Search NASA⌕ Search

SEARCH · Search NASA

Results for “Battery Modeling”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,297 records · Page 72
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Electron/Ion Transport Enhancer in High Capacity Li-Ion Battery Anodes

In this paper, magnetite (Fe 3 O 4 ) was used as a model high capacity metal oxide active material to demonstrate advantages derived from consideration of both electron and ion transport in the design of composite battery electrodes. The conjugated polymer, poly[3-(potassium-4-butanoate) thiophene] (PPBT), was introduced as a binder component, while polyethylene glycol (PEG) was coated onto the surface of Fe 3 O 4 nanoparticles. The introduction of PEG reduced aggregate size, enabled effective dispersion of the active materials and facilitated ionic conduction. As a binder for the composite electrode, PPBT underwent electrochemical doping which enabled the formation of effective electrical bridges between the carbon and Fe 3 O 4 components, allowing for more efficient electron transport. Additionally, the PPBT carboxylic moieties effect a porous structure, and stable electrode performance. Finally, the methodical consideration of both enhanced electron and ion transport by introducing a carboxylated PPBT binder and PEG surface treatment leads to effectively reduced electrode resistance, which improved cycle life performance and rate capabilities.

25 ENERGY STORAGE↗
DOE OSTI2019

Selective sodium-ion diffusion channels in Na 2 - x Fe 3 (PO 4 ) 3 positive electrode for Na-ion batteries

The electrochemical community around the world is focusing heavily on sodium-ion batteries R&D due to the huge abundance of sodium and need for large scale deployment of safe and inexpensive batteries for the electrical grid energy storage. Here, we observe the characterization of model parameters such as ionic diffusivity and interfacial kinetics, for a potential sodium-ion battery cathode material, Na 2 - x Fe 3 (PO 4 ) 3 , using experimental and computational investigations. The Na 2 - x Fe 3 (PO 4 ) 3 structure is characterized by two distinct one-dimensional (1-D) Na diffusion channels. Density Functional Theory (DFT) calculation reveals that Na is first fully removed from one of the channels followed by the subsequent removal of Na from the second channel. The experimental exploration reveals that, in the beginning of Na removal at 0 ≤ x ≤ 0.5; the sodium ion diffusivity is of the order of ~10 –11 cm 2 s –1 and then slightly decreases. This is further confirmed by comparing the calculated sodium diffusion barriers along the individual 1-D channels as well as between the channels. Nevertheless, the exchange current density slowly increases up to x=1.0 and remains quite constant thereafter. The magnitude of exchange current density is very low suggesting that the interfacial kinetics are the rate limiting factor. The obtained results indicate that Na 2 - x Fe 3 (PO 4 ) 3 could achieve better rate performance with long cycling stability through engineering of the particle morphology and microstructure.

25 ENERGY STORAGE↗
DOE OSTI2016

Interpretation of Simultaneous Mechanical-Electrical-Thermal Failure in a Lithium-Ion Battery Module: Preprint

Lithium-ion batteries are currently the state-of- the-art power sources for electric vehicles, and their safety behavior when subjected to abuse, such as a mechanical impact, is of critical concern. A coupled mechanical-electrical-thermal model for simulating the behavior of a lithium-ion battery under a mechanical crush has been developed. We present a series of production-quality visualizations to illustrate the complex mechanical and electrical interactions in this model.

25 ENERGY STORAGE↗
DOE OSTI2015

Electrochemical Modeling and Performance of a Lithium- and Manganese-Rich Layered Transition-Metal Oxide Positive Electrode

The impedance of a lithium- and manganese-rich layered transition-metal oxide (MR-NMC) positive electrode, specifically Li 1.2 Ni 0.15 Mn 0.55 Co 0.1 O 2 , is compared to two other transition-metal layered oxide materials, specifically LiNi 0.8 Co 0.15 Al 0.05 O 2 (NCA) and Li 1.05 (Ni 1/3 Co 1/3 Mn 1/3 ) 0.95 O 2 (NMC). A more detailed electrochemical impedance spectroscopy (EIS) study is conducted on the LMR-NMC electrode, which includes a range of states-of-charge (SOCs) for both current directions (i.e. charge and discharge) and two relaxation times (i.e. hours and one hundred hours) before the EIS sweep. The LMR-NMC electrode EIS studies are supported by half-cell constant current and galvanostatic intermittent titration technique (GITT) studies. Two types of electrochemical models are utilized to examine the results. The first type is a lithium ion cell electrochemical model for intercalation active material electrodes that includes a complex active material/electrolyte interfacial structure. In conclusion, the other is a lithium ion half-cell electrochemical model that focuses on the unique composite structure of the bulk LMR-NMC materials.

