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Journal ArticleDOI

A self-discharge model of Lithium-Sulfur batteries based on direct shuttle current measurement

TL;DR: In this paper, a simple but comprehensive mathematical model of the Li-S battery cell self-discharge based on the shuttle current was developed and is presented The shuttle current values for the model parameterization were obtained from the direct shuttle current measurements.
About: This article is published in Journal of Power Sources.The article was published on 2016-12-30 and is currently open access. It has received 24 citations till now. The article focuses on the topics: Self-discharge & State of charge.

Summary (4 min read)

1. Introduction

  • Lithium-Sulfur (Li-S) batteries represent a promising alternative to the Lithium-ion battery chemistry, due to their high theoretical limits in terms of specific capacity (i.e. 1672 Ah kg-1) and specific energy (i.e. 2600 Wh kg-1).
  • Furthermore, they are expected to become a cheaper and more environmentally friendly solution, mainly due to the use of sulfur, which is an abundant and benign element.
  • A mechanistic model of the polysulfide shuttle causing the self-discharge of the Li-S battery cells was presented in [8].
  • The self-discharge current was identified to be proportional to the square root of the idling time.
  • Furthermore, a methodology for direct shuttle current measurement was proposed in [12], where its results were analyzed and validated using the one-dimensional phenomenological model, which is based on Nernst and species concentrations equations.

2. Methodology

  • The work flow followed in this paper is summarized and presented in Fig.
  • At first, the measurements were performed and they are described in Section 2.1 for direct shuttle current measurements and in Section 2.2 for the self-discharge model validation measurements.
  • Later on, there were considered three fitting cases.
  • Each of these fitting cases parameterize the selfdischarge model and its accuracy is later validated in Section 3.2 by an use of the validation measurements (Section 2.2) and the SOC estimation model for the validation (Section 2.3) with the consideration of the total capacity concept (Section 2.4).
  • Ah long life chemistry Li-S pouch cell manufactured by OXIS Energy.

2.1 Direct Shuttle Current Measurement

  • The applied test procedure for the direct shuttle current measurement is based on the methodology presented in [12] and illustrated in Fig.
  • The second cycle was used for the cell’s capacity check and its calculation for the further procedure steps.
  • In practice, due to the noise in the voltage signal, the reliable value of the OCV was determined when the battery voltage dropped from the maximum point by 0.6 mV (three times the value of the battery test station accuracy which was equal to 0.2 mV) as it is presented in Fig.
  • The voltage and current signals during the direct shuttle current measurement procedure are shown in Fig. 3 for DOD equal to 10 % at 35 °C.

2.4 Concept of the total capacity of the Li-S batteries

  • The standard practice to determine the capacity of Li-S battery cells is to continuously discharge before-hand fully charged battery by a specific current at a specific temperature.
  • The obtained discharged capacity is considered as the capacity of the cell at those conditions.
  • As the polysulfide shuttle is present during the Li-S cell discharging, it causes self-discharge, which consequently reduces the measured capacity.
  • Csd is obtained from the simulation of the cell’s continuous discharge with Ccdch replacing Ct in (1).
  • Moreover, the Ish is excluded from the coulomb counting in (1) and it is integrated and recorded separately.

3. Measurement Results and Modelling

  • The current profiles obtained from the constant voltage charging steps during the direct shuttle current measurements, at 35 °C, are presented in Fig.
  • Due to the accuracy of the test station, extra noise is appearing at the current values lower than 0.06 A.
  • In order to get a higher accuracy of the measured shuttle current values, the measurement can be repeated using equipment dedicated for lower current ranges.
  • For the demonstration purposes of the model, in this paper, it is considered sufficient to take an average of the last ten minutes of the current profile during constant voltage charging step as the value for the shuttle current.
  • The measured shuttle current values for pre-determined DOD points.

3.1.1 Fitting Case 1

  • The first fitting step, referred as Fitting Case 1 (FC1), was performed by fitting the experimentally determined direct shuttle current values against the DOD points (see Fig. 6).
  • For the last DOD level, when during the battery cell relaxation period of 12 hours a peak voltage value was not detected (as described in the methodology in the previous section), a shuttle current value equal to zero was considered for fitting purposes.
  • The considered DOD levels are shown in Table I for FC1 and 35 °C.
  • These predetermined DOD points might not accurately correspond to the actual DOD levels of the cell as the influence of the shuttle current was not considered during the measurement procedure.

3.1.2 Fitting Case 2

  • Therefore, for the Fitting Case 2 (FC2), it was assumed that the self-discharge was ongoing already during the discharging steps, during the relaxation periods before the constant voltage charging step, and during the constant voltage charging step in the characterization experiment, as it is illustrated in Fig.
  • The time values of discharging and relaxation were computed and multiplied by the measured shuttle current value for the first DOD point (i.e. 2 %), which provided an estimate of the ampere-hours lost due to self-discharge during that period.
  • During the previous one hour and fifty minutes, the shuttle current is only partially compensated as the external current is lower.
  • Therefore, the amount of the self-discharged ampere-hours can be obtained by integration of the area above the current curve in a rectangle from the beginning of the constant voltage charging up to one hour and fifty minutes time coordinates.
  • The same procedure was repeated for the remaining DOD points, considering also the correction from the previous DOD point.

