Guidelines for Safe, High Performing Li-Ion Battery Designs for Manned Vehicles

New design features and test methods are in development at NASA to take advantage of the newest high power and energy dense commercial Li-ion cell designs and to achieve passively thermal runaway (TR) propagation resistant (PPR) designs for manned missions requiring high power/voltage. The goal is to minimize the parasitic mass and volume of the battery components; thus reaching a balance between high battery specific power (W/kg) and energy (Wh/kg) as well as power (W/L) and energy density (Wh/L). Current 18650 cell designs achieve greater than 275 Wh/kg, greater than 725 Wh/L, but present high risks of side wall breaching during TR which can defeat many other safety features resulting in nearly immediate TR propagation. This work seeks to better understand the phenomena of cell side wall breaches and to determine the effectiveness of promising battery design features for achieving safe, high performing battery designs for high voltage/power applications

Investigation of cycling-induced microstructural degradation in silicon-based electrodes in lithium-ion batteries using X-ray nanotomography

The microstructural degradation of a composite silicon electrode at different stages in its cycle life was investigated in 3D using X-ray nano-computed tomography. A reconstructed volume of 36 μm × 27 μm × 26 μm from the composite electrode was imaged in its pristine state and after 1, 10 and 100 cycles. Particle fracturing and phase transformation was observed within the electrode with increased cycling. In addition, a distinct, lower X-ray attenuating phase was clearly resolved, which can be associated with surface film formation resulting from electrolyte breakdown and with silicon particle phase transformation. Changes in quantified microstructural properties such as phase volume fraction and particle specific surface area were tracked. Electrode performance loss is associated with loss of active silicon. These imaging results further highlight the capability of high resolution X-ray tomography to investigate the role of electrode microstructure in battery degradation and failure

Quantitative spatiotemporal mapping of thermal runaway propagation rates in lithium-ion cells using cross-correlated Gabor filtering

Abuse testing of lithium-ion batteries is widely performed in order to develop new safety standards and strategies. However, testing methodologies are not standardised across the research community, especially with failure mechanisms being inherently difficult to reproduce. High-speed X-ray radiography is proven to be a valuable tool to capture events occurring during cell failure, but the observations made remain largely qualitative. We have therefore developed a robust image processing toolbox that can quantify, for the first time, the rate of propagation of battery failure mechanisms revealed by high-speed X-ray radiography. Using Gabor filter, the toolbox selectively tracks the electrode structure at the onset of failure. This facilitated the estimation of the displacement of electrodes undergoing abuse via nail penetration, and also the tracking of objects, such as the nail, as it propagates through a cell. Further, by cross-correlating the Gabor signals, we have produced practical, illustrative spatiotemporal maps of the failure events. From these, we can quantify the propagation rates of electrode displacement prior to the onset of thermal runaway. The highest recorded acceleration (≈514 mm s−2) was when a nail penetrated a cell radially (perpendicular to the electrodes) as opposed to axially (parallel to the electrodes). The initiation of thermal runaway was also resolved in combination with electrode displacement, which occurred at a lower acceleration (≈108 mm s−2). Our assistive toolbox can also be used to study other types of failure mechanisms, extracting otherwise unattainable kinetic data. Ultimately, this tool can be used to not only validate existing theoretical mechanical models, but also standardise battery failure testing procedures

Combining Fractional Calorimetry with Statistical Methods to Characterize Thermal Runaway

Thermal management systems designed to handle the impacts of thermal runaway (TR) are key to safe operation of lithium-ion (Li-ion) batteries. Critical factors for optimizing these systems include the total energy released and the fraction of the total energy that is released through the cell casing versus through the ejecta material. A unique calorimeter, designed to characterize said factors, was utilized to examine the TR behavior of a variety of 18650-format Li-ion cells. Statistical methods were implemented to interpret the data

Multiscale dynamics of charging and plating in graphite electrodes coupling operando microscopy and phase-field modelling

