Imperial College London
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DrMonicaMarinescu

Faculty of Engineering, Department of Mechanical Engineering

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+44 (0)20 7594 7091monica.marinescu Website

 
 
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Location

 

722Mechanical EngineeringSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@article{Propp:2016:10.1016/j.jpowsour.2016.07.090,
author = {Propp, K and Marinescu, M and Auger, DJ and O'Neill, L and Fotouhi, A and Somasundaram, K and Offer, GJ and Minton, G and Longo, S and Wild, M and Knap, V},
doi = {10.1016/j.jpowsour.2016.07.090},
journal = {Journal of Power Sources},
pages = {289--299},
title = {Multi-temperature state-dependent equivalent circuit discharge model for lithium-sulfur batteries},
url = {http://dx.doi.org/10.1016/j.jpowsour.2016.07.090},
volume = {328},
year = {2016}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - Lithium-sulfur (Li-S) batteries are described extensively in the literature, but existing computational models aimed at scientific understanding are too complex for use in applications such as battery management. Computationally simple models are vital for exploitation. This paper proposes a non-linear state-of-charge dependent Li-S equivalent circuit network (ECN) model for a Li-S cell under discharge. Li-S batteries are fundamentally different to Li-ion batteries, and require chemistry-specific models. A new Li-S model is obtained using a ‘behavioural’ interpretation of the ECN model; as Li-S exhibits a ‘steep’ open-circuit voltage (OCV) profile at high states-of-charge, identification methods are designed to take into account OCV changes during current pulses. The prediction-error minimization technique is used. The model is parameterized from laboratory experiments using a mixed-size current pulse profile at four temperatures from 10 °C to 50 °C, giving linearized ECN parameters for a range of states-of-charge, currents and temperatures. These are used to create a nonlinear polynomial-based battery model suitable for use in a battery management system. When the model is used to predict the behaviour of a validation data set representing an automotive NEDC driving cycle, the terminal voltage predictions are judged accurate with a root mean square error of 32 mV.
AU  - Propp,K
AU  - Marinescu,M
AU  - Auger,DJ
AU  - O'Neill,L
AU  - Fotouhi,A
AU  - Somasundaram,K
AU  - Offer,GJ
AU  - Minton,G
AU  - Longo,S
AU  - Wild,M
AU  - Knap,V
DO  - 10.1016/j.jpowsour.2016.07.090
EP  - 299
PY  - 2016///
SN  - 1873-2755
SP  - 289
TI  - Multi-temperature state-dependent equivalent circuit discharge model for lithium-sulfur batteries
T2  - Journal of Power Sources
UR  - http://dx.doi.org/10.1016/j.jpowsour.2016.07.090
UR  - http://hdl.handle.net/10044/1/39221
VL  - 328
ER  -
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