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Weddle, Peter J.

Publications and source records attributed to Weddle, Peter J..

13 records
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DOE OSTI2025

Generating multi-scale Li-ion battery cathode particles with radial grain architectures using stereological generative adversarial networks

Abstract Understanding structure-property relationships of Li-ion battery cathodes is crucial for optimizing rate-performance and cycle-life resilience. However, correlating the morphology of cathode particles, such as in LiNi0.8Mn0.1Co0.1O2 (NMC811), and their inner grain architecture with electrode performance is challenging, particularly, due to the significant length-scale difference between grain and particle sizes. Experimentally, it is not feasible to image such a high number of particles with full granular detail. A second challenge is that sufficiently high-resolution 3D imaging techniques remain expensive and are sparsely available at research institutions. Here, we present a stereological generative adversarial network-based model fitting approach to tackle this, that generates representative 3D information from 2D data, enabling characterization of materials in 3D using cost-effective 2D data. Once calibrated, this multi-scale model can rapidly generate virtual cathode particles that are statistically similar to experimental data, and thus is suitable for virtual characterization and materials testing through numerical simulations. A large dataset of simulated particles with inner grain architecture has been made publicly available.

25 ENERGY STORAGE↗
DOE OSTI2024

PINN surrogate of Li-ion battery models for parameter inference, Part I: Implementation and multi-fidelity hierarchies for the single-particle model

To plan and optimize energy storage demands that account for Li-ion battery aging dynamics, techniques need to be developed to diagnose battery internal states accurately and rapidly. Here, this study seeks to reduce the computational resources needed to determine a battery's internal states by replacing physics-based Li-ion battery models - such as the single-particle model (SPM) and the pseudo-2D (P2D) model - with a physics-informed neural network (PINN) surrogate. The surrogate model makes high-throughput techniques, such as Bayesian calibration, tractable to determine battery internal parameters from voltage responses. This manuscript is the first of a two-part series that introduces PINN surrogates of Li-ion battery models for parameter inference (i.e., state-of-health diagnostics). In this first part, a method is presented for constructing a PINN surrogate of the SPM. A multi-fidelity hierarchical training, where several neural nets are trained with multiple physics-loss fidelities is shown to significantly improve the surrogate accuracy when only training on the governing equation residuals. The implementation is made available in a companion repository (https://github.com/NREL/PINNSTRIPES). The techniques used to develop a PINN surrogate of the SPM are extended in Part II for the PINN surrogate for the P2D battery model, and explore the Bayesian calibration capabilities of both surrogates.

25 ENERGY STORAGE↗
DOE OSTI2024

PINN surrogate of Li-ion battery models for parameter inference, Part II: Regularization and application of the pseudo-2D model

Bayesian parameter inference is useful to improve Li-ion battery diagnostics and can help formulate battery aging models. However, it is computationally intensive and cannot be easily repeated for multiple cycles, multiple operating conditions, or multiple replicate cells. To reduce the computational cost of Bayesian calibration, numerical solvers for physics-based models can be replaced with faster surrogates. A physics-informed neural network (PINN) is developed as a surrogate for the pseudo-2D (P2D) battery model calibration. For the P2D surrogate, additional training regularization was needed as compared to the PINN single-particle model (SPM) developed in Part I. Both the PINN SPM and P2D surrogate models are exercised for parameter inference and compared to data obtained from a direct numerical solution of the governing equations. A parameter inference study highlights the ability to use these PINNs to calibrate scaling parameters for the cathode Li diffusion and the anode exchange current density. By realizing computational speed-ups of ~2250x for the P2D model, as compared to using standard integrating methods, the PINN surrogates enable rapid state-of-health diagnostics. Finally, in the low-data availability scenario, the testing error was estimated to ~2 mV for the SPM surrogate and ~10 mV for the P2D surrogate which could be mitigated with additional data.

25 ENERGY STORAGE↗
DOE OSTI2024

Cohesive phase-field chemo-mechanical simulations of inter- and trans- granular fractures in polycrystalline NMC cathodes via image-based 3D reconstruction

The optimal design and durable utilization of lithium-ion batteries necessitates an objective modeling approach to understand fracture and failure mechanisms. This paper presents a comprehensive chemo-mechanical modeling study focused on elucidating fracture-induced damage and degradation phenomena in the polycrystalline Li $\mathcal{x}$ Ni 0.5 Mn 0.3 Co 0.2 O 2 (NMC532) cathode. An innovative approach that utilizes image-based reconstructed 3D geometry as finite element (FE) mesh input is employed to enhance the precision in capturing the convoluted architecture and morphological features. For accurately representing the intricate crack configurations within the polycrystalline system, we adopted the cohesive phase-field fracture (CPF) model. Through the integration of advanced image-based geometry reconstruction technique and the promising CPF modeling approach, lithium (de)intercalation induced crack evolution (e.g., nucleation, propagation, branching and diverse modes including inter-/trans-(intra-) granular patterns) and the resulting chemical degradation can be precisely captured, which is also compared and validated with numerical predictions using a continuum damage model. In particular, this model predicts fracture induced degradation under varying fracture properties of grain boundaries and charging rates; the conclusion that NMC particles comprised of larger grains are predicted to have less degradation than those with smaller grains can also be drawn. This comprehensive analysis provides valuable insights into the fracture and degradation within polycrystalline NMC cathodes.

