Cell-balancing currents in parallel strings of a battery system

Dubarry, Matthieu; Devie, Arnaud; Liaw, Bor Yann

doi:10.1016/j.jpowsour.2016.04.125

Cited by 92 publications

(75 citation statements)

References 34 publications

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“…The IC curve of a lithium-ion cell results from the weighted convolution of the IC curves of both electrodes. 6 LTO presents a nearly constant potential plateau, which indicates that LTO undergoes a phase transformation. [14][15][16][17][18][19] Therefore, in the context of these LTO || NMC cells, the LTO electrode behaves in a way reminiscent of a reference electrode.…”

Section: Resultsmentioning

confidence: 98%

“…[1][2][3][4][5][6] Although our initial demonstration of the diagnostics capabilities was focused on a graphite || LiFePO 4 cell, the method can be applied to other chemistries. In this work, we demonstrate the utility of this approach in diagnosing abused Li 4 The LTO || NMC chemistry offers a number of benefits in designing high-power Li-ion batteries (LIB), including attractive cycle life to attain low life-cycle costs, high rate capability for energy storage system (ESS) ramping and grid stabilization applications, and high power capability for hybrid electric vehicle (HEV) applications.…”

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confidence: 99%

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Overcharge Study in Li₄Ti₅O₁₂Based Lithium-Ion Pouch Cell

Devie

Dubarry

Liaw

2015

J. Electrochem. Soc.

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Overcharge tolerance has often been studied from a safety standpoint (e.g. thermal runaway), but rarely from a durability standpoint. A quantitative battery diagnosis was developed to analyze an overcharge event in a commercial Li 4 Ti 5 O 12 || LiNi 1/3 Mn 1/3 Co 1/3 O 2 lithium-ion pouch cell and the subsequent cycle aging behavior. Using an electrochemical inference technique and the degradation emulation 'alawa toolbox, quantitative diagnoses of two cells enduring the same cycle aging conditions, with or without the overcharge event respectively, were performed. The baseline cell, which suffered from loss of active material in the positive electrode along with loss of lithium inventory in side-reactions, demonstrated excellent capacity retention (with 99.6% after 700 cycles). In contrast, the overcharged cell suffered from a larger capacity fade (15% immediately after the overcharge, and 23% after 700 cycles). We identified the loss of active material in the negative electrode as the culprit for capacity fade by the overcharge. Loss of active material in the positive electrode as well as loss of lithium inventory were also identified but did not contribute to the capacity fade. A hypothesis of localized blockage of the ionic conduction pathway due to gas accumulation was proposed as the mechanism driving the observed degradation.

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Section: Resultsmentioning

confidence: 98%

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confidence: 99%

Overcharge Study in Li₄Ti₅O₁₂Based Lithium-Ion Pouch Cell

Devie

Dubarry

Liaw

2015

J. Electrochem. Soc.

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“…23 Here, the results and verification of the SOC estimates by the anakonu method are discussed. A key question is to address the higher capacity fade in the pack than those in the cells.…”

Section: Resultsmentioning

confidence: 99%

State-of-Charge Determination in Lithium-Ion Battery Packs Based on Two-Point Measurements in Life

