Multi-Species, Multi-Reaction Model for Porous Intercalation Electrodes: Part I. Model Formulation and a Perturbation Solution for Low-Scan-Rate, Linear-Sweep Voltammetry of a Spinel Lithium Manganese Oxide Electrode

Baker, Daniel R.

doi:10.1149/2.0771816jes

Cited by 31 publications

(58 citation statements)

References 31 publications

(37 reference statements)

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“…The thermodynamics of lithiated graphite are modeled using the multi-site, multi-reaction (MSMR) model as described in [20][21][22][23]. A practical aspect of the MSMR model is that, with few parameters that can be associated with the physical chemistry of the intercalation material, a quantitative fit of the open-circuit potential results, and this is key for the overall analysis.…”

Section: Thermodynamics and Interfacial Kineticsmentioning

confidence: 99%

The influence of surface inhomogeneity on the overcharge and lithium plating of graphite electrodes

Baker

2019

J. Phys. Energy

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We seek to clarify phenomena involved in the overcharge of a graphite electrode in a lithium ion battery, including lithium (Li) plating. In Baker and Verbrugge (2019 J. Electrochem. Soc.), we developed a set of equations that can be used to treat Li plating and subsequent electro-dissolution, and we analyzed how the equation system behaved for a particle of graphite, a fundamental unit of the negative (porous) electrode in lithium ion cells. In this work, we employ the same governing equations, but we render them in a two-dimensional setting to examine the graphite-electrolyte interface, allowing us to clarify phenomena involved in Li plating over graphitic electrode elements in the absence of complicating factors associated with the architecture of a porous electrode. For a variety of reasons described in the Introduction of this work, the surface of graphite is nonuniform in terms of reaction rates for Li insertion and plating, and we show that when the electrode is subjected to constant-current charging, as is commonly employed, such nonuniformities lead to early Li plating over the highly reactive surfaces. These observations underscore the importance of maintaining a uniform electrode surface, especially when the cell is to be subjected to high rates of charge.

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Section: Thermodynamics and Interfacial Kineticsmentioning

confidence: 99%

The influence of surface inhomogeneity on the overcharge and lithium plating of graphite electrodes

Baker

2019

J. Phys. Energy

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“…Thermodynamic model attributes -The Multi-Species, Multi-Reactions (MSMR) model describes the electrochemical thermodynamics of solid-state reactions and phase transitions that insertion materials go through at different lithiation states. [29][30][31] The model has been shown to nicely match experimental halfcell open-circuit potential data, and it captures a wide range of solid-state complexity, including phase changes. Because the model has a simple deterministic form with easily interpretable parameters, it can be tuned to explore the effects of parameters on OCP and differential voltage and, as shown here, used in optimization software for robust parameter estimation.…”

Section: Physics-based Modeling and Parameter Estimation Approachmentioning

confidence: 92%

“…Studies of open-circuit and differential voltage spectra of whole-cells typically build from half-cell experimental data and models. [32][33][34] As a result of having physically interpretable parameters, the MSMR model has been used to gain insight into interfacial resistances in graphite 35,36 , interfacial reactions in Li-Si 31 , and the effect of scan rate in linear sweep voltammetry experiments 29,30 .…”

Section: Physics-based Modeling and Parameter Estimation Approachmentioning

confidence: 99%

Low-Error Estimation of Half-Cell Thermodynamic Parameters from Whole-Cell Li-Ion Battery Experiments: Physics-Based Model Formulation, Experimental Demonstration, and an Open Software Tool

