Practical identifiability of electrochemical P2D models for lithium-ion batteries

• Published in: Journal of applied electrochemistry Vol. 51; no. 9; pp. 1253 - 1265
• Main Authors: Laue, Vincent, Röder, Fridolin, Krewer, Ulrike
• Format: Journal Article
• Language: English
• Published: Dordrecht Springer Netherlands 01-09-2021; Springer Nature B.V
• Subjects: Batteries; Chemistry; Chemistry and Materials Science; Design optimization; Dynamic tests; Electrochemistry; Industrial Chemistry/Chemical Engineering; Lithium; Lithium-ion batteries; Mathematical models; Model testing; Open circuit voltage; Parameter identification; Parameterization; Physical Chemistry; Rechargeable batteries; Research Article; Spectrum analysis; Two dimensional models; Lithium-ion battery; Electrochemical modeling; Model identifiability
• ISSN: 0021-891X; 1572-8838
• DOI: 10.1007/s10800-021-01579-5

Electrochemical models play a significant role in today’s rapid development and enhancement of lithium-ion batteries. For instance, they are applied for design and process optimization. More recently, model and parameter identifiability are gaining interest as thorough model parameterization is key to reliable simulation results. Especially electrochemical models are often prone to unidentifiability and overfitting due to their high number of adjustable parameters. In this article, the most common electrochemical peudo-2D model of a lithium-ion battery is parameterized. A three-step procedure is applied which considers quasi-static 3-electrode measurements of the open-circuit potential, C-rate tests, and electrochemical impedance spectra. Identifiability of each step is discussed in-depth and a general guidance for future parameterizations is derived. The conducted study reveals the insufficiency of open-circuit potential and C-rate tests to fully parameterize the electrochemical model. Highly dynamic tests, e.g., impedance spectroscopy, are required to resolve the ambiguity of diffusive and electric processes under quasi-static conditions. Any parameterization of electrochemical models requires experimental data of electrode-resolved tests, as well as a combination of quasi-static and highly dynamic tests. The results of this study provide guidance for the use of electrochemical models in applied sciences and industry.
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