3.1.3 Fitting Case 3

  • For the further improvement of the model, the Fitting Case 3 (FC3) was applied to obtain the total capacity.
  • The Simulink model, including the self-discharge model obtained at the end of FC2, was fed by the current profile obtained from the direct current shuttle procedure.
  • Thus, the DOD points, corresponding to the shuttle current values, were extracted and are presented in Table I for 35 °C.
  • The parameters c, d, e and f of the shuttle current model for all the fitting cases are presented in Table II.
  • The presented fitting procedure with all three fitting cases and their steps are visualized in Fig. 7.

3.2 Validation of the self-discharge model

  • For the validation of the self-discharge model, four validation measurements were performed according to the procedure described in Section 2.2.
  • The validation cases consider various temperature conditions, idling times and initial DOD levels.
  • A comparison of the accuracy values of the developed self-discharge model for the different used fitting cases is shown in Table III.
  • The relative errors are noticeably reduced by moving from FC1 to FC2, except the Validation Case 1, where only a minor increase is observed.
  • The error reduction implies the correctness of the assumptions used for FC2 and that the self-discharge due to the polysulfide shuttle is still present, no matter if the Li-S battery is in charging, relaxation or discharging stage.

4.1 SOC reference frame & cell history effect

  • The challenging part of the integration of the presented self-discharge model into any other model is that the battery performance model has to have the same DOD/SOC reference frame in order that the dependency states to be matched.
  • Due to the ‘rate capacity effect’ [14], the available battery capacity varies according the applied current.
  • In [15], for practical reasons, the mixed pulse discharge was used to determine Ccdch.
  • Therefore, the DOD of the performance model has to be converted into DOD of the self-discharge model at its input.

4.2 Open-circuit voltage based self-discharge model

  • Alternatively, the DOD dependence of the self-discharge model can be replaced by the open-circuit voltage (OCV) dependence.
  • By following this approach, the shuttle current values related to the OCV are presented in Fig. 8, where it is important to note that this relation is valid only for OCV values at the side of the high voltage plateau.
  • The OCV values in the practical use can be obtained for example by online parameter identification techniques [16].
  • Based on the curve fitting of the shuttle current dependency on DOD and temperature, a simple mathematical model for the self-discharge estimation of Li-S batteries was obtained.
  • The developed model was successfully validated by the experiments considering various conditions with a relative error smaller than 7 %.

Acknowledgments

  • This work has been part of the ACEMU-project.
  • The authors gratefully acknowledge the Danish Council for Strategic Research (1313-00004B) and EUDP (1440-0007) for providing financial support and would like to thank OXIS Energy for supplying the Lithium-Sulfur battery cells.

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Citations
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Journal ArticleDOI
TL;DR: In this article, a simple ageing model is proposed for the fading of lithium-sulfur (Li-S) cell capacity with the number of cycles, considering that the degradation of the cell is simultaneously influenced by the 100% depth-of-discharge cycling and the cell staying at a charged state.
Abstract: A simple ageing model is proposed for the fading of lithium–sulfur (Li–S) cell capacity with the number of cycles The model could be applied for the ageing description of cells with an unknown internal structure in a wide range of engineering applications Cycle profile that patterns with the real-life operation of cells is proposed Thus, the degradation of the cell is simultaneously influenced by the 100% depth-of-discharge cycling and the cell staying at a charged state The proposed model is described by the differential equation considering that the decrease of cell capacity per cycle is proportional to the product of cycle number and the charge available to be discharged within the appropriate cycle The model covers the degradation processes dominant in the initial stage of ageing, where the cell capacity decreases from 100% to about 25% of its initial value The solution of the proposed differential equation is an analytical function that requires only three fitted parameters The dependence of model parameters on the charge/discharge current rate is shown for studied Li–S cells Possible sources of degradation, such as the decrease of electrode effective area and the decrease of potential barrier on the electrode/electrolyte interface, are determined from the evaluation of the coulombic efficiency of the charge/discharge process

7 citations


Cites background from "A self-discharge model of Lithium-S..."

  • ...The leakage current on the discharged cell is negligible within the 1 h time interval [40], [41]....