Schwartz

2022

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Low C-rate charge and discharge experiments, plus complementary differential voltage or differential capacity analysis, are among the most common battery characterization methods. Here, we adapt the multi-species, multi-reaction (MSMR) half-cell thermodynamic model to low C-rate cycling of whole-cell Li-ion batteries. MSMR models for the anode and cathode are coupled through whole-cell charge balances and cell-cycling voltage constraint equations, forming the basis for model-based estimation of MSMR half-cell parameters from whole-cell experimental data. Emergent properties of the whole-cell, like slippage of the anode and cathode lithiation windows, are also computed as cells cycle and degrade. A sequential least-square optimization scheme is used for parameter estimation from low-C cycling data of Samsung 18650 NMC|C cells. Low-error fits of the open-circuit cell voltage (e.g., under 5 mV mean absolute error for charge or discharge curves) and differential voltage curves for fresh and aging cells are achieved. We explore the features (and limitations) of using literature reference values for the MSMR half-cell thermodynamic parameters (reducing our whole-cell formulation to a 1-degree-of-freedom fit), and demonstrate the benefits of opening up the degrees of freedom by letting the MSMR parameters be tailored to the cell under test, within constrained bounds near the half-cell reference values. Bootstrap analysis is performed on each dataset to show the robustness of our fitting to experimental noise and data sampling over the course of 600 cell cycles. The results show which specific MSMR insertion reactions are most responsible for capacity loss in each half-cell and the collective interactions that lead to whole-cell slippage and changes in useable capacity. Open-source software is made available to easily extend this model-based analysis to other labs and battery chemistries.

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“…More recently, Baker and Verbrugge have developed a Multi-Species, Multi-Reaction (MSMR) Model [104][105][106][107][108] for porous intercalation electrodes that has been applied to plating and dissolution of Li in a Li ion cell [108] . In the latter work, a set of equations was derived to describe the overcharge of a Li ion cell.…”

Section: Plating Modelingmentioning

confidence: 99%

“…In the Multi-Species, Multi-Reaction (MSMR) Model [104][105][106][107][108] a few parameters can be associated with the physical chemistry of the intercalation material enabling a quantitative fit of the open-circuit potential. In this model, different galleries of intercalated Li are assumed to be in thermodynamic equilibrium, so that their open circuit potentials are equal to some common equilibrium potential of the intercalation material.…”

Section: Plating Modelingmentioning

confidence: 99%

Lithium Plating Detection Methods in Lithium-Ion Batteries

2020

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Lithium-ion batteries provide a low-cost, long cycle-life and high energy density solution to the expediting energy requirement of the automotive industry. There is a growing need of fast charging batteries for commercial application. However, large charging currents may cause Lithium plating which describes the deposition of metallic Lithium at the anode surface. It takes place at conditions of high currents and/or low temperatures because of kinetic limitations. The main reason behind plating is the slow solid-state diffusion of Lithium ions inside the active material. If the anode surface potential falls below 0 V versus Li/Li+, the formation of metallic Lithium is thermodynamically feasible. To avoid or reduce the amount Lithium plating, it is essential to detect its onset during a charging event. Determination of accurate Lithium plating curve is crucial in estimating the boundary conditions for battery operation without compromising life and safety. There are various data analysis methods involved in deriving the Lithium plating curve: anode potential using a three-electrode cell, variation of relaxation voltage after charging (dV/dt), variation of accumulated charge with voltage (dQ/dV) and coulombic efficiency of charge/discharge with %SOC (state of charge) are more commonly employed techniques. In addition to these methods, estimation of its occurrence is typically underpinned by electrochemical models where the negative (anode) electrode potential is expressed by a set of partial differential equations based on the electrochemical and physical properties of the battery components such as the electrodes and electrolyte. The present paper reviews the common test methods and analysis that are currently utilized in Lithium plating determination. Knowledge gaps are identified, and recommendations are made for the future development in the determination and verification of Lithium plating curve in terms of modelling and analysis.

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Multi-Species, Multi-Reaction Model for Porous Intercalation Electrodes: Part I. Model Formulation and a Perturbation Solution for Low-Scan-Rate, Linear-Sweep Voltammetry of a Spinel Lithium Manganese Oxide Electrode

Cited by 31 publications

References 31 publications

The influence of surface inhomogeneity on the overcharge and lithium plating of graphite electrodes

The influence of surface inhomogeneity on the overcharge and lithium plating of graphite electrodes

Low-Error Estimation of Half-Cell Thermodynamic Parameters from Whole-Cell Li-Ion Battery Experiments: Physics-Based Model Formulation, Experimental Demonstration, and an Open Software Tool

Lithium Plating Detection Methods in Lithium-Ion Batteries

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