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Electrochemical system analysis from impedance data to system identification

Title data

Danzer, Michael A. ; Plank, Christian ; Rüther, Tom:
Electrochemical system analysis from impedance data to system identification.
In: Cell Reports Physical Science. Vol. 5 (2024) Issue 7 . - 102091.
ISSN 2666-3864
DOI: https://doi.org/10.1016/j.xcrp.2024.102091

Official URL: Volltext

Abstract in another language

Summary Electrochemical impedance spectroscopy is a non-destructive experimental technique for the operando characterization of electrochemical systems. Here, we develop electrochemical system analysis (ELSA) as a data-driven, systems-theoretical approach to the analysis of measured impedance spectra. It solves the problem of finding an interpretable model description that explains given impedance data with high accuracy and without prior model assumptions. ELSA adopts the comprehensive analysis of the generalized distribution of relaxation time analysis and builds upon the data-driven and regularization-free Loewner method. ELSA systematically interprets the transfer function resulting from the Loewner method to reliably identify serial elements and resistive-capacitive and resistive-inductive processes with characteristic time constants. It also finds resonant elements by identifying conjugate complex poles. Based on the Shannon entropy of the residuals and the curvature of the locus, ELSA automatically and reproducibly identifies the minimal model order, thus avoiding overfitting. System characterization results are presented for different types of electrochemical power sources: batteries, fuel cells, and double-layer capacitors.

Further data

Item Type: Article in a journal
Refereed: Yes
Keywords: electrochemical impedance spectroscopy; distribution of relaxation times; Loewner method; system identification; system characterization; electrochemical analysis; lithium-ion battery; process identification; Shannon entropy
Institutions of the University: Faculties
Faculties > Faculty of Engineering Science
Faculties > Faculty of Engineering Science > Chair Electrical Energy Systems
Faculties > Faculty of Engineering Science > Chair Electrical Energy Systems > Chair Electrical Energy Systems - Univ.-Prof. Dr. Michael Danzer
Research Institutions
Research Institutions > Central research institutes
Research Institutions > Central research institutes > Bayerisches Zentrum für Batterietechnik - BayBatt
Result of work at the UBT: Yes
DDC Subjects: 600 Technology, medicine, applied sciences
600 Technology, medicine, applied sciences > 620 Engineering
Date Deposited: 25 Jul 2024 09:42
Last Modified: 25 Jul 2024 09:42
URI: https://eref.uni-bayreuth.de/id/eprint/90093