Parameterising continuum level Li-ion battery models & the LiionDB database

TL;DR

This paper reviews methods for parameter estimation in the Doyle-Fuller-Newman lithium-ion battery model and introduces LiionDB, a comprehensive database of model parameters from literature.

Contribution

It provides a critical review of parameter measurement methods and introduces the LiionDB database for standard model parameters.

Findings

Comprehensive review of parameter estimation techniques.

Introduction of the LiionDB database for model parameters.

Discussion of limitations in current parameter measurement methods.

Abstract

The Doyle-Fuller-Newman framework is the most popular physics-based continuum-level description of the chemical and dynamical internal processes within operating lithium-ion-battery cells. With sufficient flexibility to model a wide range of battery designs and chemistries, the framework provides an effective balance between detail, needed to capture key microscopic mechanisms, and simplicity, needed to solve the governing equations at a relatively modest computational expense. Nevertheless, implementation requires values of numerous model parameters, whose ranges of applicability, estimation, and validation pose challenges. This article provides a critical review of the methods to measure or infer parameters for use within the isothermal DFN framework, discusses their advantages or disadvantages, and clarifies limitations attached to their practical application. Accompanying this discussion we provide a searchable database, available at www.liiondb.com, which aggregates many parameters and state functions for the standard Doyle-Fuller-Newman model that have been reported in the literature.