25 ENERGY STORAGE↗
DOE OSTI2024

Consequences of plane-strain and plane-stress assumptions in fully coupled chemo-mechanical Li-ion battery models

In Li-ion battery research, it is common to simulate chemo-mechanical phenomena in reduced dimensions (e.g., 2-D) as opposed to fully resolve these complex physics in 3-D. It is common to assume either (1) the out-of-plane strain is negligible (commonly referred to as plane-strain), or (2) the out-of-plane stress is negligible (commonly referred to as plane-stress). However, there is typically little consideration as to the quantitative consequences of these approximations. Furthermore, the influence of these out-of-plane assumptions can be compounded and convoluted when chemo-mechanics models implement so-called “fully coupled” formulations, where the local species concentrations influence the stress-state and the stress-state influences the local species fluxes. Here, the present manuscript explores the implications of using plane-stress and plane-strain assumptions in 2-D as compared to simulating a full 3-D electrode particle. This comparative study includes simulating both isotropic and anisotropic particle intercalation where the particles can be surrounded by either a liquid or solid electrolyte. Additionally, common Li-ion battery-model metrics such as the state-of-stress, intercalation fraction distribution, and specific capacity are compared, while also considering the effects of particle size and C-rate. As alternatives to the pure plane-strain and plane stress approximations, two modified plane-strain assumptions are found to better approximate the fully coupled chemo-mechanical 3-D behavior.

25 ENERGY STORAGE↗
DOE OSTI2023

Battery state-of-health diagnostics during fast cycling using physics-informed deep-learning

Rapid, in-situ Li-ion battery state-of-health (SOH) quantification is challenging. Li-ion battery aging can vary significantly with chemistry, operating conditions, cycling demands, electrode design, and operation history. As a cell ages, optimal and safe operating conditions need to be adapted to account for battery degradation by tracking critical aging modes such as loss-of-lithium-inventory (LLI), loss-of-active-material (LAM) in either electrode, and/or impedance rise. This manuscript describes a framework for identifying battery aging modes in-operando using fast-rate voltage charge/discharge responses. The framework uses a physically based Li-ion battery model to produce synthetic high-rate responses at aged states. The aging model is calibrated against experimental data from cells with different electrode loadings and cycled under a variety of fast-charging conditions (1 h, 15 min, 10 min, and 7 min charging). The synthetically generated high-rate responses at aged states are then used to train a deep-learning model to identify real cell state-of-health from fast charge/discharge battery voltage responses. The synthetically trained deep-learning model performance is validated by comparing to standard incremental capacity analysis and half-cell measurements. Finally, the framework demonstrates the benefits of using high-rate physics-based models to generate synthetic data for training deep-learning models.

25 ENERGY STORAGE↗
DOE OSTI2023

Voltage-Based Strategies for Preventing Battery Degradation under Diverse Fast-Charging Conditions

Maintaining safe operating conditions is a key challenge for high-performance lithium-ion battery applications. The lithium-plating reaction remains a risk during charging, but limited studies consider the highly variable charging conditions possible in commercial cells. Here we combine pseudo-2D electrochemical modeling with data visualization methods to reveal important relationships between the measurable cell voltage and difficult-to-predict Li-plating onset criteria. An extensively validated model is used to compute Li plating for thousands of multistep charging conditions spanning diverse rates, temperatures, states-of-charge, and cell aging. Here we observe an empirical cell operating voltage limit below which plating does not occur across all conditions, and this limit varies with the battery state-of-charge and aging. A model sensitivity analysis also indicates that, when comparing two charging voltage profiles, the capacity difference at 4.0 V correlates well with the difference in the plating onset capacity. These results encourage simple strategies for Li-plating prevention that are complementary to existing battery controls.

