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Garrick, Taylor R. (ORCID:0000000322518129)

Publications and source records attributed to Garrick, Taylor R. (ORCID:0000000322518129).

10 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Modeling Losses in a Three Electrode System Towards Fast Charge Control

In this work we demonstrate the applicability of a versatile separator-reference mounted electrode in a three-electrode setup to accurately capture the primary current pathway in the battery cell during operation, calibrate a porous electrode model to the individual anode and cathode potential signals, and assign the various resistances to electrochemical phenomena in the battery cell. This calibrated electrochemical model is validated using continuous rate discharges associated with highway driving scenarios in an electric vehicle, and in turn utilized to predict the local anode potential and proximity to lithium plating onset. Finally, we demonstrate the strategy associated with utilization of the model to estimate constant anode potential charging during fast charge scenarios at various rates and starting conditions as a future look to fast charge calibration development and controls.

Garrick, Taylor R. (ORCID:0000000322518129)↗
DOE OSTI2024

Modeling Reversible Volume Change in Automotive Battery Cells with Porous Silicon Oxide-Graphite Composite Anodes

Automotive battery manufacturers are working to improve the individual cell and overall pack design by increasing durability, performance, and range, while reducing cost, and active material volume change is a key aspect that needs to be considered during this design process. Recently, silicon oxide-graphite composite anodes are being explored to increase total anode capacity while maintaining a tolerable amount of cell level reversible volume expansion due to the relatively lower reversible volume change of the silicon oxide compared to pure battery grade or metallurgical grade silicon. To predict the blended anode response and contribution to the overall cell volume change, we integrated the mechanical behavior of the individual active materials with the multi-species, multi-reaction model to predict the state-of-lithiation of the active materials in the cell at a given potential. The resulting simulations illustrate the tradeoff in volume change between the silicon oxide and the graphite during cell operation. This type of modeling approach will allow designers to virtually consider the impact of cell level and pack level design changes on overall system mechanical performance for automotive and grid storage applications, namely that relatively small addition of silicon containing materials can drive a significant increase in the volume change at the cell level, as demonstrated by the 5 wt% addition of silicon oxide accounting for half of the overall volume change in the cell.

Garrick, Taylor R. (ORCID:0000000322518129)↗
DOE OSTI2024

Quantifying the Temperature Dependence of the Multi-Species, Multi-Reaction Model. Part 1: Parameterization for a Meso-Carbon Micro-Bead Graphite

In this work, the temperature impact on the Multi-Species, Multi-Reaction (MSMR) model is studied. This is accomplished by acquiring data from slow rate lithiation and delithiation of a meso-carbon micro-bead (MCMB) graphite. The MSMR model is used to simulate linear-sweep voltammetry data of a porous electrode composed of graphite, and because the electrode is close to a state of dynamic equilibrium, the peaks in the differential voltage spectroscopy plot can be analyzed. Through this analysis, the temperature impact on the total fraction of available host sites in a particular MSMR gallery (X j ), the impact on the reference potential (U° j ), and the impact on the parameter detailing the deviation from Nernstian behavior ( ω j ) can be found. This is the first time the temperature dependence of the MSMR parameters have been experimentally analyzed. In Part 2, the impact of the temperature dependence of the MSMR parameters on the entropy coefficient of an intercalation material will be studied.

Paul, Abigail (ORCID:0000000172892069)↗
DOE OSTI2024

Quantifying the Entropy and Enthalpy of Insertion Materials for Battery Applications Via the Multi-Species, Multi-Reaction Model

The entropy coefficient of a battery cell is the property that governs the amount of reversible heat that is generated during operation. In this work, we propose an extension of the Multi-Species, Multi-Reaction (MSMR) model to capture the entropy coefficient of a large format lithium-ion battery cell. We utilize the hybridized time-frequency domain analysis (HTFDA) method using a multi-functional calorimeter to probe the entropy coefficient of a large format pouch type lithium-ion battery with a NMC 811 cathode and a graphite anode. The measured entropy coefficient profile of the battery cell is deconvoluted into an entropy coefficient for each active material, which is then estimated using an extension of the MSMR model. Finally, we extend the entropy of a material to individual entropy for each gallery as treated by the model.

