BibTex format

author = {Prosser, R and Patel, Y and Offer, GJ},
doi = {10.1149/ma2020-02623175mtgabs},
journal = {ECS Meeting Abstracts},
pages = {3175--3175},
title = {Lithium-Ion Battery Degradation Mode Diagnostics Using Heat Generation Profiles},
url = {},
volume = {MA2020-02},
year = {2020}

RIS format (EndNote, RefMan)

AB - <jats:p> As lithium ion cells are used, internal chemical and physical degradation processes occur which negatively impact cell performance. A key issue for battery systems engineers is extending the life of their battery pack which amounts to slowing down the rate of these degradation processes.</jats:p> <jats:p>The first step in addressing this problem is being able to frequently and accurately diagnose cell degradation. With this knowledge of cell state, it is possible to make better decisions on how to adjust the operating conditions of the battery pack to optimise cell longevity and performance.</jats:p> <jats:p>Current methods which are capable of accurate quantitative diagnostics employ thermodynamic models parameterised by different degradation modes. These models require very slow discharge rates or galvanic intermittent titration tests (GITT) to obtain the cell open circuit voltage (OCV) and therefore cannot be used in most commercial applications. Other methods which do not require OCV conditions involve an impedance model coupled to the thermodynamic model. This adds computational complexity of the methods as well as incurring an accuracy penalty compared to the thermodynamic models.</jats:p> <jats:p>We present a novel technique which uses cell instantaneous heat generation rate obtained in operando to quantify the extent of cell degradation. The proposed method provides results comparable to those obtained from thermodynamic models using a model which is no more computationally intense. The method also decouples the thermodynamic and kinetic effects of degradation allowing for a full diagnosis to be obtained more accurately and in a fraction of the time compared to alternative methods.</jats:p> <jats:p>With this powerful and simple method, a battery management system would be able to make better and more frequent adjustments to its cell’
AU - Prosser,R
AU - Patel,Y
AU - Offer,GJ
DO - 10.1149/ma2020-02623175mtgabs
EP - 3175
PY - 2020///
SP - 3175
TI - Lithium-Ion Battery Degradation Mode Diagnostics Using Heat Generation Profiles
T2 - ECS Meeting Abstracts
UR -
VL - MA2020-02
ER -