Nondestructive EIS Testing to Estimate a Subset of Physics-Based-Model Parameter Values for Lithium-Ion Cells


This paper is the final installment in a series of articles that collectively shows how to estimate parameter values for lumped-parameter physics-based models of lithium-ion cells without requiring cell teardown. In this paper, we leverage electrochemical impedance spectroscopy (EIS) to find estimates of all as-yet-unresolved parameter values. The characterization process regresses the measured cell impedance spectrum to exact analytic closed-form expressions of the frequency response of an extended Doyle–Fuller–Newman model to identify thirteen lumped parameters plus multiple reaction-rate constants. A nonlinear optimization algorithm performs the regression, and so it is important to provide reasonable initial parameter estimates and constraints, which we also discuss. As part of this process, the generalized distribution of realization times technique is used to isolate time constants from the two electrodes as well as to calibrate the laboratory EIS-test data. The overall methodology is studied on a virtual cell and on a laboratory cell (both having graphite//NMC chemistries). Parameter estimates found in the simulation study are highly accurate, leading us to have confidence in the values estimated for the physical cell as well.

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This publication pertains to:
Charging Stations
Publication Authors:
  • Dongliang Lu
  • Michael Trimboli
  • Guodong Fan
  • Yujun Wang
  • Gregory Plett
It appeared in:
Peer-reviewed technical journal
Battery model