A physically meaningful equivalent circuit network model of a lithium-ion battery accounting for local electrochemical and thermal behaviour, variable double layer capacitance and degradation
File(s)JPS_manuscript_Srbik.pdf (1.94 MB)
Accepted version
Author(s)
von Srbik, Marie-Therese
Marinescu, Monica
Martinez-Botas, Ricardo F
Offer, Gregory J
Type
Journal Article
Abstract
A novel electrical circuit analogy is proposed modelling
electrochemical systems under realistic automotive operation conditions. The model is developed for a lithium ion battery and is based on a pseudo 2D electrochemical model. Although cast in the framework familiar to application engineers, the model is
essentially an electrochemical battery model: all variables have a direct physical interpretation and there is direct access to all states of the cell via the model variables (concentrations, potentials) for monitoring and
control systems design. This is the first Equivalent Circuit Network-
type model that tracks directly the evolution of species inside the cell. It accounts for complex electrochemical phenomena that are usually omitted in online battery performance predictors such as variable double layer capacitance, the full current-overpotential relation and overpotentials due to mass transport limitations. The coupled electrochemical and thermal model accounts for capacity fade via a loss in active species and for power
fade via an increase in resistive solid electrolyte passivation layers at both electrodes. The model's capability to simulate cell behaviour under dynamic events is validated against test procedures, such as standard battery testing load cycles for current rates up to 20 C, as well as realistic automotive drive cycle loads.
electrochemical systems under realistic automotive operation conditions. The model is developed for a lithium ion battery and is based on a pseudo 2D electrochemical model. Although cast in the framework familiar to application engineers, the model is
essentially an electrochemical battery model: all variables have a direct physical interpretation and there is direct access to all states of the cell via the model variables (concentrations, potentials) for monitoring and
control systems design. This is the first Equivalent Circuit Network-
type model that tracks directly the evolution of species inside the cell. It accounts for complex electrochemical phenomena that are usually omitted in online battery performance predictors such as variable double layer capacitance, the full current-overpotential relation and overpotentials due to mass transport limitations. The coupled electrochemical and thermal model accounts for capacity fade via a loss in active species and for power
fade via an increase in resistive solid electrolyte passivation layers at both electrodes. The model's capability to simulate cell behaviour under dynamic events is validated against test procedures, such as standard battery testing load cycles for current rates up to 20 C, as well as realistic automotive drive cycle loads.
Date Issued
2016-09-01
Date Acceptance
2016-05-11
Citation
Journal of Power Sources, 2016, 325 (1), pp.171-184
ISSN
0378-7753
Publisher
Elsevier
Start Page
171
End Page
184
Journal / Book Title
Journal of Power Sources
Volume
325
Issue
1
Copyright Statement
© 2016 Elsevier. This manuscript is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/
Sponsor
Engineering & Physical Science Research Council (EPSRC)
Engineering & Physical Science Research Council (EPSRC)
Identifier
https://www.sciencedirect.com/science/article/pii/S0378775316305973?via%3Dihub
Grant Number
EP/I00422X/1
EP/I00422X/1
Subjects
Science & Technology
Physical Sciences
Technology
Chemistry, Physical
Electrochemistry
Energy & Fuels
Materials Science, Multidisciplinary
Chemistry
Materials Science
Lithium-ion battery
Equivalent circuit modelling
Electrochemical phenomenological model
Thermal modelling
Degradation
Battery management system optimisation
STATE-OF-CHARGE
ELECTRIC VEHICLE
AGING MODEL
POWER
OPTIMIZATION
SIMULATIONS
PREDICTION
VOLTAGE
DESIGN
03 Chemical Sciences
09 Engineering
Energy
Publication Status
Published
Date Publish Online
2016-06-14