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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Systems and methods for direct estimation of battery parameters using only charge/discharge curves

Electrochemical models for the lithium-ion battery are useful in predicting and controlling its performance. The values of the parameters in these models are vital to their accuracy. However, not all parameters can be measured precisely, especially when destructive methods are prohibited. In some embodiments of the present disclosure, a parameter estimation approach is used to estimate the open circuit potential of the positive electrode (Up) using piecewise linear approximation together with all the other parameters of a single particle model. Up and 10 more parameters may be estimated from a single discharge curve without knowledge of the electrode chemistry using a technique such as a genetic algorithm. Different case studies were presented for estimating Up with different types of parameters of the battery model. The estimated parameters were then validated by comparing simulations at different discharge rates with experimental data.

Qi, Yanbo↗
DOE OSTI2024

Substantial oxygen loss and chemical expansion in lithium-rich layered oxides at moderate delithiation

Delithiation of layered oxide electrodes triggers irreversible oxygen loss, one of the primary degradation modes in lithium-ion batteries. However, the delithiation-dependent mechanisms of oxygen loss remain poorly understood. Here we investigate the oxygen non-stoichiometry in Li 1.18–x Ni 0.21 Mn 0.53 Co 0.08 O 2–δ electrodes as a function of Li content by using cycling protocols with long open-circuit voltage steps at varying states of charge. Surprisingly, we observe substantial oxygen loss even at moderate delithiation, corresponding to 2.5, 4.0 and 7.6 ml O 2 per gram of Li 1.18–x Ni 0.21 Mn 0.53 Co 0.08 O 2–δ after resting at upper capacity cut-offs of 135, 200 and 265 mAh g −1 for 100 h. Our observations suggest an intrinsic oxygen instability consistent with predictions of high oxygen activity at intermediate potentials versus Li/Li + . In addition, we observe a large chemical expansion coefficient with respect to oxygen non-stoichiometry, which is about three times greater than those of classical oxygen-deficient materials such as fluorite and perovskite oxides. Furthermore, our work challenges the conventional wisdom that deep delithiation is a necessary condition for oxygen loss in layered oxide electrodes and highlights the importance of calendar ageing for investigating oxygen stability.

Atomistic models↗
DOE OSTI2022

Electrochemically induced amorphous-to-rock-salt phase transformation in niobium oxide electrode for Li-ion batteries

Intercalation-type metal oxides are promising negative electrode materials for safe rechargeable lithium-ion batteries due to the reduced risk of Li plating at low voltages. Nevertheless, their lower energy and power density along with cycling instability remain bottlenecks for their implementation, especially for fast-charging applications. Here, we report a nanostructured rock-salt Nb 2 O 5 electrode formed through an amorphous-to-crystalline transformation during repeated electrochemical cycling with Li + . This electrode can reversibly cycle three lithiums per Nb 2 O 5 , corresponding to a capacity of 269 mAh g –1 at 20 mA g –1 , and retains a capacity of 191 mAh g –1 at a high rate of 1 A g –1 . Further, it exhibits superb cycling stability with a capacity of 225 mAh g –1 at 200 mA g –1 for 400 cycles, and a Coulombic efficiency of 99.93%. We attribute the enhanced performance to the cubic rock-salt framework, which promotes low-energy migration paths. Our work suggests that inducing crystallization of amorphous nanomaterials through electrochemical cycling is a promising avenue for creating unconventional high-performance metal oxide electrode materials.

25 ENERGY STORAGE↗
DOE OSTI2022

Feature engineering for machine learning enabled early prediction of battery lifetime

Accurate battery lifetime estimates enable accelerated design of novel battery materials and determination of optimal use protocols for longevity in deployments. Unfortunately, traditional battery testing may take years to reach thousands of cycles. Recent studies have shown that machine learning (ML) tools can predict lithium-ion battery lifetimes from 100 or fewer preliminary cycles, representing only a few weeks of cycling. Until now, conclusions about the efficacy and broad applicability of these predictions across a variety of cathode chemistries have been limited by available experimental information. In this work, we leverage a battery cycling dataset representing six cathode chemistries (NMC111, NMC532, NMC622, NMC811, HE5050, and 5Vspinel), multiple electrolyte/anode compositions, and 300 total carefully prepared pouch batteries to explore feature selection and battery chemistry's role in ML battery lifetime predictions. Here, a mean absolute error (MAE) of 78 cycles in prediction was seen for a chemistry-spanning test set from 100 preliminary cycles. Furthermore, an MAE of 103 cycles was seen when using only the first cycle. This study represents an in-depth investigation of strategies for feature selection for battery lifetime prediction, ML models' generalization across multiple battery chemistries, and predictions beyond the training set in the chemical space.

