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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Battery Life Prediction Using Reduced-Order Physics Models and Machine Learning (CRADA Final Report)

Phase 1 (Original CRADA, plus no-cost extension modifications #1-3, 6/1/2017 to 3/13/2021): The Australian Department of Defence (AUDoD) is performing accelerated aging tests of Li-ion batteries to benchmark their reliability and degradation characteristics. Using its previously developed battery lifetime predictive model framework, the National Laboratory of the Rockies (NLR) will develop analytical models based the AUDoD data to predict lifetime of the multiple Li-ion battery chemistries under real-world use scenarios of interest to AUDoD. The NLR model is based on physical degradation mechanisms encountered by Li-ion batteries and has been previously validated. Phase 2 (CRADA modification #4, plus no-cost extension modification #5, 2/22/2021 to 3/30/2025): Train and support Australian Department of Defence personnel to use NLR software for model-based estimation of Li-ion battery lifetime using accelerated battery aging data collected by the Australian Department of Defence. Under separate DOE funding from 2019 to 2021, NLR enhanced its battery life-prediction software using machine learning algorithms to automate portions of the model-fitting process, requiring significantly less labor and expert judgment and also adding uncertainty quantification, increasing statistical rigor. Under Phase 2, NLR will customize NLR Software and provide it to AuDoD. NLR will enhance its NLR Model to capture aging modes of AuDoD's multi-cell modules, including cell-balancing effects. NLR will develop example single-cell and multi-cell models based on one AuDoD battery aging dataset. NLR will train AuDoD personnel on NLR Software. By the conclusion of the project, NLR will have provided AuDoD the training materials, a user manual and software needed to perform their own analysis of additional and/or future battery aging datasets.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2023

Machine-Learning Assisted Identification of Battery Life Models

Predictive battery life models are commonly utilized to extrapolate degradation trends observed during accelerated aging tests for simulation of degradation in real-world applications. Thus, fitting accelerated aging data as accurately as possible and with low uncertainty is crucial for making believable projections of battery lifetime, but it is challenging to identify algebraic expressions that accurately fit multivariate degradation trends. A review of models published in literature reveal some common expressions for fitting calendar aging data, which is only dependent on temperature and state-of-charge, but no consistency across many models for fitting cycle aging data, indicating the need for a statistically rigorous data driven approach for developing empirical models. This talk will describe a machine-learning assisted method for identification of predictive battery life models utilizing bilevel optimization and symbolic regression. Bilevel optimization with cross-validation is used to statistically determine cell- and stress-dependent model parameters, while symbolic regression identifies both linear and multiplicative candidate expressions to predict stress-dependent degradation rates by selecting low-order subsets of features from a generated feature library. Because model expressions are identified empirically, it is crucial to ensure resulting models behave according to physical expectations, so the stability of models for interpolation or extrapolation is interrogated qualitatively through simulation and quantitatively through cross-validation and uncertainty quantification via bootstrap resampling. This model identification approach substantially improves upon models identified purely using expert judgement in terms of both accuracy and uncertainty. Model simulation and validation is then conducted by deriving a state-equation form of the predictive model, enabling simulation of battery aging under dynamic stresses. This enables validation of the predictive battery model on lab-based tests with varying conditions or on drive-cycle or application-cycle testing protocols. Parameter uncertainty can be carried forward into model simulation, giving lifetime estimates and confidence windows for cell- or system-level lifetime. The financial impact of battery model uncertainty can be estimated by incorporating uncertainty into a technoeconomic model.

battery↗
DOE OSTI2023

Experimental Aging and Lifetime Prediction in Grid Applications for Large-Format Commercial Li-Ion Batteries

