Development of Experimental Techniques for Parameterization of Multi-scale Lithium-ion Battery Models
By Chang-Hui Chen, Ferran Brosa Planella, K. O’Regan, Dominika Gastol, Widanalage Dhammika Widanage, Emma Kendrick. Journal of the Electrochemical Society, 2020
363 citations recorded by the source corpus.
Presented here, is an extensive 35 parameter experimental data set of a cylindrical 21700 commercial cell (LGM50), for an electrochemical pseudo-two-dimensional (P2D) model. The experimental methodologies for tear-down and subsequent chemical, physical, electrochemical kinetics and thermodynamic analysis, and their accuracy and validity are discussed. Chemical analysis of the LGM50 cell shows that it is comprised of a NMC 811 positive electrode and bi-component Graphite-SiOx negative electrode. The thermodynamic open circuit voltages (OCV) and lithium stoichiometry in the electrode are obtained using galvanostatic intermittent titration technique (GITT) in half cell and three-electrode full cell configurations. The activation energy and exchange current coefficient through electrochemical impedance spectroscopy (EIS) measurements. Apparent diffusion coefficients are estimated using the Sand equation on the voltage transient during the current pulse; an expansion factor was applied to the bi-component negative electrode data to reflect the average change in effective surface area during lithiation. The 35 parameters are applied within a P2D model to show the fit to experimental validation LGM50 cell discharge and relaxation voltage profiles at room temperature. The accuracy and validity of the processes and the techniques in the determination of these parameters are discussed, including opportunities for further modelling and data analysis improvements.
Subfields: Automotive Engineering, Electrical and Electronic Engineering
View Paper: https://www.semanticscholar.org/paper/46c384903d1682ac6315bc4e66396d42c22649b4
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Citations in the corpus
- Battery digital twins: Perspectives on the fusion of models, data and artificial intelligence for smart battery management systems (2020, methodology): “This was highlighted by Chen et al. [18] who presented a comprehensive parameterisation of a NMC811-Gr/SiOx cell, whereby 35 different parameters, broken down into physical, chemical and electro-chemical parameters, for the electrode and separator/electrolyte were extracted.”
- The challenge and opportunity of battery lifetime prediction from field data (2021, neutral): “cell teardown and specialized testing equipment [92, 93] to determine a wide range of parameters such as reaction rate constants, conductivities, diffusivities, particle sizes etc.”