visual comparison with a model obtained from 8000 Monte Carlo samples, it can be seen that the PC model is not able to handle such a complex relationship properly.

KW - Computational Modelling

KW - Electromagnetic Compatibility

KW - Halton Sequences

KW - Monte Carlo

KW - Latin Hypercube Sampling

KW - Parasitic elements

KW - Sobol' Sequences

KW - Sparse Polynomial Chaos

U2 - 10.1109/EMCSI39492.2022.9889372

DO - 10.1109/EMCSI39492.2022.9889372

M3 - Conference contribution

SN - 978-1-6654-0930-8

SP - 232

EP - 237

BT - 2022 IEEE International Symposium on Electromagnetic Compatibility & Signal/Power Integrity (EMCSI)

PB - IEEE

T2 - IEEE International Symposium On Electromagnetic Compatibility, Signal & Power Integrity, EMC+SIPI 2022

Y2 - 1 August 2022 through 5 August 2022

ER -

Stochastic Modelling of Power Electronic Converters under Uncertainties

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Conference

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