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Batteries 2016, 2(2), 13; doi:10.3390/batteries2020013

Characterising Lithium-Ion Battery Degradation through the Identification and Tracking of Electrochemical Battery Model Parameters

1
WMG, International Digital Laboratory, University of Warwick, Coventry CV4 7AL, UK
2
Maplesoft Europe Ltd., Broers Building, 21 JJ Thompson Avenue, Cambridge CB3 OFA, UK
*
Author to whom correspondence should be addressed.
Academic Editor: Juan Carlos Álvarez Antón
Received: 10 March 2016 / Revised: 8 April 2016 / Accepted: 12 April 2016 / Published: 26 April 2016
(This article belongs to the Special Issue Battery Modeling)
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Abstract

Lithium-ion (Li-ion) batteries undergo complex electrochemical and mechanical degradation. This complexity is pronounced in applications such as electric vehicles, where highly demanding cycles of operation and varying environmental conditions lead to non-trivial interactions of ageing stress factors. This work presents the framework for an ageing diagnostic tool based on identifying and then tracking the evolution of model parameters of a fundamental electrochemistry-based battery model from non-invasive voltage/current cycling tests. In addition to understanding the underlying mechanisms for degradation, the optimisation algorithm developed in this work allows for rapid parametrisation of the pseudo-two dimensional (P2D), Doyle-Fuller-Newman, battery model. This is achieved through exploiting the embedded symbolic manipulation capabilities and global optimisation methods within MapleSim. Results are presented that highlight the significant reductions in the computational resources required for solving systems of coupled non-linear partial differential equations. View Full-Text
Keywords: lithium-ion (Li-ion) battery; degradation mechanism; ageing; parameter identification; diagnostic lithium-ion (Li-ion) battery; degradation mechanism; ageing; parameter identification; diagnostic
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).

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Uddin, K.; Perera, S.; Widanage, W.D.; Somerville, L.; Marco, J. Characterising Lithium-Ion Battery Degradation through the Identification and Tracking of Electrochemical Battery Model Parameters. Batteries 2016, 2, 13.

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