25 ENERGY STORAGE↗
DOE OSTI2020

An Atomic View of Cation Diffusion Pathways from Single‐Crystal Topochemical Transformations

Abstract The diffusion pathways of Li‐ions as they traverse cathode structures in the course of insertion reactions underpin many questions fundamental to the functionality of Li‐ion batteries. Much current knowledge derives from computational models or the imaging of lithiation behavior at larger length scales; however, it remains difficult to experimentally image Li‐ion diffusion at the atomistic level. Here, by using topochemical Li‐ion insertion and extraction to induce single‐crystal‐to‐single‐crystal transformations in a tunnel‐structured V 2 O 5 polymorph, coupled with operando powder X‐ray diffraction, we leverage single‐crystal X‐ray diffraction to identify the sequence of lattice interstitial sites preferred by Li‐ions to high depths of discharge, and use electron density maps to create a snapshot of ion diffusion in a metastable phase. Our methods enable the atomistic imaging of Li‐ions in this cathode material in kinetic states and provide an experimentally validated angstrom‐level 3D picture of atomic pathways thus far only conjectured through DFT calculations.

Handy, Joseph V.↗
DOE OSTI2018

Understanding the Lithium Storage Mechanism of Ti 3 C 2 T x MXene

MXenes, as an emerging family of conductive two-dimensional materials, hold promise for late-model electrode materials in Li-ion batteries. A primary challenge hindering the development of MXenes as electrode materials is that a complete understanding of the intrinsic storage mechanism underlying the charge/discharge behavior remains elusive. This article presents two key discoveries: first, the characteristics of the Ti 3 C 2 T x structure can be modified systematically by calcination in various atmospheres, and second, these structural changes greatly affect Li-ion storage behavior, which reveals the mechanism for lithium storage in Ti 3 C 2 T x MXene. Specifically, via ammonization, the interlayer spacing gets dilated and uniform, giving rise to only one redox couple. In stark contrast, there are two well-recognized redox couples corresponding to two interlayer spacings in pristine Ti 3 C 2 T x MXene, in which Li-ion (de)intercalation occurs between interlayers in a sequential manner as evidenced by ex situ X-ray diffraction (XRD). Notably, the XRD diffraction peaks shift hardly in the whole range of charge/discharge voltage, indicating a zero-strain feature upon Li-ion (de)intercalation. Moreover, the diffusion-controlled contribution percentage to capacity inversely depends on the scan rate. The understanding suggests a new design principle of the MXene anode: reduced lateral size to shorten the diffusion path and dilated interlayer spacing.

25 ENERGY STORAGE↗
DOE OSTI2022

Dynamics of Polymer Nanocapsule Buckling and Collapse Revealed by In Situ Liquid-Phase TEM

Nanocapsules are hollow nanoscale shells that have applications in drug delivery, batteries, self-healing materials, and as model systems for naturally occurring shell geometries. In many applications, nanocapsules are designed to release their cargo as they buckle and collapse, but the details of this transient buckling process have not been directly observed. In this work, we use in situ liquid-phase transmission electron microscopy to record the electron-irradiation-induced buckling in spherical 60-187 nm polymer capsules with ~3.5 nm walls. We observe in real time the release of aqueous cargo from these nanocapsules and their buckling into morphologies with single or multiple indentations. The in situ buckling of nanoscale capsules is compared to ex situ measurements of collapsed and micrometer-sized capsules and to Monte Carlo (MC) simulations. The shape and dynamics of the collapsing nanocapsules are consistent with MC simulations, which reveal that the excessive wrinkling of nanocapsules with ultrathin walls results from their large Föppl-von Kármán numbers around 10 5 . Our experiments suggest design rules for nanocapsules with the desired buckling response based on parameters such as capsule radius, wall thickness, and collapse rate.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

An electrostatic spectral neighbor analysis potential for lithium nitride

Machine-learned interatomic potentials based on local environment descriptors represent a transformative leap over traditional potentials based on rigid functional forms in terms of prediction accuracy. However, a challenge in their application to ionic systems is the treatment of long-ranged electrostatics. Here, we present a highly accurate electrostatic Spectral Neighbor Analysis Potential (eSNAP) for ionic α-Li 3 N, a prototypical lithium superionic conductor of interest as a solid electrolyte or coating for rechargeable lithium-ion batteries. We show that the optimized eSNAP model substantially outperforms traditional Coulomb–Buckingham potential in the prediction of energies and forces, as well as various properties, such as lattice constants, elastic constants, and phonon dispersion curves. We also demonstrate the application of eSNAP in long-time, large-scale Li diffusion studies in Li 3 N, providing atomistic insights into measures of concerted ionic motion (e.g., the Haven ratio) and grain boundary diffusion. This work aims at providing an approach to developing quantum-accurate force fields for multi-component ionic systems under the SNAP formalism, enabling large-scale atomistic simulations for such systems.

