Degradation of lithium ion batteries employing graphite negatives and nickel–cobalt–manganese oxide + spinel manganese oxide positives: Part 1, aging mechanisms and life estimation

Wang, John; Purewal, Justin; Liu, Ping; Hicks-Garner, Jocelyn; Soukazian, Souren; Sherman, Elena; Sorenson, Adam; Vu, L.H.; Tataria, Harshad; Verbrugge, Mark W.

doi:10.1016/j.jpowsour.2014.07.030

Cited by 379 publications

(282 citation statements)

References 30 publications

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“…formation and reconstruction of SEI. 20 A higher capacity fade rate at 10 • C than at 25 • C is possibly a result of lithium plating, 7,8 since internal electrode resistances increase with lower temperature and the anode potential eventually drops to potentials negative to reversible Li/Li + potential. 23 The ohmic resistance originates from the bulk chemistry of a cell, including resistance of the electrolyte, active materials and current collectors.…”

Section: Resultsmentioning

confidence: 99%

Impact of Temperature and Discharge Rate on the Aging of a LiCoO₂/LiNi_0.8Co_0.15Al_0.05O₂Lithium-Ion Pouch Cell

Keil

Schuster

et al. 2017

J. Electrochem. Soc.

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This paper presents a lithium-ion battery aging study in which pouch cells comprising a LiCoO 2 /LiNi 0.8 Co 0.15 Al 0.05 O 2 blended cathode and a graphite anode are examined. The study focuses on the impact of temperature and discharge rate on the cycle life of the tested cells. Compared to the aging behavior of other lithium-ion cells in the literature, the cells tested here are less sensitive to the discharge rate but more vulnerable to low temperature cycling. The vulnerability to low temperature mainly comes from cathode degradation, especially of the LiCoO 2 component. This is identified by electrochemical impedance spectroscopy, differential voltage analysis and incremental capacity analysis. The cells are able to achieve 3000-5000 cycles before reaching a capacity fade of 20%, also at higher discharge rates up to 5C. All in all, the high discharge rate capability could be a general advantage of pouch cells due to less mechanical and thermal stress in their geometry. Furthermore, more attention should be paid to the cathode health in low temperature applications of lithium-ion cells containing layered oxides. This paper focuses mainly on non-invasive aging detection methods for lithium-ion cells. Post-mortem results will be published in a following paper.

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Section: Resultsmentioning

confidence: 99%

Impact of Temperature and Discharge Rate on the Aging of a LiCoO₂/LiNi_0.8Co_0.15Al_0.05O₂Lithium-Ion Pouch Cell

Keil

Schuster

et al. 2017

J. Electrochem. Soc.

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“…P , could be acquired in combination with (21) and (22). The energy consumption of driving cycles when vehicle is driving (Q , ) could be accessed in combination with (20) (21) and (22), as Equation (23) shows.…”

Section: Vehicle Electricity Consumption Costmentioning

confidence: 99%

“…Often, battery cycle life tests are performed under accelerating conditions such as elevated temperatures, high DOD or high current rates. Based on Arrhenius Law and a large number of test data, Wang et al [19,20] established a semi-empirical life model to predict calendar-life loss. This model is widely adopted and further developed, but for actual vehicle usage it should be modified because the battery is subjected to complex load profiles.…”

Section: Introductionmentioning

confidence: 99%

An Optimized Energy Management Strategy for Preheating Vehicle-Mounted Li-Ion Batteries at Subzero Temperatures

Zhu

Min

et al. 2016

Preprint

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This paper presents an optimized energy management strategy for Li-ion power batteries used on electric vehicles (EVs) at low temperatures. Under low-temperature environments, EVs suffer a sharp driving range loss resulted from the energy and power capability reduction of the battery. Simultaneously, because of Li plating, battery degradation becomes an increasing concern as temperature drops. All these factors could greatly increase the total vehicle operation cost. Prior to battery charging and vehicle operating, preheating battery to a battery-friendly temperature is an approach to promote energy utilization and reduce total cost. Based on the proposed LiFePO4 battery model, the total vehicle operation cost under certain driving cycles is quantified in the present paper. Then given a certain ambient temperature, a target temperature of preheating is optimized under the principle of minimizing total cost. As for the preheating method, a liquid heating system is also implemented on an electric bus. Simulation results show that the preheating process becomes increasingly necessary with a decreasing ambient temperature; however, the preheating demand declines as driving range grows. Vehicle tests verify that the preheating management strategy proposed in this paper is able to save total vehicle operation cost.