25 ENERGY STORAGE↗
DOE OSTI2024

Ca-dimers, solvent layering, and dominant electrochemically active species in Ca(BH4)2 in THF

Abstract Divalent ions (Mg, Ca, and Zn) are being considered as competitive, safe, and earth-abundant alternatives to Li-ion electrochemistry, but present challenges for stable cycling due to undesirable interfacial phenomena. We explore the formation of electroactive species in the electrolyte Ca(BH 4 ) 2 ∣THF using molecular dynamics coupled with a continuum model of bulk and interfacial speciation. Free-energy analysis and unsupervised learning indicate a majority population of neutral Ca dimers and monomers with diverse molecular conformations and an order of magnitude lower concentration of the primary electroactive charged species – the monocation, $${\rm{CaBH}}_{4}^{+}$$ CaBH 4 + – produced via disproportionation of neutral complexes. Dense layering of THF molecules within ~1 nm of the electrode surface strongly modulates local electrolyte species populations. A dramatic increase in monocation population in this interfacial zone is induced at negative bias. We see no evidence for electrochemical activity of fully-solvated Ca 2+ . The consequences for performance are discussed in light of this molecular-scale insight.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Defect-driven anomalous transport in fast-ion conducting solid electrolytes

We report solid-state ionic conduction is a key enabler of electrochemical energy storage and conversion. The mechanistic connections between material processing, defect chemistry, transport dynamics, and practical performance are of considerable importance, but remain incomplete. Here, inspired by studies of fluids and biophysical systems, we re-examine anomalous diffusion in the iconic two-dimensional fast-ion conductors, the β- and β"-aluminas. Using large-scale simulations, we reproduce the frequency dependence of alternating-current ionic conductivity data. We show how the distribution of charge-compensating defects, modulated by processing, drives static and dynamic disorder, which lead to persistent sub-diffusive ion transport at macroscopic timescales. We deconvolute the effects of repulsions between mobile ions, the attraction between the mobile ions and charge-compensating defects, and geometric crowding on ionic conductivity. Our quantitative framework based on these model solid electrolytes connects their atomistic defect chemistry to macroscopic performance with minimal assumptions and enables mechanism-driven 'atoms-to-device' optimization of fast-ion conductors.

25 ENERGY STORAGE↗
DOE OSTI2022

Optimal operation and sizing of pumped thermal energy storage for net benefits maximization

Abstract Current trends in the modern grid are leading to the development and deployment of energy storage to help integrate increasing variable renewable energy sources into the grid. This paper studies a pumped thermal energy storage (PTES) system for multiple grid services including energy arbitrage, frequency regulation, spinning and non‐spinning reserve, and resource adequacy. Optimal dispatch methods are proposed for individual services as well as value stacking from multiple services to maximize the economic benefits. Assessment results demonstrate the superiority of value stacking. Specifically, the study shows the maximum revenue from an individual grid service with a 30‐MWh PTES system was $522,520, while the value stacking could increase the benefits to $678,477. In addition, sensitivity analyses were conducted to explore the cost‐effectiveness of a PTES system with different combinations of power transfer limits and energy capacity. It was found that the power transfer limit had a greater impact than the energy capacity on the benefits. The proposed method could help determine the optimal duration of a future PTES system.

25 ENERGY STORAGE↗
DOE OSTI2025

Impact of Electrolyte Solvent on Li 4 Ti 5 O 12 /LiNi 0.90 Mn 0.05 Co 0.05 O 2 Battery Performance for Behind-the-Meter Storage Applications