36 MATERIALS SCIENCE↗
DOE OSTI2023

The role of ionic blockades in controlling the efficiency of energy recovery in forward bias bipolar membranes

Limited understanding exists about the operation of bipolar membranes (BPMs) in forward bias to convert protonic gradients into electrical work, despite their emerging role in many electrochemical devices. In these device contexts, the BPM is typically exposed to complex electrolyte mixtures, but their impact on polarization remains poorly understood. Here, for this work, we develop a mechanistic model explaining the forward bias polarization behaviour of BPMs in mixed electrolytes with different acidities/basicities. This model invokes that weak acids/bases accumulate in the BPM and impose an ionic blockade that inhibits the recombination of stronger acids/bases, resulting in a substantial neutralization overpotential. We demonstrate the utility of our model for fuel cells and redox flow batteries and introduce two materials design strategies for mitigating this inhibition. Lastly, we apply our findings to enhance the energy efficiency of carbonate management in CO 2 electrolysers. This work highlights how non-equilibrium local environments at membrane–membrane interfaces can define the efficiency of protonic-to-electrical energy conversion.

25 ENERGY STORAGE↗
DOE OSTI2015

The migration mechanism of transition metal ions in LiNi 0.5 Mn 1.5 O 4

The migration of transition metal ions in the oxygen framework was recently proposed to be responsible for the continuous loss of average working potential of high energy density layered–layered composite cathodes for lithium-ion batteries. The potential migration pathway in a model material, LiNi 0.5 Mn 1.5 O 4 spinel, was investigated using in situ high-energy X-ray diffraction and in situ neutron diffraction during the solid state synthesis process. It was found that the migration of transition metal ions among octahedral sites is possible by using tetrahedral vacancies as intermediate sites. It was also suggested that the number of electrons in 3d orbitals has a significant impact on their mobility in the hosting oxygen framework.

25 ENERGY STORAGE↗
DOE OSTI2025

A high-throughput experimentation platform for data-driven discovery in electrochemistry

Automating electrochemical analyses combined with artificial intelligence is poised to accelerate discoveries in renewable energy sciences and technologies. This study presents an automated high-throughput electrochemical characterization (AHTech) platform as a cost-effective and versatile tool for rapidly assessing liquid analytes. The Python-controlled platform combines a liquid handling robot, potentiostat, and customizable microelectrode bundles for diverse, reproducible electrochemical measurements in microtiter plates, minimizing chemical consumption and manual effort. To showcase the capability of AHTech, we screened a library of 180 small molecules as electrolyte additives for aqueous zinc metal batteries, generating data for training machine learning models to predict Coulombic efficiencies. Key molecular features governing additive performance were elucidated using Shapley Additive exPlanations and Spearman’s correlation, pinpointing high-performance candidates like cis-4-hydroxy-d-proline, which achieved an average Coulombic efficiency of 99.52% over 200 cycles. The workflow established herein is highly adaptable, offering a powerful framework for accelerating the exploration and optimization of extensive chemical spaces across diverse energy storage and conversion fields.

Lin, Dian-Zhao [Johns Hopkins University, Baltimor↗
DOE OSTI2023

Simulation of Impedance Changes with Aging in Lithium Titanate-based Cells Using Physics-Based Dimensionless Modeling

Quantifying aging effects in lithium-ion cells with chemistries that have a flat open circuit potential is challenging. We implement a physics-based electrochemical model to track changes in the electrochemical impedance response of lithium titanate-based cells. Frequency domain equations of a pseudo two-dimensional model are made dimensionless, and the corresponding non-dimensional parameters are estimated using a Levenberg-Marquardt routine. The model weighs the relative contributions of changes in diffusion, ionic conduction within the electrolyte phase against solid phase electronic conduction towards cell aging. Solid-phase diffusion, charge transfer resistance and double layer capacitance at the solid-liquid interface are accounted for in the particle impedance. The estimation routine tracks dimensionless parameters using accelerated cycling data from full cells over 1000 cycles. The model can be deployed within a short time for state estimation using physics-based models without requiring prior knowledge of the battery chemistry, format, or capacity.