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“…Consequently, it will lead to the SEI formation on the cracked surfaces, which will consume the active Lithium-ion. This diffusion-inducedstresses failure mechanism usually makes capacity fade linearly over cycles [1,10,18]. …”

mentioning

confidence: 99%

“…2 as a case of constant stress degradation tests, and the regression-based model is often used to handle this type of degradation data [6]. In the previous literature [1,10,18], capacity fading of Lithium-ion cells is generally assumed to follow a linear trend with cycles, namely:where the intercept a and slope b are unknown parameters, c(n) is the cell capacity at nth cycle.The estimators of model parameters for each cell can be obtained with the linear regression techniques. The end of life (EOL) for Lithium-ion cell is often defined as the number of charge/discharge cycles before cell capacity falls below 80% of its rated capacity [13].…”

mentioning

confidence: 99%

Cycle life prediction of lithium-ion cells under complex temperature profiles

Cheng

Pan

et al. 2016

EiN

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These studies mentioned above, however, are mainly conducted based on the cycle life tests under one or more deterministic temperature levels, in which the high-precision temperature chamber and rigid data acquisition methods are required. Unlike the laboratory testing condition, cells in the field-use condition are usually run under complex temperature profiles. Previous researches indicate that the capacity fading process of Lithium-ion cells is significantly influenced by temperature [5,7,10]. In [10], capacity fading of Lithium-ion cells can be divided into true capacity fading and temporary capacity loss. True capacity fading leads to permanent capacity loss as a result of lithium ion and active material consuming, where high temperatures will accelerate the fading rate. On the other hand, temporary capacity loss is due to the temperature drop in a certain cycle, which is somewhat recoverable if the temperature goes back. A more accurate capacity fading model can be obtained by considering these temperature effects, especially for the cells operating under field-use conditions.However, because of the difficulty in modeling the complicated temperature effects, the existing papers regarding capacity fading modeling or cycle life prediction under complex temperature profiles are very rare. In most of them, the classic regression-based approach [6] is adopted, which assumes that field conditions are deterministic or to simply use the mean value of temperatures while ignore their variability. This approach may result in significant prediction errors. For predicting the cycle life of Lithium-ion cells without the temperature chamber, this paper proposes a cycle life prediction method considering complex temperature profiles, including a cycle life test plan and an improved capacity fading model.In our test, cells experience ambient temperature that continuously varies at all times. It will lead to the variance of cell capacity. The variance contains abundant information about cycle life and the relationship between cycle life and temperature. If we can effectively mine the information from the immense performance data using data modeling methods, the cycle life of Lithium-ion cells can be predicted accurately.In this paper, firstly, the cycle life test plan for Lithium-ion cells under complex temperature profiles is introduced. Then, the classic regression-based life prediction method which ignores temperature effects is reviewed. Based on the classic method, we establish a more accurate capacity fading model, by taking into account the effects of temperature on both the actual capacity fading and the temporal capacity loss. Using the data acquired from the cycle life test, the parameters of the model are estimated. At last, the cycle life of this type of Lithium-ion cells is predicted. Experimental Testing proceduresIn the cycle life test, 6 LiFePO 4 18650 cells, which are indexed as Cell #1, Cell #2,· · ·, Cell #6 respectively, are used to charge and discharge repetitively. The parameters setup of these cells i...

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Degradation of lithium ion batteries employing graphite negatives and nickel–cobalt–manganese oxide + spinel manganese oxide positives: Part 1, aging mechanisms and life estimation

Cited by 379 publications

References 30 publications

Impact of Temperature and Discharge Rate on the Aging of a LiCoO₂/LiNi_0.8Co_0.15Al_0.05O₂Lithium-Ion Pouch Cell

Impact of Temperature and Discharge Rate on the Aging of a LiCoO₂/LiNi_0.8Co_0.15Al_0.05O₂Lithium-Ion Pouch Cell

An Optimized Energy Management Strategy for Preheating Vehicle-Mounted Li-Ion Batteries at Subzero Temperatures

Cycle life prediction of lithium-ion cells under complex temperature profiles

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Degradation of lithium ion batteries employing graphite negatives and nickel–cobalt–manganese oxide + spinel manganese oxide positives: Part 1, aging mechanisms and life estimation

Cited by 379 publications

References 30 publications

Impact of Temperature and Discharge Rate on the Aging of a LiCoO2/LiNi0.8Co0.15Al0.05O2Lithium-Ion Pouch Cell

Impact of Temperature and Discharge Rate on the Aging of a LiCoO2/LiNi0.8Co0.15Al0.05O2Lithium-Ion Pouch Cell

An Optimized Energy Management Strategy for Preheating Vehicle-Mounted Li-Ion Batteries at Subzero Temperatures

Cycle life prediction of lithium-ion cells under complex temperature profiles

Contact Info

Product

Resources

About

Impact of Temperature and Discharge Rate on the Aging of a LiCoO₂/LiNi_0.8Co_0.15Al_0.05O₂Lithium-Ion Pouch Cell

Impact of Temperature and Discharge Rate on the Aging of a LiCoO₂/LiNi_0.8Co_0.15Al_0.05O₂Lithium-Ion Pouch Cell