Behind-the-Meter Storage (BTMS) systems require dedicated development of battery materials that target long cycle life and low cost at the system level. Pairing Li 4 Ti 5 O 12 (LTO) and LiNi 0.9 Mn 0.05 Co 0.05 O 2 (NMC90-5-5) shows promise to achieve targets for BTMS applications; however, minimal literature is available that discusses electrolyte solvent selection for this pairing. This study explores the role of electrolyte solvent on cycle life in LTO/NMC90-5-5 batteries. Four model electrolytes are evaluated; the baseline, Gen2, is compared with 1M LiPF 6 added to each of three separate solvents: ethylene carbonate (EC), ethyl methyl carbonate (EMC), and fluoroethylene carbonate (FEC). An additional consideration is that NMC90-5-5 undergoes an H2→H3 phase transition that allows for a significant increase to capacity; however, it’s unclear how this phase transition impacts electrolyte stability and cycle life. Therefore, the phase transition is avoided or accessed by cycling to 2.6V or 2.7V, respectively. The cells with Gen2, cycled to 2.6V, show the highest capacity retention due to EC passivating the LTO, EMC improving stability at the NMC90-5-5, and avoiding increased degradation from the 2.7V protocol. Despite having high initial reactivity that causes Li-depletion, FEC was the only solvent to avoid increased degradation when moving to the higher termination voltage.

25 ENERGY STORAGE↗
DOE OSTI2021

Storage Futures Study: Distributed Solar and Storage Outlook: Methodology and Scenarios

This report is one in a series of NREL’s Storage Futures Study (SFS) publications. The SFS is a multiyear research project that explores the role and impact of energy storage in the evolution and operation of the U.S. power sector. The SFS is designed to examine the potential impact of energy storage technology advancement on the deployment of utility-scale storage and the adoption of distributed storage, and the implications for future power system infrastructure investment and operations. The research findings and supporting data will be published as a series of reports, with each report being released on its completion. The table below lists the specific research topics planned for examination under the SFS and the associated publication formats. This report, the fourth in the SFS series, provides a set of scenarios for cost-effectiveness and customer adoption for a range of scenarios that include future technology costs and valuation of backup power. The SFS series provides data and analysis in support of the U.S. Department of Energy’s Energy Storage Grand Challenge, a comprehensive program to accelerate the development, commercialization, and utilization of next-generation energy storage technologies and sustain American global leadership in energy storage. The Energy Storage Grand Challenge employs a use case framework to ensure storage technologies can cost-effectively meet specific needs, and it incorporates a broad range of technologies in several categories: electrochemical, electromechanical, thermal, flexible generation, flexible buildings, and power electronics. More information, any supporting data associated with this report, links to other reports in the series, and other information about the broader study are available at https://www.nrel.gov/analysis/storage-futures.html.

25 ENERGY STORAGE↗
DOE OSTI2023

Interfacial Engineering and Modeling of High Energy Li Batteries

In the past 6 years, the UW team have collaborated extensively with the Battery500 Consortium team members, including The Pacific Northwest National Lab, The Idaho National Lab, Binghamton University, and UT Austin. We have accomplished all milestones and deliverables at the end of the program.

25 ENERGY STORAGE↗
DOE OSTI2023

MATBOX, an Open-Source Microstructure Analysis Toolbox for Meshing, Generation, Segmentation, and Characterization of 3D Heterogenous Volumes

Battery performance is strongly correlated with electrode microstructural properties. To account for its impact, lithium-ion battery (LIB) models either abstract the microstructural heterogeneity of composite electrodes using effective macroscopic properties (macro- or meso- scale models) or directly solve the system of equations on the microstructure geometry or mesh (microstructure-scale models). Therefore, to be adequate, both families of models require information from the microstructure geometry, which can be provided by the numerical tool presented in this work. MATBOX is a MATLAB open-source application [1] developed by NREL for performing various microstructure-related tasks including microstructure numerical generation, image filtering and microstructure segmentation, microstructure characterization and correlation, visualization, and microstructure meshing. MATBOX was originally developed for the analysis of LIB electrode microstructures; however, the algorithms provided by the toolbox are widely applicable to other heterogeneous materials. The toolbox provides a user-friendly experience thanks to a Graphical-User Interface, requires no coding by the user, and is well documented. This presentation will illustrate various MATBOX features for the characterization of a LIB electrode, including a fully automated Representative Volume Element (RVE) analysis, the numerical generation of complex 'virtual' microstructure, including dual-layer electrodes and carbon-binder additive phase, and the meshing of a complex NMC/graphite full cell microstructure suitable for 3D finite-element modeling. Other modules (segmentation, visualization, and correlation) will be briefly presented. Thanks to its modular, open-source approach, MATBOX can easily incorporate third-party algorithms to eventually build a standard in the field that will benefit the whole scientific community. Effective diffusion coefficient [2], additive phase numerical generation [3], and meshing [4] third-party algorithms have been already integrated in the toolbox with more to come.

DIRECT ENERGY CONVERSION,MATHEMATICS AND COMPUTING↗