4.4 Article

Practical identifiability of electrochemical P2D models for lithium-ion batteries

期刊

JOURNAL OF APPLIED ELECTROCHEMISTRY
卷 51, 期 9, 页码 1253-1265

出版社

SPRINGER
DOI: 10.1007/s10800-021-01579-5

关键词

Lithium-ion battery; Electrochemical modeling; Model identifiability

资金

  1. German Federal Ministry for Economic Affairs and Energy (BMWi) through the project Data-Mining in der Produktion von Lithium-Ionen Batteriezellen (DaLion) [03ET6089]

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Electrochemical models are crucial for the development of lithium-ion batteries, but parameterization poses challenges of identifiability and overfitting. A combination of static and dynamic tests is needed for accurate simulation results.
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. [GRAPHICS] .

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