25 ENERGY STORAGE↗
DOE OSTI2025

Role of Pb/PbSO 4 Morphologies in Dynamic Charge Acceptance of Lead Acid Batteries

The dynamic charge acceptance (DCA) of negative pastes in lead acid batteries is studied using a continuum level model that is validated against in situ X-ray diffraction experiments. The model matches the current transient during a ten-minute, 2.4 V charge at 80% state of charge (SOC) using a distribution of PbSO 4 particles. <2% by volume of small, reactive particles is shown to provide ∼50% of the capacity during the first ten seconds. Increases in DCA with increasing carbon content are captured with increasing lead surface area. The increase in DCA when the 2.4 V charge is done after discharging to 80% SOC (vs charging to 80%) is captured by reducing the PbSO 4 particle sizes. It is hypothesized that the lower DCA after charging is caused by the absence of smaller particles that were consumed during the initial charge to 80% SOC, which is confirmed from X-ray measurements. Finally, two-particle case studies show that reducing the PbSO 4 particle size is more effective for increasing DCA than increasing the PbSO 4 dissolution rate alone. For a given lead surface area, the optimal DCA occurs when the particle sizes are large enough to avoid blocking the surface but small enough to provide dissolution/diffusion improvements.

Knehr, Kevin W. [Argonne National Laboratory (ANL)↗
DOE OSTI2025

ampworks: Battery analysis tools in Python [SWR-25-39]

Ampworks is a collection of tools designed to process experimental battery data with a focus on model-relevant analyses. It currently provides functions for incremental capacity analysis and GITT data processing, helping extract key properties for life and physics-based models (e.g., SPM and P2D). Some tools, like the incremental capacity analysis module, also include graphical user interfaces for ease of use. https://github.com/NREL/ampworks/ https://pypi.org/project/ampworks/

Randall, Corey [National Renewable Energy Laborato↗
DOE OSTI2020

Long-Term Vehicle Speed Prediction via Historical Traffic Data Analysis for Improved Energy Efficiency of Connected Electric Vehicles

Connected and automated vehicles (CAVs) are expected to provide enhanced safety, mobility, and energy efficiency. While abundant evidence has been accumulated showing substantial energy saving potentials of CAVs through eco-driving, traffic condition prediction has remained to be the main challenge in capitalizing the gains. The coupled power and thermal subsystems of CAVs necessitate the use of different speed preview windows for effective and integrated power and thermal management. Real-time vehicle-to-infrastructure (V2I) communications can provide an accurate speed prediction over a short prediction horizon (e.g., 30 s to 60 s), but not for a long range (e.g., over 180 s). Therefore, advanced approaches are required to develop detailed speed prediction for robust optimization-based energy management of CAVs. This paper presents an integrated speed prediction framework based on historical traffic data classification and real-time V2I communications for efficient energy management of electrified CAVs. The proposed framework provides multi-range speed predictions with different fidelity over short and long horizons. The proposed multi-range speed prediction is integrated with an economic model predictive control (MPC) strategy for the battery thermal management (BTM) of connected and automated electric vehicles (EVs). The simulation results over real-world urban driving cycles confirm the enhanced prediction performance of the proposed data classification strategy over a long prediction horizon. Despite the uncertainty in long-range CAVs’ speed predictions, the vehicle-level simulation results show that 14% and 19% energy savings can be accumulated sequentially through eco-driving and BTM optimization (eco-cooling), respectively, when compared with normal driving (i.e., human driver) and conventional BTM strategy.

Engineering↗
DOE OSTI2024

Status and prospects of lithium iron phosphate manufacturing in the lithium battery industry

Abstract Lithium iron phosphate (LiFePO 4 , LFP) has long been a key player in the lithium battery industry for its exceptional stability, safety, and cost-effectiveness as a cathode material. Major car makers (e.g., Tesla, Volkswagen, Ford, Toyota) have either incorporated or are considering the use of LFP-based batteries in their latest electric vehicle (EV) models. Despite LFP’s well-researched status as a cathode material, it is expected to fulfill additional demands in electric vehicle applications, such as fast-charging capabilities, wide temperature range adaptability, and higher energy density. This perspective examines the LFP supply chain, synthetic approaches, manufacturing processes, market trends, recent advancements, and evolving demands to better understand its future role in the EV market. Graphical abstract

Lu, Yanying↗