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Book ChapterDOI
01 Jan 2019
TL;DR: Electrochemical models, mathematical models, and electrical models of batteries are discussed, and the use of adaptive neuro-fuzzy inference systems (ANFISs) is introduced.
Abstract: Electrochemical models, mathematical models, and electrical models of batteries are discussed in this section. The properties and models of a lead-acid battery are presented in this section. Models of lithium-ion cells, their parameters, and their relation to the lithium sulfur cells are discussed. The model for the polysulfide transfer in a Li-S cell is described in the section. A one-dimensional mechanical model (1D) based on the Nernst-Planck equations for dilute solutions is also discussed. The Kumaresan model and some electrochemical models for a Li-S cell are discussed. A zero-dimensional model and equivalent circuit network (ECN) are described. The mathematical model of the Li-S cell self-discharge based on the shuttle current is reported. Use of the Kalman filter family, i.e., extended Kalman filter (EKF), unscented Kalman filter (UKF), and particle filter techniques are discussed. The use of adaptive neuro-fuzzy inference systems (ANFISs) is also introduced. Several models of a Na-S battery are announced in this section. The most commonly used simple battery model is discussed in this section. The Thevenin battery model is discussed in the section. A modified battery model useful for a Na-S battery is discussed in this section. Charging and discharging resistance used in the modified battery model are explained in the section. Resistance during cycles loading-discharging used in the modified battery model is explained in the section. Battery circuit voltage used in the modified battery model is explained in the section. A simulation model in the PSCAD/EMTDC program useful for the Na-S battery is discussed in the section.

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Journal ArticleDOI
TL;DR: In this article , the authors performed a long-term calendar aging test on 3.4 Ah Li-S pouch cells and found that the decrease in performance over two years of calendar aging was more pronounced for temperature than for depth-of-discharge.

1 citations

Journal ArticleDOI
TL;DR: In this paper , a method for predicting battery self-discharge voltage drop based on pre-classifier is proposed, where features for predicting the SDV-drop are obtained in two ways: direct extraction from the charge and discharge curve and generation based on the classifier.

1 citations

References
More filters
Journal ArticleDOI
TL;DR: In this paper, the authors report a quantitative analysis of the shuttle phenomenon in Li/S rechargeable batteries and present experimental evidence that selfdischarge, charge-discharge efficiency, charge profile, and overcharge protection are all facets of the same phenomenon.
Abstract: This work reports a quantitative analysis of the shuttle phenomenon in Li/S rechargeable batteries. The work encompasses theoretical models of the charge process, charge and discharge capacity, overcharge protection, thermal effects, self-discharge, and a comparison of simulated and experimental data. The work focused on the features of polysulfide chemistry and polysulfide interaction with the Li anode, a quantitative description of these phenomena, and their application to the development of a high-energy rechargeable battery. The objective is to present experimental evidence that self-discharge, charge-discharge efficiency, charge profile, and overcharge protection are all facets of the same phenomenon.

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TL;DR: In this paper, the methods for monitoring the battery state of charge, capacity, impedance parameters, available power, state of health, and remaining useful life are reviewed with the focus on elaboration of their strengths and weaknesses for the use in on-line BMS applications.

827 citations

Journal ArticleDOI
TL;DR: In this paper, a review of a range of analytical studies and physical models for Li-S batteries is presented, showing that experimental understanding is well ahead of state-of-the-art models.
Abstract: Lithium sulfur (Li–S) batteries are one of the most promising next generation battery chemistries with potential to achieve 500–600 W h kg−1 in the next few years. Yet understanding the underlying mechanisms of operation remains a major obstacle to their continued improvement. From a review of a range of analytical studies and physical models, it is clear that experimental understanding is well ahead of state-of-the-art models. Yet this understanding is still hindered by the limitations of available techniques and the implications of experiment and cell design on the mechanism. The mechanisms at the core of physical models for Li–S cells are overly simplistic compared to the latest thinking based upon experimental results, but creating more complicated models will be difficult, due to the lack of and inability to easily measure the necessary parameters. Despite this, there are significant opportunities to improve models with the latest experimentally derived mechanisms. Such models can inform materials research and lead to improved high fidelity models for controls and application engineers.

825 citations

Journal ArticleDOI
TL;DR: It is shown here that consistent progress has been achieved, to the point that this battery is now considered to be near to industrial production, however, the performance of present lithium-sulfur batteries is still far from meeting their real energy density potentiality.

458 citations

Journal ArticleDOI
TL;DR: Simplified models based on porous electrode theory are used to describe the discharge of rechargeable lithium batteries and derive analytic expressions for the specific capacity against discharge rate in terms of the relevant system parameters as mentioned in this paper.
Abstract: Simplified models based on porous electrode theory are used to describe the discharge of rechargeable lithium batteries and derive analytic expressions for the specific capacity against discharge rate in terms of the relevant system parameters. The resulting theoretical expressions are useful for design and optimization purposes and can also be used as a tool for the identification of system limitations from experimental data. Three major cases are considered that are expected to hold for different classes of systems being developed in the lithium battery industry. The first example is a cell with solution phase diffusion limitations for the two extreme cases of a uniform and a completely nonuniform reaction rate distribution in the porous electrode. Next, a discharge dominated by solid phase diffusion limitations inside the insertion electrode particles is analysed. Last, we consider an ohmically-limited cell with no concentration gradients and having an insertion reaction whose open-circuit potential depends linearly on state of charge. The results are applied to a cell of the form Li|solid polymer electrolyte|LiyMn2O4 in order to illustrate their utility.

224 citations