4.6 Article

Nonlinear Identifiability Analysis of the Porous Electrode Theory Model of Lithium-Ion Batteries

Journal

JOURNAL OF THE ELECTROCHEMICAL SOCIETY
Volume 168, Issue 9, Pages -

Publisher

ELECTROCHEMICAL SOC INC
DOI: 10.1149/1945-7111/ac26b1

Keywords

Batteries-Lithium; Batteries; Batteries-Li-ion; Electrochemical Engineering; Energy Storage; Power Sources; Theory and Modelling

Funding

  1. Toyota Research Institute

Ask authors/readers for more resources

Porous electrode theory is commonly used to model battery behavior, but most effective parameters are not practically identifiable from cycling data in lithium-ion batteries. The only identifiable parameter from C/10 discharge data is the effective solid diffusion coefficient. Additional experiments are required to uniquely determine the full set of parameters.
Porous electrode theory (PET) is widely used to model battery cycling behavior by describing electrochemical kinetics and transport in solid particles and electrolyte, and modeling thermodynamics by fitting an open-circuit potential. The PET model consists of tightly coupled nonlinear partial differential-algebraic equations in which effective kinetic and transport parameters are fit to battery cycling data, and then the model is used to analyze the effects of variations in design parameters or operating conditions such as charging protocols. In a detailed nonlinear identifiability analysis, we show that most of the effective model parameters in porous electrode theory are not practically identifiable from cycling data for a lithium-ion battery. The only identifiable parameter that can be identified from C/10 discharge data is the effective solid diffusion coefficient, indicating that this battery is in the diffusion-limited regime at this discharge rate. A resistance in series correlation was shown for the practically unidentifiable parameters by mapping out the confidence region. Alternative experiments in addition to discharge cycles are required in order to uniquely determine the full set of parameters.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.6
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available