A comparative study of equivalent circuit models for Li-ion batteries

Hu, Xiaosong; Li, Shengbo Eben; Peng, Huei

doi:10.1016/j.jpowsour.2011.10.013

Cited by 1,655 publications

(686 citation statements)

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“…With the battery current assumed as the independent variable the model should accurately predict the voltage response given the initial states of the battery. This mapping from current to voltage has been realised extensively in the form of an Equivalent Circuit Model (ECM) [2,3,4,5]. Models that do not rely on the current to voltage causality have also been developed in [6], and in [7] a Li-ion Bond Graph model is presented.…”

Section: Notationsmentioning

confidence: 99%

“…As shown in [2] a first-order ECM is sufficient to model pulse responses and as explained in the introduction the ECM is estimated as a function of SoC, temperature and current direction together with OCV with hysteresis. For comparison the two models are estimated at the same SoC and temperature points and are validated with the same drive-cycle current profiles.…”

Section: Model Validationmentioning

confidence: 99%

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Design and use of multisine signals for Li-ion battery equivalent circuit modelling. Part 2: Model estimation

Widanage

Barai

Chouchelamane

et al. 2016

Journal of Power Sources

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Copyright and reuse:The Warwick Research Archive Portal (WRAP) makes this work by researchers of the University of Warwick available open access under the following conditions. Copyright © and all moral rights to the version of the paper presented here belong to the individual author(s) and/or other copyright owners. To the extent reasonable and practicable the material made available in WRAP has been checked for eligibility before being made available.Copies of full items can be used for personal research or study, educational, or not-for-profit purposes without prior permission or charge. Provided that the authors, title and full bibliographic details are credited, a hyperlink and/or URL is given for the original metadata page and the content is not changed in any way.

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Section: Notationsmentioning

confidence: 99%

Section: Model Validationmentioning

confidence: 99%

Design and use of multisine signals for Li-ion battery equivalent circuit modelling. Part 2: Model estimation

Widanage

Barai

Chouchelamane

et al. 2016

Journal of Power Sources

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“…In [6] a first-order ECM is shown to be sufficient to model pulse responses, as such a first-order ECM is used to model the 18650 3.03 Ah NCA battery.…”

Section: Pulse-multisine Performancementioning

confidence: 99%

“…The ECM parameters are usually obtained by minimising the sum of squared errors between the measured and simulated voltage via some nonlinear least squares algorithm [6,7]. By applying the PPC current sequence and measuring the corresponding voltage response (which together forms the estimation data set) at different SoCs and at different battery temperatures, an ECM can be parametrised as a function of SoC and temperature, and if required, be parametrised for charge/discharge and C-rate.…”

Section: Introductionmentioning

confidence: 99%

Design and use of multisine signals for Li-ion battery equivalent circuit modelling. Part 1: Signal design

Widanage

Barai

Chouchelamane

et al. 2016

Journal of Power Sources

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Permanent WRAP URL:http://wrap.warwick.ac.uk/79240 Copyright and reuse:The Warwick Research Archive Portal (WRAP) makes this work by researchers of the University of Warwick available open access under the following conditions. Copyright © and all moral rights to the version of the paper presented here belong to the individual author(s) and/or other copyright owners. To the extent reasonable and practicable the material made available in WRAP has been checked for eligibility before being made available.Copies of full items can be used for personal research or study, educational, or not-for-profit purposes without prior permission or charge. Provided that the authors, title and full bibliographic details are credited, a hyperlink and/or URL is given for the original metadata page and the content is not changed in any way. A note on versions:The version presented here may differ from the published version or, version of record, if you wish to cite this item you are advised to consult the publisher's version. Please see the 'permanent WRAP URL' above for details on accessing the published version and note that access may require a subscription. AbstractThe Pulse Power Current (PPC) profile is often the signal of choice for obtaining the parameters of a Lithium-ion (Li-ion) battery Equivalent Circuit Model (ECM). Subsequently, a drive-cycle current profile is used as a validation signal. Such a profile, in contrast to a PPC, is more dynamic in both the amplitude and frequency bandwidth. Modelling errors can occur when using PPC data for parametrisation since the model is optimised over a narrower bandwidth than the validation profile. A signal more representative of a drive-cycle, while maintaining a degree of generality, is needed to reduce such modelling errors.In Part 1 of this 2-part paper a signal design technique defined as a pulsemultisine is presented. This superimposes a signal known as a multisine to a discharge, rest and charge base signal to achieve a profile more dynamic in amplitude and frequency bandwidth, and thus more similar to a drive-cycle. * Corresponding author. Email: Dhammika.Widanalage@warwick.ac.uk. Address: WMG, University of Warwick, Coventry, CV4 7AL, UK. Telephone: 0044 24765 28191. Preprint submitted to Journal of Power SourcesMay 25, 2016The signal improves modelling accuracy and reduces the experimentation time, per state-of-charge (SoC) and temperature, to several minutes compared to several hours for an PPC experiment.

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“…At each aging cycle, charging or discharging the battery with constant current mode until it reaches the specified voltage [7]. Cycle life is determined by the number of cycles of charge-discharge a battery in which the battery can work well before its nominal capacity falls below 80% of the initial capacity of the battery.…”

Section: Aging Cycle Testmentioning

confidence: 99%