Failure statistics for commercial lithium ion batteries: A study of 24 pouch cells

Harris, Stephen J.; Harris, David J.; Li, Chen

doi:10.1016/j.jpowsour.2016.12.083

Cited by 162 publications

(128 citation statements)

References 53 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%

“…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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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%

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

2018

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“…However, due to variations in internal characteristics and differences in operating conditions, batteries may suffer from imbalance problems, mainly imbalance of remaining effective capacity and state-of-charge (SOC) [2,3]. Imbalance will reduce the total effective capacity of battery pack and shorten charge-discharge cycle life.…”

Section: Introductionmentioning

confidence: 99%

A highly-integrated and efficient commercial distributed EV battery balancing system

Chen

Jun

Zheng

et al. 2018

IEICE Electron. Express

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This paper focuses on the imbalance problem of serial cells in lithium-ion batteries applied in electric vehicles (EVs). In order to meet more strict requirements of size, efficiency, cost, and reliability in commercial application, a highly-integrated and efficient distributed battery balancing system is developed. In the system, each balancing node (BN) and its controller, a designed specific integrated circuit (IC), are independent, distributed and integrated in an IC-packaged module. Besides, a 50% stateof-charge (SOC)-aligned balancing strategy is proposed and applied. The experiment and commercial application results show the designed balancing system performs excellently in improving battery capacity and extending cycle life.

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“…Similarly, after analyzing the failure cycles of the lithium ion battery, Harris et al [26] concluded that the variation in failure times of the batteries was wide among the various cells. Despite the poor failure estimation results obtained by them using the three-parameter Weibull distribution function [26], they also obtained results that showed better fits to the experimental data with a two-parameter Weibull distribution as well as the normal distribution.…”

Section: Introductionmentioning

confidence: 99%

Statistical Characterization of the State-of-Health of Lithium-Ion Batteries with Weibull Distribution Function—A Consideration of Random Effect Model in Charge Capacity Decay Estimation

Ossai

Raghavan

2017

Batteries

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Effective prognosis of lithium-ion batteries involves the inclusion of the influences of uncertainties that can be incorporated through random effect parameters in a nonlinear mixed effect degradation model framework. This study is geared towards the estimation of the reliability of lithium-ion batteries, using parametric effects determination involving uncertainty, using a multiphase decay patterned sigmoidal model, experimental data and the Weibull distribution function. The random effect model, which uses Maximum Likelihood Estimation (MLE) and Stochastic Approximation Expectation Maximization (SAEM) algorithm to predict the parametric values, was found to estimate the remaining useful life (RUL) to an accuracy of more than 98%. The State-of-Health (SOH) of the batteries was estimated using the Weibull distribution function, which is found to be an appropriate formulation to use.

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Failure statistics for commercial lithium ion batteries: A study of 24 pouch cells

Abstract: 2017-08-30T02:06:41

Cited by 162 publications

References 53 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

A highly-integrated and efficient commercial distributed EV battery balancing system

Statistical Characterization of the State-of-Health of Lithium-Ion Batteries with Weibull Distribution Function—A Consideration of Random Effect Model in Charge Capacity Decay Estimation

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