Citation

BibTex format

@article{Merla:2018:10.1016/j.jpowsour.2018.02.065,
author = {Merla, Y and Wu, B and Yufit, V and Martinez-Botas, RF and Offer, GJ},
doi = {10.1016/j.jpowsour.2018.02.065},
journal = {Journal of Power Sources},
pages = {66--79},
title = {An easy-to-parameterise physics-informed battery model and its application towards lithium-ion battery cell design, diagnosis, and degradation},
url = {http://dx.doi.org/10.1016/j.jpowsour.2018.02.065},
volume = {384},
year = {2018}
}

RIS format (EndNote, RefMan)

TY  - JOUR
AB - Accurate diagnosis of lithium ion battery state-of-health (SOH) is of significant value for many applications, to improve performance, extend life and increase safety. However, in-situ or in-operando diagnosis of SOH often requires robust models. There are many models available however these often require expensive-to-measure ex-situ parameters and/or contain unmeasurable parameters that were fitted/assumed. In this work, we have developed a new empirically parameterised physics-informed equivalent circuit model. Its modular construction and low-cost parametrisation requirements allow end users to parameterise cells quickly and easily. The model is accurate to 19.6 mV for dynamic loads without any global fitting/optimisation, only that of the individual elements. The consequences of various degradation mechanisms are simulated, and the impact of a degraded cell on pack performance is explored, validated by comparison with experiment. Results show that an aged cell in a parallel pack does not have a noticeable effect on the available capacity of other cells in the pack. The model shows that cells perform better when electrodes are more porous towards the separator and have a uniform particle size distribution, validated by comparison with published data. The model is provided with this publication for readers to use.
AU - Merla,Y
AU - Wu,B
AU - Yufit,V
AU - Martinez-Botas,RF
AU - Offer,GJ
DO - 10.1016/j.jpowsour.2018.02.065
EP - 79
PY - 2018///
SN - 0378-7753
SP - 66
TI - An easy-to-parameterise physics-informed battery model and its application towards lithium-ion battery cell design, diagnosis, and degradation
T2 - Journal of Power Sources
UR - http://dx.doi.org/10.1016/j.jpowsour.2018.02.065
UR - https://www.sciencedirect.com/science/article/pii/S0378775318301861
UR - http://hdl.handle.net/10044/1/58077
VL - 384
ER -