Zugriffsnummer 48414
Dokumenttyp Zeitschriftenartikel Open Access Hybrid
Peer Review mit Peer Review
Sprache Englisch
Titel Comparison of methodologies to estimate state-of-health of commercial Li-ion cells from electrochemical frequency response data.
Autor(in); Institution
Chana, Hoon Seng; Karlsruhe Institute of Technology (KIT), Institute for Applied Materials - Electrochemical Technologies (IAM-ET), Karlsruhe, GERMANY
Dickinson, Edmund J.F.; National Physical Laboratory (NPL), Teddington, UK
Heins, Tom P.; 3.1, Allgemeine und Anorganische Chemie, PTB-Braunschweig
Park, Juyeon; National Physical Laboratory (NPL), Teddington, UK
Gaberšček, Miran; National Institute of Chemistry (NIC), Department of Materials Chemistry, Ljubljana, SLOVENIA
Lee, Yan Ying; Karlsruhe Institute of Technology (KIT), Institute for Applied Materials - Electrochemical Technologies (IAM-ET), Karlsruhe, GERMANY
Heinrich, Marco; 3.1, Allgemeine und Anorganische Chemie, PTB-Braunschweig
Ruiz, Vanesa; European Commission, Joint Research Centre (JRC) Petten, THE NETHERLANDS
Napolitano, Emilio; European Commission, Joint Research Centre (JRC) Petten, THE NETHERLANDS
Kauranen, Pertti; Research Group of Electrochemical Energy Conversion and Storage, Department of Chemistry, School of Chemical Engineering, Aalto University, FINLAND; LUT University, Lappeenranta, FINLAND
Fedorovskaya, Ekaterina; Research Group of Electrochemical Energy Conversion and Storage, Department of Chemistry, School of Chemical Engineering, Aalto University, FINLAND; LUT University, Lappeenranta, FINLAND
Moškon, Joe; National Institute of Chemistry (NIC), Department of Materials Chemistry, Ljubljana, SLOVENIA
Kallio, Tanja; Research Group of Electrochemical Energy Conversion and Storage, Department of Chemistry, School of Chemical Engineering, Aalto University, FINLAND
Mousavihashemi, Seyedabolfaz; Research Group of Electrochemical Energy Conversion and Storage, Department of Chemistry, School of Chemical Engineering, Aalto University, FINLAND
Krewer, Ulrike; Karlsruhe Institute of Technology (KIT), Institute for Applied Materials - Electrochemical Technologies (IAM-ET), Karlsruhe, GERMANY
Hinds, Gareth; National Physical Laboratory (NPL), Teddington, UK
Seitz, Steffen; 3.1, Allgemeine und Anorganische Chemie, PTB-Braunschweig
Quelle/Jahr Journal of Power Sources: 542 (2022), 1 - 14
Artikelnummer 231814
ISSN 0378-7753 (PRINT) ; 1873-2755 (ONLINE)
DOI
Verlag Amsterdam: Elsevier
Freie Schlagworte Electrochemical impedance spectroscopy ; Equivalent circuit ; Distribution of relaxation times ; Nonlinear frequency response analysis ; State-of-health prediction
Zusammenfassung arious impedance-based and nonlinear frequency response-based methods for determining the state-of-health (SOH) of commercial lithium-ion cells are evaluated. Frequency response-based measurements provide a spectral representation of dynamics of underlying physicochemical processes in the cell, giving evidence about its internal physical state. The investigated methods can be carried out more rapidly than controlled full discharge and thus constitute prospectively more efficient measurement procedures to determine the SOH of aged lithium-ion cells. We systematically investigate direct use of electrochemical impedance spectroscopy (EIS) data, equivalent circuit fits to EIS, distribution of relaxation times analysis on EIS, and nonlinear frequency response analysis. SOH prediction models are developed by correlating key parameters of each method with conventional capacity measurement (i.e., current integration). The practical feasibility, reliability and uncertainty of each of the established SOH models are considered: all models show average RMS error in the range 0.75%-1.5% SOH units, attributable principally to cell-to-cell variation. Methods based on processed data (equivalent circuit, distribution of relaxation times) are more experimentally and numerically demanding but show lower average uncertainties and may offer more flexibility for future application.
Kostenfreier Zugang Open Access Hybrid
Rechteinformation CC BY 4.0 ; Creative Commons Attribution 4.0 License
Innovationscluster Umwelt und Klima

Zitierung

Chana, H. S., Dickinson, E. J., Heins, T. P., Park, J., Gaberšček, M., Lee, Y. Y., Heinrich, M., Ruiz, V., Napolitano, E., Kauranen, P., Fedorovskaya, E., Moškon, J., Kallio, T., Mousavihashemi, S., Krewer, U., Hinds, G., & Seitz, S. (2022). Comparison of methodologies to estimate state-of-health of commercial Li-ion cells from electrochemical frequency response data. Journal of Power Sources, 542, 1–14. https://doi.org/10.1016/j.jpowsour.2022.231814

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