The phase separation dynamics in graphitic anodes significantly affects lithium plating propensity, which is the major degradation mechanism that impairs the safety and fast charge capabilities of automotive lithium-ion batteries. In this study, we present comprehensive investigation employing operando high-resolution optical microscopy combined with non-equilibrium thermodynamics implemented in a multi-dimensional (1D+1D to 3D) phase-field modeling framework to reveal the rate-dependent spatial dynamics of phase separation and plating in graphite electrodes. Here we visualize and provide mechanistic understanding of the multistage phase separation, plating, inter/intra-particle lithium exchange and plated lithium back-intercalation phenomena. A strong dependence of intra-particle lithiation heterogeneity on the particle size, shape, orientation, surface condition and C-rate at the particle level is observed, which leads to early onset of plating spatially resolved by a 3D image-based phase-field model. Moreover, we highlight the distinct relaxation processes at different state-of-charges (SOCs), wherein thermodynamically unstable graphite particles undergo a drastic intra-particle lithium redistribution and inter-particle lithium exchange at intermediate SOCs, whereas the electrode equilibrates much slower at low and high SOCs. These physics-based insights into the distinct SOC-dependent relaxation efficiency provide new perspective towards developing advanced fast charge protocols to suppress plating and shorten the constant voltage regime

Bridging Nano and Micro-scale X-ray Tomography for Battery Research by Leveraging Artificial Intelligence

X-ray Computed Tomography (X-ray CT) is a well-known non-destructive imaging technique where contrast originates from the materials' absorption coefficients. Novel battery characterization studies on increasingly challenging samples have been enabled by the rapid development of both synchrotron and laboratory-scale imaging systems as well as innovative analysis techniques. Furthermore, the recent development of laboratory nano-scale CT (NanoCT) systems has pushed the limits of battery material imaging towards voxel sizes previously achievable only using synchrotron facilities. Such systems are now able to reach spatial resolutions down to 50 nm. Given the non-destructive nature of CT, in-situ and operando studies have emerged as powerful methods to quantify morphological parameters, such as tortuosity factor, porosity, surface area, and volume expansion during battery operation or cycling. Combined with powerful Artificial Intelligence (AI)/Machine Learning (ML) analysis techniques, extracted 3D tomograms and battery-specific morphological parameters enable the development of predictive physics-based models that can provide valuable insights for battery engineering. These models can predict the impact of the electrode microstructure on cell performances or analyze the influence of material heterogeneities on electrochemical responses. In this work, we review the increasing role of X-ray CT experimentation in the battery field, discuss the incorporation of AI/ML in analysis, and provide a perspective on how the combination of multi-scale CT imaging techniques can expand the development of predictive multiscale battery behavioral models.Comment: 33 pages, 5 figure

Quantifying Bulk Electrode Strain and Material Displacement within Lithium Batteries via High-Speed Operando Tomography and Digital Volume Correlation

Tracking the dynamic morphology of active materials during operation of lithium batteries is essential for identifying causes of performance loss. Digital volume correlation (DVC) is applied to high-speed operando synchrotron X-ray computed tomography of a commercial Li/MnO₂ primary battery during discharge. Real-time electrode material displacement is captured in 3D allowing degradation mechanisms such as delamination of the electrode from the current collector and electrode crack formation to be identified. Continuum DVC of consecutive images during discharge is used to quantify local displacements and strains in 3D throughout discharge, facilitating tracking of the progression of swelling due to lithiation within the electrode material in a commercial, spiral-wound battery during normal operation. Displacement of the rigid current collector and cell materials contribute to severe electrode detachment and crack formation during discharge, which is monitored by a separate DVC approach. Use of time-lapse X-ray computed tomography coupled with DVC is thus demonstrated as an effective diagnostic technique to identify causes of performance loss within commercial lithium batteries; this novel approach is expected to guide the development of more effective commercial cell designs

Signification d'un acte à une société civile dont le gérant est en curatelle ; Note sous Cour de cassation, deuxième Chambre civile, 7 avril 2016, pourvoi numéro 15-12.739

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