Dubarry

Truchot

Devie

et al. 2015

J. Electrochem. Soc.

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The state-of-charge (SOC) estimation is of extreme importance for the reliability and safety of battery operation. How to estimate SOC for an assembly of cells in a battery pack remains a subject of great interest. Here a viable method for SOC determination and tracking for multi-cell assemblies is proposed and validated. Using 3S1P (three in series and one in parallel) strings as an example, an inference of SOC is illustrated in a battery assembly based on a correct open pack voltage (OPV) versus SOC (i.e. OPV = f (SOC)) function. The proposed method only requires the measurements of the rest cell voltages of the single cells at two distinct occasions. Rechargeable lithium-ion batteries (LIB) continue being considered viable choices for mobile power and energy storage applications. Yet, a reliable deployment of LIB in powertrains remains very challenging, primarily due to the requirements for reliable multi-cell assemblies to provide high energy and power. Better capability to characterize battery pack performance, identify aging mechanism, and perform state-of-charge (SOC) estimation is desired to achieve great efficiency.1,2 In our previous work, we devoted substantial effort to understand the behavior of cells in a pack and the impact of cell variability on pack performance. 3,4 We also reported a diagnostic and prognostic approach to identify and quantify cell-aging mechanisms in the course of cycle aging for a number of cell chemistries.5-11 To enable these methodologies, the SOC determination is the most vital component among all for accurate operation of the battery management system (BMS).1 In our latest work, 12 we showed that the most accurate method to obtain the SOC of a battery pack is either by measuring the residual capacity (Q res ) against the maximum pack capacity (Q max ); i.e. pack SOC = Q res /Q max , or by measuring the rest pack voltage (RPV) to infer SOC based on a SOC versus open pack voltage (OPV) function; i.e. pack SOC = f -1 (OPV). Both methods, however, suffer from their inoperability in practical applications, due to (1) in the case of capacity measurements, the uncertainty related to Q res in a duty cycle, (2) the fade in the Q max over lifetime, and (3) in the case of voltage-based measurements, the need for accurate OPV across the full SOC range. Therefore, a simple and practical method for SOC estimation remains very desirable.For a single cell (SC), the open circuit voltage (OCV) versus SOC function is often preferred for SOC determination because in principle, and at the beginning-of-life (BOL) of the cell, the sc SOC = f -1 (OCV) function is universal for cells of the same chemistry, disregarding size or geometry.3 Therefore, this OCV = f(SOC) function only needs to be determined once and for all from a single cell of a specific design. Upon aging, uncertainties to this OCV = f(SOC) function are introduced due to aging-pathway dependence.6 Such variations could be predicted as a function of duty cycle characteristics using the mechanistic model reported in our prior work. 5...

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“…Within [45], the authors discuss the challenge of quantifying energy capacity for a complete 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 14 module assembly or battery pack, taking into account cell-to-cell variations [46] and the unmeasurable current flows that may occur within the battery module when cells are connected electrically in parallel [47]. A comprehensive review of different capacity (and thus SOC) estimation methods for inclusion within the BMS is presented within [3,48].…”

Section: Review Of Academic Literaturementioning

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Accelerated energy capacity measurement of lithium-ion cells to support future circular economy strategies for electric vehicles

Groenewald

Grandjean

Marco

2017

Renewable and Sustainable Energy Reviews

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Within the academic and industrial communities there has been an increasing desire to better understand the sustainability of producing vehicles that contain embedded electrochemical energy storage. Underpinning a number of studies that evaluate different circular economy strategies for the electric vehicle (EV) or Hybrid electric vehicle (HEV) battery system are implicit assumptions about the retained capacity or State of Health (SOH) of the battery. International standards and best-practice guides exist that address the performance evaluation of both EV and HEV battery systems. However, a common theme is that the test duration can be excessive and last for a number of hours. The aim of this research is to assess whether energy capacity measurements of Li-ion cells can be accelerated; reducing the test duration to a value that may facilitate further EOL options. Experimental results are presented that highlight it is possible to significantly reduce the duration of the battery characterisation test by 70% -90% while still retaining levels of measurement accuracy for retained energy capacity in the order of 1% for cell temperatures equal to 25 0 C. Even at elevated temperatures of 40 0 C, the peak measurement error was found to be only 3%. Based on these experimental results, a simple cost-function is formulated to highlight the flexibility of the proposed test framework. This approach would allow different organizations to prioritize the relative importance of test accuracy verses experimental test time when grading used Li-ion cells for different end-of-life (EOL) applications.

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Cell-balancing currents in parallel strings of a battery system

Cited by 92 publications

References 34 publications

Overcharge Study in Li₄Ti₅O₁₂Based Lithium-Ion Pouch Cell

Overcharge Study in Li₄Ti₅O₁₂Based Lithium-Ion Pouch Cell

State-of-Charge Determination in Lithium-Ion Battery Packs Based on Two-Point Measurements in Life

Accelerated energy capacity measurement of lithium-ion cells to support future circular economy strategies for electric vehicles

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Cell-balancing currents in parallel strings of a battery system

Cited by 92 publications

References 34 publications

Overcharge Study in Li4Ti5O12Based Lithium-Ion Pouch Cell

Overcharge Study in Li4Ti5O12Based Lithium-Ion Pouch Cell

State-of-Charge Determination in Lithium-Ion Battery Packs Based on Two-Point Measurements in Life

Accelerated energy capacity measurement of lithium-ion cells to support future circular economy strategies for electric vehicles

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Product

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Overcharge Study in Li₄Ti₅O₁₂Based Lithium-Ion Pouch Cell

Overcharge Study in Li₄Ti₅O₁₂Based Lithium-Ion Pouch Cell