Due to the growth of electric vehicle and stationary energy storage markets, the production and use of lithium-ion batteries has grown exponentially in recent years. For many of these applications, large-format lithium-ion batteries are being utilized, as large cells have less inactive material relative to their energy capacity and require fewer electrical connections to assemble into packs. And especially for stationary energy storage systems, where energy delivered is the only revenue source, the economics of these battery systems is highly dependent on cell lifetime. However, testing of large-format lithium-ion batteries is time consuming and requires high current channels and large testing chambers, making information on the performance of commercial, large-format lithium-ion batteries hard to come by. Here, accelerated aging test data from four commercial large-format lithium-ion batteries is reported. These batteries span both NMC-Gr and LFP-Gr cell chemistries, pouch and prismatic formats, and a range of cell designs with varying power capabilities. Accelerated aging test results are analyzed to examine both cell performance, in terms of efficiency and thermal response under load, as well as cell lifetime. Cell thermal response is characterized by measuring temperature during cycle aging, which is used to calculated a normalized thermal resistance value that may help estimate both cell cooling needs or to help extrapolate aging test results to different thermal environments. Cell lifetime is evaluated qualitatively, considering simply the average calendar and cycle life across a range of conditions, as well as quantitatively, using statistical modeling and machine-learning methods to identify predictive aging models from the accelerated aging data. These predictive aging models are then used to investigate cell sensitivities to stressors, such as cycling temperature, voltage window, and C-rate, as well as to predict cell lifetime in various stationary storage applications. Results from this work show that cell lifetime and sensitivity to aging conditions varies substantially across commercial cells, necessitating testing for specific cell formats to make quantitative lifetime predictions. That being said, all commercial cells tested here are predicted to reach at least 10-year lifetimes for stationary storage applications. Based on the aging test results and modeling, some cells are expected to be relatively insensitive to temperature and use-case, making them suited for simple use cases with little or no thermal management and simple controls, while the lifetime of other cells could be extended to 20+ years if operated with thermal management and degradation-aware controls.

battery↗
DOE OSTI2024

Li-Ion Battery Thermal Characterization for Thermal Management Design

Battery design efforts often prioritize enhancing the energy density of the active materials and their utilization. However, optimizing thermal management systems at both the cell and pack levels is also key to achieving mission-relevant battery design. Battery thermal management systems, responsible for managing the thermal profile of battery cells, are crucial for balancing the trade-offs between battery performance and lifetime. Designing such systems requires accounting for the multitude of heat sources within battery cells and packs. This paper provides a summary of heat generation characterizations observed in several commercial Li-ion battery cells using isothermal battery calorimetry. The primary focus is on assessing the impact of temperatures, C-rates, and formation cycles. Moreover, a module-level characterization demonstrated the significant additional heat generated by module interconnects. Characterizing heat signatures at each level helps inform manufacturing at the design, production, and characterization phases that might otherwise go unaccounted for at the full pack level. Further testing of a 5 kWh battery pack revealed that a considerable temperature non-uniformity may arise due to inefficient cooling arrangements. To mitigate this type of challenge, a combined thermal characterization and multi-domain modeling approach is proposed, offering a solution without the need for constructing a costly module prototype.

25 ENERGY STORAGE↗
DOE OSTI2023

In-situ determination of moisture- and temperature-driven deflection of an encapsulated Si photovoltaic cell

Module reliability and service lifetime are critical factors in improving photovoltaic system performance and reducing the levelized cost of electricity (LCOE). Soldering and lamination of the cell impart residual stresses that persist over time and superimpose additional loads during operation. This paper demonstrates the use of X-ray Topography (XRT) to image in-situ the dynamic response of a glass/backsheet mini-module upon drying at elevated temperature after saturation at humidity levels compatible with accelerated testing. The local water content in the encapsulant is also determined in-situ over time via Water Reflectometric Detection (WaRD), with diffusion of water in the front (glass side) and rear (backsheet side) resolved. As water diffuses out from the back of the glass/backsheet module, the cell curves towards the backsheet concomitantly. Here we find that the cell edges deflect 40μm out-of-plane with respect to its center while the encapsulant dries, compared to ~100 μm deflection when heating from 25°C to 85°C. The local cell deflections (changes in cell orientation) are correlated with the dynamic loss of water in the backside encapsulant. We conclude that the observed cell deflections are the result of hygroscopic stress induced by the encapsulant upon moisture outdiffusion. Therefore, the cell experiences a continually changing stress state and curvature dependent on local humidity and temperature. Depending on cell architecture and interconnection, this “breathing” mode of the cell may induce wear out and fatigue of the interconnects, affect the electrical connection of cracked pieces or cause failure near the interconnected edges of two cells.