25 ENERGY STORAGE↗
DOE OSTI2023

Cell-Format-Dependent Mechanical Damage in Silicon Anodes

Strong binders can be counterproductive for silicon anodes. Here, we show that stresses from cycling Si-based electrodes can cause permanent stretching and wrinkling of the current collector. Furthermore, this deformation damages the electrode coating and accelerates cell aging due to the inactivation of Si domains and facilitation of Li plating. Interestingly, we demonstrate that the formation of wrinkles is size-dependent, being present in pouch cells but absent from coin cells. This size-dependent performance decay indicates that, in extreme cases, testing outcomes are highly dependent on scale and that the validation of battery materials may require testing at larger cell formats.

25 ENERGY STORAGE↗
DOE OSTI2023

Rational designs to enable 10-min fast charging and long cycle life in lithium-ion batteries

A daunting challenge in the design of lithium ion batteries (LiBs) is enabling 10-min extreme fast charging (XFC) while achieving appreciable charge acceptance and cycle life. This desirable outcome requires both a comprehensive understanding of LiB operation and aging behavior at different length scales and careful optimization. Lithium plating has been a critical bottleneck because, at XFC rates, it consumes cyclable lithium causing distinct aging and safety concerns even in moderate-loading LiBs. Here, we propose combining multiple solutions, including materials-to-electrode design-to-charging protocols, that are intended to overcome limitations in lithium-ion transport in the electrolyte phase, thus enabling 10-min XFC in LiBs. Some implemented strategies include cathode chemistry, optimized carbon binder domain in the cathode, dual layer anode design, improved separator and advanced electrolyte. Further, innovative charging protocols in moderately loading (~3 mAh/cm 2 anode/2.7 mAh/cm 2 cathode) single-layer pouch cells are proposed, together with demonstrated 10-min XFC with higher charge acceptance between 87.3 and 92.1% (or 2–2.1 mAh/cm 2 ) for 600 cycles without lithium plating. This methodical study with well-defined cells shows promise in combining multiple solution strategies to enable 10-min XFC, charting a pathway to achieve XFC in higher-loading energy-optimized LiBs.

25 ENERGY STORAGE↗
DOE OSTI2023

Dynamic In‐Plane Heterogeneous and Inverted Response of Graphite to Fast Charging and Discharging Conditions in Lithium‐Ion Pouch Cells

Solutions for improving fast charging of lithium‐ion batteries have largely focused on alleviating through‐plane lithiation gradients while little is understood about in‐plane heterogeneities and how to resolve them. Herein, high‐speed synchrotron X‐ray diffraction (XRD) resolves graphite lithiation spatially and temporally during 6 C charging and 2 C discharging. At every point during operation, considerable differences in the state of lithiation across the pouch cell are present. Some regions are more responsive to operation than others, reaching full lithiation early during charge and full delithiation during discharge. Other regions within the cell never fully delithiate during discharge, despite a prolonged voltage hold at 2.8 V. Using time‐resolved XRD data, the calculated local current density (mA cm −2 ) at the graphite surface shows an unexpected occurrence of local inverted current densities where regions of graphite are observed to delithiate during charging and lithiate during discharging. A pseudo‐3D model is developed for the graphite electrode with spatially varying microstructural tortuosity to show how microstructural heterogeneity could influence spatial charge dynamics. The model could not predict the complex in‐plane charge behavior observed within the cell. Consequently physics‐based charging protocols based on homogeneous electrode assumptions may underestimate the local variations in charge dynamics and occurrence of lithium plating.

25 ENERGY STORAGE↗
DOE OSTI2022

Enabling Extreme Fast-Charging: Challenges at the Cathode and Mitigation Strategies

We report charging lithium-ion batteries (LiBs) in 10 to 15 min via extreme fast-charging (XFC) is important for the widespread adoption of electric vehicles (EVs). Lately, the battery research community has focused on identifying XFC bottlenecks and determining novel design solutions. Like other LiB components, cathodes can present XFC bottlenecks, especially when considering long-term battery life. Therefore, it is necessary to develop a comprehensive understanding of how XFC conditions degrade LiB cathodes. The present article reviews relevant cathode-focused studies and summarizes the current understanding regarding cathode performance and aging issues under XFC conditions. Dominant aging modes and mechanisms are identified at different length-scales with electrochemical correlations for LiNi x Mn y Co z O 2 (NMC)-based cathodes. A range of electrochemical techniques and models provide key insights into cathode performance and life issues. A suite of multimodal and multiscale microscopy and X-ray techniques is surveyed to quantify chemical, structural, and crystallographic NMC-cathode degradation. Cathode cycle-life is scaled to equivalent EV miles to illustrate how cathode degradation translates to real-world scenarios and quantifies cathode-related bottlenecks that hinder XFC adoption. Finally, the article discusses several cathode cycle-life aging mitigation strategies with example case studies and identifies remaining challenges.

25 ENERGY STORAGE↗