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Nonlinear Frequency Response Analysis on Lithium-Ion Batteries : A Model-Based Assessment

Title data

Wolff, Nicolas ; Harting, Nina ; Heinrich, Marco ; Röder, Fridolin ; Krewer, Ulrike:
Nonlinear Frequency Response Analysis on Lithium-Ion Batteries : A Model-Based Assessment.
In: Electrochimica Acta. Vol. 260 (2018) . - pp. 614-622.
ISSN 0013-4686
DOI: https://doi.org/10.1016/j.electacta.2017.12.097

Abstract in another language

The nonlinear behavior of electrochemical systems, such as batteries bears essential information on their state and processes interacting within them. A Pseudo-two-Dimensional Lithium-ion battery model is used for Nonlinear Frequency Response Analysis (NFRA). Focus is laid on identification of processes in Lithium-ion batteries. The most commonly applied dynamic electrochemical analysis method, Electrochemical Impedance Spectroscopy (EIS), is limited to linear deflections of the system. This denotes loss of information about nonlinear system behavior. In contrast, NFRA extends this approach to study the nonlinear behavior of the Lithium-ion battery. We show dependency of nonlinear responses on the input amplitude and several model parameters, such as diffusion coefficient, reaction rate constant and double layer capacitance. Parameter variation demonstrates the capability of this method for process identification by investigating the individual higher harmonics and the respective sum. Characteristic peaks can be attributed to electrode reactions and diffusion and frequency regions influenced by the signal can be identified. This work gives a deeper understanding of the nonlinear response of a Lithium-ion battery and as such of how to apply this analysis method for Lithium-ion battery state estimation. It is shown that the method NFRA is essential for reliable process identification. Battery characterization highly benefits from the combination of EIS and NFRA.

Further data

Item Type: Article in a journal
Refereed: Yes
Keywords: NFRA; Electrochemical impedance spectroscopy; Modeling; Dynamic analysis
Institutions of the University: Faculties > Faculty of Engineering Science
Faculties
Faculties > Faculty of Engineering Science > Junior Professor Methods of Monitoring and Managing Batteries > Junior Professor Methods of Monitoring and Managing Batteries - Juniorprof. Dr.-Ing. Fridolin Röder
Result of work at the UBT: No
DDC Subjects: 600 Technology, medicine, applied sciences > 620 Engineering
Date Deposited: 20 Nov 2020 07:49
Last Modified: 27 Nov 2020 07:34
URI: https://eref.uni-bayreuth.de/id/eprint/59656