14 SOLAR ENERGY↗
DOE OSTI2022

Scalable High-H 2 Flux, Robust Thin Film Solid Oxide Electrolyzer

This project was aimed at the development of proton-conducting SOEC (P-SOEC) technology that has the potential to meet key DOE H 2 production targets. A decreased proton resistance of the electrolyte and Faradaic efficiency improvements were sought to increase the fraction of consumed electrolysis power that is used to actually generate H 2 , while simultaneously decreasing cost dramatically. Moreover, the development project was intended to yield maximum durability through the use of a steam protective layer. Furthermore, sputtering was used to overcome processing challenges that have hampered P-SOEC development, while the low-temperature operation goal of 500 °C was expected to aid in mitigating thermally activated long-term degradation. The approach to high-performance, lower-temperature SOECs leveraged our existing SOFC Ni-cermet anode support and extensive thin-film sputtering layer-deposition experience. Rather than an all-in-one, reversible fuel cell approach which has many unacceptable tradeoffs, we focused on the many benefits to hydrogen generating SOECs, including the existence of synergies for reduced manufacturing costs (e.g., SOECs and SOFCs share supporting layers and overall manufacturing processing). The end result of this project was expected to increase current performance at 500 °C from approximately 0.8 A/cm 2 (at 60% Faradaic efficiency) at 1.4 V to > 1 A/cm 2 (at > 95% Faradaic efficiency) with a > 40% reduction in system cost and to enable operation of P-SOECs in steam contents >> 20% for a goal of a > 40,000 hours lifetime. To enable 500 °C operation in a very high steam atmosphere (> 20%), we proposed the use of a sputtered dense thin film (~0.1-1 µm thick) of high-stability Ba(Zr,Y)O 3 (BZY) to protect the Ba(Ce,Zr,Y,Yb)O 3 (BCZYYb) electrolyte. The BZCYYb, in turn, blocks the hole conductivity of the BZY to boost Faradaic efficiency. As FE increases, more of the consumed electricity is used in electrolysis to generate H 2 , rather than being shunted. Additionally, as cell resistance decreases, the voltage required to maintain current decreases, as well as the power required to generate the same amount of H 2 . With the proposed enhancements, these two factors result in the final 46% decrease in power needed to run the system. Likewise, a production rate of 50,000 kg H 2 /day will require 55% less active area, such that a system will need only 650 cells for an 80 cm 2 active area instead of ~1,440. Taking the 2016 DOE projected current cost and modifying the electricity cost and linearly scaling the other costs (except thermal feedstock) based on the cell area improvement, results in a 44% decrease in lifetime system cost, or a decrease from $\$$4.95/kg H 2 to $\$$2.75/kg H 2 . This is well below the 2018 DOE target of $\$$4/kg H 2 . The results from this project showed that we can create a P-SOEC with enhanced steam stability using two different electrolytes (i.e., one on top of the other) and achieve sufficiently low area specific resistance (ASR) to achieve the target performance. Unfortunately, due to extended delays at the beginning of the project and related supply chain and equipment access issues, we were not able to completely show increased Faradaic efficiency for the P-SOEC and therefore were unable to demonstrate the full proof of concept within the first budget period budget. While there are still challenges that remain to be solved, significant progress was made during this project and the concept still has merit that warrants further development.

08 HYDROGEN↗
DOE OSTI2023

Light-sheet autofluorescence lifetime imaging with a single-photon avalanche diode array

Significance: Fluorescence lifetime imaging microscopy (FLIM) of the metabolic co-enzyme nicotinamide adenine dinucleotide (phosphate) [NAD(P)H] is a popular method to monitor single-cell metabolism within unperturbed, living 3D systems. However, FLIM of NAD(P)H has not been performed in a light-sheet geometry, which is advantageous for rapid imaging of cells within live 3D samples. Aim: We aim to design, validate, and demonstrate a proof-of-concept light-sheet system for NAD(P)H FLIM. Approach: A single-photon avalanche diode camera was integrated into a light sheet microscope to achieve optical sectioning and limit out-of-focus contributions for NAD(P)H FLIM of single cells. Results: An NAD(P)H light-sheet FLIM system was built and validated with fluores cence lifetime standards and with time-course imaging of metabolic perturbations in pancreas cancer cells with 10 s integration times. NAD(P)H light-sheet FLIM in vivo was demonstrated with live neutrophil imaging in a larval zebrafish tail wound also with 10 s integration times. Finally, the theoretical and practical imaging speeds for NAD(P)H FLIM were compared across laser scanning and light-sheet geometries, indicating a 30× to 6× acquisition speed advantage for the light sheet compared to the laser scanning geometry. Conclusions: FLIM of NAD(P)H is feasible in a light-sheet geometry and is attrac tive for 3D live cell imaging applications, such as monitoring immune cell metabolism and migration within an organism.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Degradation and Modeling of Large-Format Commercial Lithium-Ion Cells as a Function of Chemistry, Design, and Aging Conditions

