Multi-temperature state-dependent equivalent circuit discharge model for lithium-sulfur batteries

Karsten Propp, Monica Marinescu, Daniel J. Auger, Laura O'Neill, Abbas Fotouhi, Karthik Somasundaram, Gregory J. Offer, Geraint Minton, Stefano Longo, Mark Wild, Vaclav Knap

Research output: Contribution to journalJournal articleResearchpeer-review

68 Citations (Scopus)
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Abstract

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.
Original languageEnglish
JournalJournal of Power Sources
Volume328
Pages (from-to)289-299
Number of pages11
ISSN0378-7753
DOIs
Publication statusPublished - Oct 2016

Keywords

  • Lithium-sulfur battery
  • Parameter estimation
  • System identification
  • Battery model

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