Mathematical modeling of the capacity fade of Li-ion cells

Ramadass, Premanand; Haran, Bala; White, Ralph E.; Popov, Branko N.

doi:10.1016/s0378-7753(03)00531-7

Cited by 394 publications

(259 citation statements)

References 9 publications

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“…These properties justify the choice of the full-order model for our ongoing efforts to simulate the behavior of both individual cells and battery packs installed in hybrid electric vehicles. The proposed numerical algorithm is a convenient basis for such efforts, as it allows straightforward generalizations in order to incorporate heat effects and aging phenomena in the scope of the models found, for example, in [3,[6][7][8][9].…”

Section: Resultsmentioning

confidence: 99%

“…The charge transfer is proportional to the mass transfer and is subject to Butler-Volmer reaction kinetics [6,7,15,21] in the form…”

Section: Butler-volmer Reaction Kineticsmentioning

confidence: 99%

“…For the model with thermal effects included, we refer the reader, for example, to Cai and White [3], Kumaresan et al [4], or Gu and Wang [5]. The aging effects of Li-ion batteries are discussed, for example, by Ramadass et al [6,7] or Ning et al [8,9].…”

Section: Introductionmentioning

confidence: 99%

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An Efficient and Robust Numerical Solution of the Full-Order Multiscale Model of Lithium-Ion Battery

Beneš

Fučík

Havlena

et al. 2018

Mathematical Problems in Engineering

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We propose a novel and efficient numerical approach for solving the pseudo two-dimensional multiscale model of the Li-ion cell dynamics based on first principles, describing the ion diffusion through the electrolyte and the porous electrodes, electric potential distribution, and Butler-Volmer kinetics. The numerical solution is obtained by the finite difference discretization of the diffusion equations combined with an original iterative scheme for solving the integral formulation of the laws of electrochemical interactions. We demonstrate that our implementation is fast and stable over the expected lifetime of the cell. In contrast to some simplified models, it provides physically consistent results for a wide range of applied currents including high loads. The algorithm forms a solid basis for simulations of cells and battery packs in hybrid electric vehicles, with possible straightforward extensions by aging and heat effects.

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Section: Resultsmentioning

confidence: 99%

“…The charge transfer is proportional to the mass transfer and is subject to Butler-Volmer reaction kinetics [6,7,15,21] in the form…”

Section: Butler-volmer Reaction Kineticsmentioning

confidence: 99%

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An Efficient and Robust Numerical Solution of the Full-Order Multiscale Model of Lithium-Ion Battery

Beneš

Fučík

Havlena

et al. 2018

Mathematical Problems in Engineering

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“…According to [11] and [15], the effect of temperature on the performance of lithiumion cells, on the one hand, is positive. High temperature enhances the activities of lithium ions and decreases internal resistance, which makes a cell release more capacity in a certain cycle.…”

Section: Capacity Fading Model Considering Temperature Effectsmentioning

confidence: 99%

“…After studying the accelerated degradation test of numerous LiFePO 4 cells, Lam and Bauer [10] proposed an empirical linear model describing the capacity fade, and the Arrhenius function was used to describe the fading rates under different temperatures. Besides the linear model, there are some studies centering on capacity fading models for different Lithium-ion type cells, such as the radical and linear model [19] and the quadratic and linear model [15]. 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.…”

Section: Introductionmentioning

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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2013

Battery Systems Engineering

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Mathematical modeling of the capacity fade of Li-ion cells

Cited by 394 publications

References 9 publications

An Efficient and Robust Numerical Solution of the Full-Order Multiscale Model of Lithium-Ion Battery

An Efficient and Robust Numerical Solution of the Full-Order Multiscale Model of Lithium-Ion Battery

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

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