Demand for large-format (>10 Ah) lithium-ion batteries has increased substantially in recent years, due to the growth of both electric vehicle and stationary energy storage markets. The economics of these applications is sensitive to the lifetime of the batteries, and end-of-life can either be due to energy or power limitations. Despite this, there is little information from cell manufacturers on the sensitivity of cell degradation to environmental conditions or battery use. This work reports accelerated aging test data from four commercial large-format lithium-ion batteries from three manufacturers, with varying design (thickness, casings, ...), chemistry (lithium-iron-phosphate (LFP) or lithium-nickel-manganese-cobalt-oxide positive electrodes (NMC), with graphite (Gr) negative electrodes), and capacity (50 to 250 Amp hours). The tested LFP|Gr cell is found to be relatively insensitive to cycling conditions like temperature or voltage window, while NMC|Gr cells have varying sensitivity. Degradation trends are further investigated by training predictive models: simple polynomial trend lines, a semi-empirical reduced-order model, and an empirical reduced-order model identified using machine-learning based on symbolic regression. Calendar and cycle life are simulated over a variety of conditions to directly compare the various batteries. Cell size and thickness are found to substantially impact sensitivity to temperature during cycle aging, while electrode chemistry impacts depth-of-discharge sensitivity. Real-world battery lifetime is evaluated by simulating residential energy storage and commercial frequency containment reserve systems in several U.S. climate regions. Predicted lifetime across cell types varies from 7 years to 20+ years, though all cells are predicted to have at least 10 year life in certain conditions.

battery lifetime↗
DOE OSTI2026

Early calendar life and health prediction of silicon batteries via machine learning with uncertainty quantification

Lithium-ion batteries with silicon anodes promise high energy density but are limited by calendar lifetime. Reducing the long iteration time to obtain experimental results requires predicting calendar lifetime early in a cell's life. In this study, we demonstrate that lightweight machine learning models with feature engineering can provide calendar lifetime estimates from early electrochemical signals. After 1 month of electrochemical aging, the best models achieve 10% error in calendar-life prediction and can separate "bad" from "good" lifetime cells with a mean F1 score of 0.857. As battery systems exhibit inherent variability, four methods for uncertainty quantification are compared, and confidence intervals are demonstrated with an uncertainty of +-3.6 months in lifetime prediction. A feature importance analysis indicates that early patterns in voltage decay are the strongest indicators of calendar lifetime. Finally, this modeling approach has high error when generalizing to new electrode chemistries or testing conditions but with appropriately low confidence.

25 ENERGY STORAGE↗
DOE OSTI2023

Determination of Ce 3+ , Co 2+ , Mn 2+ and Fe 2+ diffusion coefficients in Nafion® membrane

Concentration gradient diffusion coefficients for Ce 3+ , Co 2+ , Mn 2+ and Fe 2+ cations are determined in Nafion®211 membranes over a wide range of environmental conditions. Measurements are made using finite-width cation-rich bands introduced to NR211 via a hot-pressing procedure. A robust method of accurate diffusion coefficient determination of the finite-width deposits is developed using a Fick's second law of diffusion solution for one-dimensional systems. The transition metal dications are found to have nearly identical NR211 diffusion coefficients under water saturated conditions over the 22–80 °C range. The powerful chemical mitigant, Ce 3+ , is about one-half as diffusive as the dications under identical conditions. Derived diffusion coefficients for Ce 3+ and Co 2+ are found to be independent of initial cation concentration over the range of 12.5–70 mol% exchange level. The diffusion behavior of Ce 3+ in 80 °C liquid water and saturated water vapor is identical. The diffusion coefficients of Ce 3+ are shown to have a strong dependence on membrane hydration level varying by a factor of more than 30 over the range of 95 to 40% RH. Finally, the implications of these new diffusion findings are applied to a discussion of potential guidelines for the development of highly durable fuel cell systems, which employ mobile metal cations as lifetime-extending redox stabilizers.

