Production caused variation in capacity aging trend and correlation to initial cell performance

Baumhöfer, Thorsten; Brühl, Manuel; Rothgang, Susanne; Sauer, Dirk Uwe

doi:10.1016/j.jpowsour.2013.08.108

Cited by 310 publications

(202 citation statements)

References 12 publications

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“…Maximizing the lifetime of a battery pack stipulates that all of its cells degrade in nearly identical fashion so that there are no weak links. To date, variations between cells upon aging were shown to exist [3][4][5][6], and it is very difficult, if not impossible, to forecast the cycle-life of millions of cells in a timely and resource-efficient manner. This is a problem because an intrinsic degradation variability that is too large or has yet to be quantified has several implications.…”

Section: Introductionmentioning

confidence: 99%

“…The extent of initial cell-to-cell variations within a batch of cells, although not reported often enough, has been the topic of multiple studies in the literature [4][5][6][8][9][10][11][12][13]. Researchers have reported statistical studies on 12 [14], 50 [5,15,16], 100 [17][18][19][20], and 1000 [8][9][10]21] cells.…”

Section: Introductionmentioning

confidence: 99%

“…Researchers have reported statistical studies on 12 [14], 50 [5,15,16], 100 [17][18][19][20], and 1000 [8][9][10]21] cells. All of these studies determined that cells within a batch are different and that these differences need to be quantified and taken into consideration.…”

Section: Introductionmentioning

confidence: 99%

“…Few studies focused on long-term considerations [3][4][5][6]. In these studies, a noticeable spread in cycle-lives was reported.…”

Section: Introductionmentioning

confidence: 99%

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Intrinsic Variability in the Degradation of a Batch of Commercial 18650 Lithium-Ion Cells

2018

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Abstract:The use of lithium batteries for power and energy-hungry applications has risen drastically in recent years. For such applications, it is necessary to connect the batteries in large assemblies of cells in series and parallel. With a large number of cells operating together, it is necessary to understand their intrinsic variabilities, not only at the initial stage but also upon aging. In this study, we studied a batch of commercial cells to address their initial cell-to-cell variations and also the variations induced by cycling. To do so, we not only tracked several metrics associated with cell performance, the maximum capacity, the resistance, and the rate capability but also the degradation mechanism via a non-invasive quantification of the loss of lithium inventory (LLI), the loss of active material (LAM) and the kinetic degradation on both electrodes. We found that, even with small initial cell-to-cell variations, significant variations will be observed upon aging because the cells degrade at a different pace. We also observed that these variations were not correlated with the initial variations.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

“…Few studies focused on long-term considerations [3][4][5][6]. In these studies, a noticeable spread in cycle-lives was reported.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Intrinsic Variability in the Degradation of a Batch of Commercial 18650 Lithium-Ion Cells

2018

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“…By connecting more cells in parallel, the redundancy is enhanced as a single cell fault does not necessarily lead to a failure of the complete system. Moreover, there is always a spread in the aging of the single cell capacities as shown in [35]. This can be statistically lowered by building the mean over several cells in a parallel connection [21].…”

Section: System Designmentioning

confidence: 99%

Battery Design for Successful Electrification in Public Transport

et al. 2015

Self Cite

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Abstract:Public transport is an especially promising sector for full electric vehicles due to the high amount of cycles and predictable workload. This leads to a high amount of different vehicle concepts ranging from large batteries, designed for a full day of operation without charging, to fast-charging systems with charging power up to a few hundred kilowatts. Hence, many different issues have to be addressed in the whole design and production process regarding high-voltage (HV) batteries for buses. In this work, the design process for electric public buses is analyzed in detail, based on two systems developed by the research projects Smart Wheels/econnect and SEB eÖPNV. The complete development process starting, with the demand analysis and the operating scenario, including the charging routine, is discussed. This paper also features details on cell selection and cost estimations as well as technical details on the system layout, such as the management system and passive components as well as thermal management.

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Data‐Driven Fast Clustering of Second‐Life Lithium‐Ion Battery: Mechanism and Algorithm

Ran

Zhou

Chen

et al. 2020

Advcd Theory and Sims

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While electrical vehicles (EVs) are expanding rapidly and getting more and more popular in the market, researchers have started to leverage the remaining capacity of used or to‐be‐retired batteries for their second‐life applications. It is crucial to develop a fast and efficient technology to first sort them and then extend their life while delivering energy, waste reduction, and economic benefits. In this work, a pulse clustering model embedded with improved bisecting K‐means algorithm is developed to effectively sort retired batteries with life cycles ranging from new to an end‐of‐life state. The relevance of selected variables is rigorously validated, reaching the accuracy as high as 88% compared with the traditional full charge–discharge test. To note, the test time has largely reduced from hours to minutes. This data‐driven clustering modeling with fast pulse test is a promising approach for clustering lithium‐ion batteries, which is demonstrated with a home‐built and high throughput intelligent clustering machine. In general, the technology opens a new generation of battery clustering, improving the efficiency and accuracy over the past semiempirical approaches.

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Production caused variation in capacity aging trend and correlation to initial cell performance

Cited by 310 publications

References 12 publications

Intrinsic Variability in the Degradation of a Batch of Commercial 18650 Lithium-Ion Cells

Intrinsic Variability in the Degradation of a Batch of Commercial 18650 Lithium-Ion Cells

Battery Design for Successful Electrification in Public Transport

Data‐Driven Fast Clustering of Second‐Life Lithium‐Ion Battery: Mechanism and Algorithm

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