Electrochemistry↗
DOE OSTI2024

Application of the Multi-Species, Multi-Reaction Model to Coal-Derived Graphite for Lithium-Ion Batteries

Graphite is a critical material used as the negative electrode in lithium-ion batteries. Both natural and synthetic graphites are utilized, with the latter obtained from a range of carbon raw materials. In this paper, efforts to synthesize graphite from coal as a domestic feedstock for synthetic graphite are reported. Domestic coal-derived graphite could address national security and energy issues by standing up domestic supply chains for battery critical materials. The performance in lithium-ion coin cells of this coal derived graphite is compared to a commercial battery-grade graphite. For the first time, a multi-species, multi-reaction (MSMR) modeling technique is applied to synthetic graphite derived from coal. Key thermodynamic, transport, and kinetic parameters are obtained for the coal derived graphite and compared to the same parameters for commercial battery-grade graphite. Modeling of synthetic graphites will allow for virtual evaluation of these materials toward production of domestically sourced graphite.

Paul, Abigail (ORCID:0000000172892069)↗
DOE OSTI2023

From Atoms to Wheels: The Role of Multi-Scale Modeling in the Future of Transportation Electrification

Traditionally, prototype hardware is built for validation testing to ensure battery systems design changes meet vehicle-level requirements, which is expensive both in cost and time. Virtual engineering (VE) of battery systems for electric vehicle (EV) propulsion offers a reduced-cost alternative to the traditional development process and uses multi-scale modeling to virtually probe the impact of design changes in a particular part on the overall performance of the system. This allows for rapid iteration over multiple design spaces, without committing to build hardware. This perspective article discusses current trends in VE for EV applications and proposes improvements to accelerate EV adoption.

Garrick, Taylor R. (ORCID:0000000322518129)↗
DOE OSTI2023

Quantifying Aging-Induced Irreversible Volume Change of Porous Electrodes

Automotive manufacturers are working to improve cell and pack design by increasing their performance, durability, and range. One of the critical factors to consider as the industry moves towards materials with higher energy density is the ability to consider the irreversible volume change characteristic of the accelerated SEI layer growth tied to the large volume change and particle cracking typically associated with active material strain. As the time from initial design to manufacture of electric vehicle is decreased in order to rapidly respond to consumer demands and widespread adoption of electric vehicles, the ability to link aging and volume change to end of life vehicle requirements using virtual tools is critical. In this study, apply a mechano-electrochemical model to determine the irreversible volume change at the electrode and cell level, allowing for virtual design iterations to predict the volume change at battery cell aged states.

Electrochemistry↗
DOE OSTI2023

Quantifying Volume Change in Porous Electrodes via the Multi-Species, Multi-Reaction Model

Automotive manufacturers are working to improve individual cell and overall pack design by increasing their performance, durability, and range, while reducing cost; and active material volume change is one of the more complex aspects that needs to be considered during this process. As the time from initial design to manufacture of electric vehicles is decreased, design work that used to rely solely on testing needs to be supplemented or replaced by virtual methods. As electrochemical engineers drive battery and system design using model-based methods, the need for coupled electrochemical/mechanical models that take into account the active material change utilizing physics based or semi-empirical approaches is necessary. In this study, we illustrated the applicability of a mechano-electrochemical coupled modeling method considering the multi-species, multi-reaction model as popularized by Verbrugge and Baker. To do this, validation tests were conducted using a computer-controlled press apparatus that can control the press displacement and press force with precision. The coupled MSMR volume change model was developed and its applicability to graphite and NMC cells was illustrated. The increased accuracy of the model considering the coupled MSMR volume change approach shows in the importance of accounting for individual gallery volume change behavior on cell level predictions.

25 ENERGY STORAGE↗
DOE OSTI2023

Efficient Reformulation of Linear and Nonlinear Solid-Phase Diffusion in Lithium-ion Battery Models using Symmetric Polynomials: Mass Conservation and Computational Efficiency

Lithium-ion batteries are typically modeled using porous electrode theory coupled with various transport and reaction mechanisms, along with suitable discretization or approximations for the solid-phase diffusion equation. The solid-phase diffusion equation represents the main computational burden for typical pseudo-2-dimensional (p2D) models since these equations in the pseudo r -dimension must be solved at each point in the computational grid. This substantially increases the complexity of the model as well as the computational time. Traditional approaches towards simplifying solid-phase diffusion possess certain significant limitations, especially in modeling emerging electrode materials which involve phase changes and variable diffusivities. A computationally efficient representation for solid-phase diffusion is discussed in this paper based on symmetric polynomials using Orthogonal Collocation and Galerkin formulation (weak form). A systematic approach is provided to increase the accuracy of the approximation (p form in finite element methods) to enable efficient simulation with a minimal number of semi-discretized equations, ensuring mass conservation even for non-linear diffusion problems involving variable diffusivities. These methods are then demonstrated by incorporation into the full p2D model, illustrating their advantages in simulating high C-rates and short-time dynamic operation of Lithium-ion batteries.

25 ENERGY STORAGE↗