Communication—Identifying and Managing Reversible Capacity Losses that Falsify Cycle Ageing Tests of Lithium-Ion Cells

Burrell, Robert; Zulke, Alana Aragon; Keil, Peter; Hoster, Harry E.

doi:10.1149/1945-7111/abbce1

Cited by 18 publications

(21 citation statements)

References 24 publications

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“…DVA tracking of cell degradation [16,28,29,44] as illustrated in Figure 9 relies on the DVA markers Q1 to Q5 (all expressed in Ah values) as summarized in Table 3. The left side (Figures 9a, c, e) shows voltage profiles and DVA plots for a cell aged at 0 % SoC and 25 °C.…”

Section: Resultsmentioning

confidence: 99%

High‐Energy Nickel‐Cobalt‐Aluminium Oxide (NCA) Cells on Idle: Anode‐ versus Cathode‐Driven Side Reactions

Zulke

Keil³

et al. 2021

Batteries & Supercaps

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We report on the first year of calendar ageing of commercial high‐energy 21700 lithium‐ion cells, varying over eight state of charge (SoC) and three temperature values. Lithium‐nickel‐cobalt‐aluminium oxide (NCA) and graphite with silicon suboxide (Gr‐SiOx) form cathodes and anodes of those cells, respectively. Degradation is fastest for cells at 70–80 % SoC according to monthly electrochemical check‐up tests. Cells kept at 100 % SoC do not show the fastest capacity fade but develop internal short circuits for temperatures T≥40 °C. Degradation is slowest for cells stored close to 0 % SoC at all temperatures. Rates of capacity fade and their temperature dependencies are distinctly different for SoC values below and above 60 %, respectively. Differential voltage analyses, apparent activation energy analysis, and endpoint slippage tracking provide useful insights into the degradation mechanisms and the respective roles of anode and cathode potential. We discuss how reversible losses of lithium might play a role in alleviating the rate of irreversible losses on commercial cells.

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Section: Resultsmentioning

confidence: 99%

High‐Energy Nickel‐Cobalt‐Aluminium Oxide (NCA) Cells on Idle: Anode‐ versus Cathode‐Driven Side Reactions

Zulke

Keil³

et al. 2021

Batteries & Supercaps

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“…The cell examined in the present study was found to have an anode area ≈ 790 cm 2 and cathode area ≈ 740 cm 2 , resulting in an overhang ≈ 6%. The resulting non-uniform lithium distribution in the anode material could lead to higher lithium disorder and hence a greater entropy change due to disordered Stage II configurations [59,60,25]; anode overhang areas can also lead to reversible LLI [61]. The net result of all of these effects may lead to some disparities between combined entropy from half-cells and the full-cell entropy change, particularly at the boundaries between graphite phase transitions.…”

Section: Half-cell Entropy Contributionsmentioning

confidence: 99%

“…This resulted in calendar aged cells experiencing a recovery in LLI together with a less pronounced increase in LAM NE . This suggests recovery of capacity from the 'anode overhang' effect [61]. Geometrically, anode overhang is defined as an additional anode area which is not directly opposed by the cathode [76].…”

Section: Impact Of Silicon On Entropy Profilesmentioning

confidence: 99%

Entropy profiling for the diagnosis of NCA/Gr-SiOx Li-ion battery health

Wojtala¹,

Zulke²,

Burrell³

et al. 2022

Preprint

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Graphite-silicon (Gr-Si) blends have become common in commercial Li-ion battery negative electrodes, offering increased capacity over pure graphite. Lithiation/delithiation of the silicon particles results in volume changes, which may be associated with increased hysteresis of the open circuit potential (OCP). The OCP is a function of both concentration and temperature. Entropy change measurement--which probes the response of the OCP to temperature--offers a unique battery diagnostics tool. While entropy change measurements have previously been applied to study degradation, the implications of Si additives on the entropy profiles of commercial cells have not been explored.Here, we use entropy profiling to track ageing markers in the same way as differential voltage analysis. In addition to lithiation/delithiation hysteresis in the OCP of Gr-Si blends, cells with Gr-Si anodes also exhibit differences in entropy profile depending on cycling direction, reflecting degradation-related morphological changes. For cycled cells, entropy change decreased during discharge, likely corresponding to graphite particles breaking and cracking. However, entropy change during charge increased with cycling, likely due to the volume change of silicon. Over a broad voltage range, these combined effects led to the observed rise in entropy hysteresis with age. Conversely, for calendar aged cells entropy hysteresis remained stable.

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“…In this way, anodetocathode ratios in commercial cells are always larger than 1. The anode region which has no cathode counterpart is often called overhang area, and lithium movement from/to these regions are known to cause reversible capacity effects taking place at varied timescales [36].…”

Section: Geometric Parameters and Physical Characterisationmentioning

confidence: 99%

Parametrisation and Use of a Predictive DFN Model for a High-Energy NCA/Gr-SiOx Battery

Zulke

Korotkin

Foster

et al. 2021

J. Electrochem. Soc.

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We demonstrate the predictive power of a parametrised Doyle-Fuller-Newman (DFN) model of a commercial cylindrical (21700) lithium-ion cell with NCA/Gr-SiOx chemistry. Model parameters result from the deconstruction of a fresh commercial cell to determine/confirm chemistry and microstructure, and also from electrochemical experiments with half-cells built from electrode samples. The simulations predict voltage proles for (i) galvanostatic discharge and (ii) drive-cycles. Predicted voltage responses deviate from measured ones by <1% throughout at least 95% of a full galvanostatic discharge, whilst the drive cycle discharge is matched to a 1-3% error throughout. All simulations are performed using the online computational tool DandeLiion, which rapidly solves the DFN model using only modest computational resource. The DFN results are used to quantify the irreversible energy losses occurring in the cell and deduce their location. In addition to demonstrating the predictive power of a properly validated DFN model, this work provides a novel simplifed parametrisation work that can be used to accurately calibrate an electrochemical model of a cell.

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Communication—Identifying and Managing Reversible Capacity Losses that Falsify Cycle Ageing Tests of Lithium-Ion Cells

Cited by 18 publications

References 24 publications

High‐Energy Nickel‐Cobalt‐Aluminium Oxide (NCA) Cells on Idle: Anode‐ versus Cathode‐Driven Side Reactions

High‐Energy Nickel‐Cobalt‐Aluminium Oxide (NCA) Cells on Idle: Anode‐ versus Cathode‐Driven Side Reactions

Entropy profiling for the diagnosis of NCA/Gr-SiOx Li-ion battery health

Parametrisation and Use of a Predictive DFN Model for a High-Energy NCA/Gr-SiOx Battery

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