Data-driven Based PEMFC EIS Modeling with Nyquist Plot

Haochuan Zhang; Jianfeng Lv; Jiyuan Kuang; Zhenhuan Wang; Imad Matraji; Patrick Muhl; Jianxing Liu

doi:10.1109/IECON49645.2022.9969019

Data-driven Based PEMFC EIS Modeling with Nyquist Plot

Haochuan Zhang
, Jianfeng Lv
, Jiyuan Kuang
, Zhenhuan Wang
, Imad Matraji
, Patrick Muhl
, Jianxing Liu^*

^*Corresponding author for this work

Harbin Institute of Technology
Ltd.

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

2 Scopus citations

Abstract

Electrochemical impedance spectroscopy (EIS) Nyquist plot modeling has been attached great importance to fault diagnosis of proton exchange membrane fuel cell (PEMFC) system. This paper applies Gaussian process regression (GPR) and Bayesian optimization (BO) to the problem of building an adaptive EIS Nyquist plot model of PEMFC. The experimental results show that GPR performs better than multivariate polynomial regression and equivalent circuit model (ECM) method for this task when a small number of training samples are available. Therefore, this method can be a suitable approach for online adaption of EIS Nyquist plot model for fault diagnosis application.

Original language	English
Title of host publication	IECON 2022 - 48th Annual Conference of the IEEE Industrial Electronics Society
Publisher	IEEE Computer Society
ISBN (Electronic)	9781665480253
DOIs	https://doi.org/10.1109/IECON49645.2022.9969019
State	Published - 2022
Event	48th Annual Conference of the IEEE Industrial Electronics Society, IECON 2022 - Brussels, Belgium Duration: 17 Oct 2022 → 20 Oct 2022

Publication series

Name	IECON Proceedings (Industrial Electronics Conference)
Volume	2022-October
ISSN (Print)	2162-4704
ISSN (Electronic)	2577-1647

Conference

Conference	48th Annual Conference of the IEEE Industrial Electronics Society, IECON 2022
Country/Territory	Belgium
City	Brussels
Period	17/10/22 → 20/10/22

Keywords

Data-driven
Electrochemical Impedance Spectroscopy
Gaussian Process Regression
Hyper-parameter Adaptive
Proton Exchange Membrane Fuel Cell

Access to Document

10.1109/IECON49645.2022.9969019

Cite this

@inproceedings{ac6521236e84446cb1a4f70e0219f07c,

title = "Data-driven Based PEMFC EIS Modeling with Nyquist Plot",

abstract = "Electrochemical impedance spectroscopy (EIS) Nyquist plot modeling has been attached great importance to fault diagnosis of proton exchange membrane fuel cell (PEMFC) system. This paper applies Gaussian process regression (GPR) and Bayesian optimization (BO) to the problem of building an adaptive EIS Nyquist plot model of PEMFC. The experimental results show that GPR performs better than multivariate polynomial regression and equivalent circuit model (ECM) method for this task when a small number of training samples are available. Therefore, this method can be a suitable approach for online adaption of EIS Nyquist plot model for fault diagnosis application.",

keywords = "Data-driven, Electrochemical Impedance Spectroscopy, Gaussian Process Regression, Hyper-parameter Adaptive, Proton Exchange Membrane Fuel Cell",

author = "Haochuan Zhang and Jianfeng Lv and Jiyuan Kuang and Zhenhuan Wang and Imad Matraji and Patrick Muhl and Jianxing Liu",

note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 48th Annual Conference of the IEEE Industrial Electronics Society, IECON 2022 ; Conference date: 17-10-2022 Through 20-10-2022",

year = "2022",

doi = "10.1109/IECON49645.2022.9969019",

language = "英语",

series = "IECON Proceedings (Industrial Electronics Conference)",

publisher = "IEEE Computer Society",

booktitle = "IECON 2022 - 48th Annual Conference of the IEEE Industrial Electronics Society",

address = "美国",

}

Zhang, H, Lv, J, Kuang, J , Wang, Z, Matraji, I, Muhl, P & Liu, J 2022, Data-driven Based PEMFC EIS Modeling with Nyquist Plot. in IECON 2022 - 48th Annual Conference of the IEEE Industrial Electronics Society. IECON Proceedings (Industrial Electronics Conference), vol. 2022-October, IEEE Computer Society, 48th Annual Conference of the IEEE Industrial Electronics Society, IECON 2022, Brussels, Belgium, 17/10/22. https://doi.org/10.1109/IECON49645.2022.9969019

Data-driven Based PEMFC EIS Modeling with Nyquist Plot. / Zhang, Haochuan; Lv, Jianfeng; Kuang, Jiyuan et al.
IECON 2022 - 48th Annual Conference of the IEEE Industrial Electronics Society. IEEE Computer Society, 2022. (IECON Proceedings (Industrial Electronics Conference); Vol. 2022-October).

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

TY - GEN

T1 - Data-driven Based PEMFC EIS Modeling with Nyquist Plot

AU - Zhang, Haochuan

AU - Lv, Jianfeng

AU - Kuang, Jiyuan

AU - Wang, Zhenhuan

AU - Matraji, Imad

AU - Muhl, Patrick

AU - Liu, Jianxing

PY - 2022

Y1 - 2022

N2 - Electrochemical impedance spectroscopy (EIS) Nyquist plot modeling has been attached great importance to fault diagnosis of proton exchange membrane fuel cell (PEMFC) system. This paper applies Gaussian process regression (GPR) and Bayesian optimization (BO) to the problem of building an adaptive EIS Nyquist plot model of PEMFC. The experimental results show that GPR performs better than multivariate polynomial regression and equivalent circuit model (ECM) method for this task when a small number of training samples are available. Therefore, this method can be a suitable approach for online adaption of EIS Nyquist plot model for fault diagnosis application.

AB - Electrochemical impedance spectroscopy (EIS) Nyquist plot modeling has been attached great importance to fault diagnosis of proton exchange membrane fuel cell (PEMFC) system. This paper applies Gaussian process regression (GPR) and Bayesian optimization (BO) to the problem of building an adaptive EIS Nyquist plot model of PEMFC. The experimental results show that GPR performs better than multivariate polynomial regression and equivalent circuit model (ECM) method for this task when a small number of training samples are available. Therefore, this method can be a suitable approach for online adaption of EIS Nyquist plot model for fault diagnosis application.

KW - Data-driven

KW - Electrochemical Impedance Spectroscopy

KW - Gaussian Process Regression

KW - Hyper-parameter Adaptive

KW - Proton Exchange Membrane Fuel Cell

UR - https://www.scopus.com/pages/publications/85143893842

U2 - 10.1109/IECON49645.2022.9969019

DO - 10.1109/IECON49645.2022.9969019

M3 - 会议稿件

AN - SCOPUS:85143893842

T3 - IECON Proceedings (Industrial Electronics Conference)

BT - IECON 2022 - 48th Annual Conference of the IEEE Industrial Electronics Society

PB - IEEE Computer Society

T2 - 48th Annual Conference of the IEEE Industrial Electronics Society, IECON 2022

Y2 - 17 October 2022 through 20 October 2022

ER -

Data-driven Based PEMFC EIS Modeling with Nyquist Plot

Abstract

Publication series

Conference

Keywords

Access to Document

Other files and links

Fingerprint

Cite this