Next Article in Journal
A States of Matter Search-Based Approach for Solving the Problem of Intelligent Power Allocation in Plug-in Hybrid Electric Vehicles
Next Article in Special Issue
Integrated Traction Control Strategy for Distributed Drive Electric Vehicles with Improvement of Economy and Longitudinal Driving Stability
Previous Article in Journal
New Approaches to Circulating Current Controllers for Modular Multilevel Converters
Previous Article in Special Issue
Field Synergy Analysis and Optimization of the Thermal Behavior of Lithium Ion Battery Packs
Article Menu
Issue 1 (January) cover image

Export Article

Open AccessArticle
Energies 2017, 10(1), 90; doi:10.3390/en10010090

Structural Identifiability of Equivalent Circuit Models for Li-Ion Batteries

Energy and Electrical Systems, WMG, University of Warwick, Coventry CV4 7AL, UK
*
Author to whom correspondence should be addressed.
Academic Editor: K.T. Chau
Received: 15 November 2016 / Revised: 31 December 2016 / Accepted: 3 January 2017 / Published: 13 January 2017
(This article belongs to the Collection Electric and Hybrid Vehicles Collection)
View Full-Text   |   Download PDF [1064 KB, uploaded 13 January 2017]   |  

Abstract

Structural identifiability is a critical aspect of modelling that has been overlooked in the vast majority of Li-ion battery modelling studies. It considers whether it is possible to obtain a unique solution for the unknown model parameters from experimental data. This is a fundamental prerequisite of the modelling process, especially when the parameters represent physical battery attributes and the proposed model is utilised to estimate them. Numerical estimates for unidentifiable parameters are effectively meaningless since unidentifiable parameters have an infinite number of possible numerical solutions. It is demonstrated that the physical phenomena assignment to a two-RC (resistor–capacitor) network equivalent circuit model (ECM) is not possible without additional information. Established methods to ascertain structural identifiability are applied to 12 ECMs covering the majority of model templates used previously. Seven ECMs are shown not to be uniquely identifiable, reducing the confidence in the accuracy of the parameter values obtained and highlighting the relevance of structural identifiability even for relatively simple models. Suggestions are proposed to make the models identifiable and, therefore, more valuable in battery management system applications. The detailed analyses illustrate the importance of structural identifiability prior to performing parameter estimation experiments, and the algebraic complications encountered even for simple models. View Full-Text
Keywords: structural identifiability; lithium ion battery modelling; equivalent circuit models structural identifiability; lithium ion battery modelling; equivalent circuit models
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Grandjean, T.R.B.; McGordon, A.; Jennings, P.A. Structural Identifiability of Equivalent Circuit Models for Li-Ion Batteries. Energies 2017, 10, 90.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Energies EISSN 1996-1073 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top