08 HYDROGEN↗
DOE OSTI2023

Geometric Optimization of an Electrochemical Purification Cell to Prevent Corrosion in CSP Plants During Operation

When exposed to moisture or oxygen, molten chloride salts produce corrosive impurities which degrade containment alloys. This can significantly decrease the lifetime and increase costs of molten-salt-based systems. To overcome this barrier, we designed and modeled an electrochemical purification cell to remove the corrosive impurity MgOH+. Various reactor architectures, including continuous stirred tank reactors (CSTRs) and plug flow reactors (PFRs) were investigated. Steady-state thermoelectric properties were evaluated using analytical methods, allowing assessment of the effects of structure and design parameters such as flow rate, cell length, and cross-sectional area of molten salt. The results suggest that our design could most effectively increase reliability and decrease costs of molten-chloride-salt-based systems by protecting them during continuous operation using an annular plug flow reactor.

analytical modeling↗
DOE OSTI2023

Optimal Long-term Operation of SOEC Systems

This presentation was delivered at the 2023 AICHE Annual Meeting. This presentation would focus on dynamic optimization of solid oxide cell systems with due consideration of chemical degradation over the cell lifetime. A multi-scale dynamic optimization algorithm is solved and found to yield superior results compared to the constant voltage or constant H2 production operation approaches.

Giridhar, Nishant↗
DOE OSTI2024

Performance and Durability of Hybrid Fuel Cell Systems for Class-8 Long Haul Trucks

Hybrid fuel cell-battery configurations are investigated that overcome thermal management issues in fuel cell powertrains for heavy-duty Class 8 trucks. The battery is sized so that it has sufficient capacity to provide supplemental power and energy on a hill climb transient at end-of-life. A dynamic load sharing strategy is developed to distribute the power demand between the fuel cell system (FCS) and the energy storage system in a manner that optimizes their lifetimes. The FCS end-of-life is identified as the terminal point beyond which the stack cannot generate the rated power with target power density at 0.7 V and 40 °C ambient temperature. Reaching the target lifetime with a-Pt/C cathode catalyst in one hybrid configuration requires voltage clipping to 813 mV, idle power limited to 50 kW, catalyst overloading to 0.45 mg cm -2 total Pt in anode and cathode, and 44% active membrane area oversizing. The stack and FCS drive cycle efficiencies decrease by 4.2% and 5.4%, respectively, during the electrode lifetime. Further, the FCS performance, durability and cost are compared with the targets of 68% peak efficiency, 0.30 mg cm -2 total Pt loading, 2.5 kW/g PGM Pt group metal (PGM) loading, 750 mW cm -2 power density, 25,000-h lifetime and $80/kW cost.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2026

Multi-Objective Boundary Analysis of Discrete and Integrated SiC FET Modular Non-inverting Buck and Boost Converters for Fuel Cell EVs

This paper presents a multi-objective analysis of discrete and integrated SiC FET-based non-inverting buck-boost converter modules for modular fuel cell electric vehicle (EV) systems. Two converter ratings, 60 kW and 90 kW, are evaluated for both implementations, scalable up to 420 kW and 450 kW, respectively. Performance is assessed across efficiency, volumetric and gravimetric power density, cost, thermal stress, and estimated lifetime, where lifetime is derived from SiC FET B10 power-cycling data and junction temperature variations at rated power. A normalized overall performance index combined with a Pareto-boundary framework is used to identify configurations that optimally balance competing objectives. Results show that most configurations lie on the Pareto front, providing balanced trade-offs, while certain high-power discrete (90 kW at 450 kW) and integrated (60 kW at 180−420 kW) configurations are dominated. In general, discrete modules are more favorable for lower-power modular systems due to higher power density and lower cost, whereas integrated modules become more advantageous at higher power levels due to improved thermal behavior and longer lifetime. These findings provide practical design guidance for scalable fuel cell converter architectures and highlight the importance of system-level trade-offs in modular power electronics design.

Asa, Erdem [ORNL] (ORCID:0000000190884812)↗
DOE OSTI2025

Fuel cells for single-aisle regional aircraft: System configuration, performance and cost

A hydrogen fuel cell propelled electric aircraft can compete with incumbent turbofan technologies for single-aisle regional aircraft by coupling design of stack, air handling, thermal management, propulsion, and airframe to optimize performance. The stack operates at 95°C to facilitate heat rejection during take-off and below 75°C during cruise to extend lifetime and is oversized to satisfy power requirements at end of life. A multi-stage turbocompressor with a compression ratio >10 is selected to reach high stack power density at 11,300-m cruise altitude. The propulsion system is configured to accommodate air handling within the core duct, an inclined heat exchanger in the outer duct to limit the nacelle size, and variable area nozzles to independently control mass flows through the core and bypass ducts. The airframe is modified for maximum lift coefficient and longer balanced field length for dramatically reduced thrust during take-off, and the fuselage is stretched by 20% to store liquid hydrogen (LH 2 ). Modularization of power systems promotes safety in one engine inoperative scenarios and allows reaching specific power metrics for stack, balance-of-plant and fuel cell system (FCS), necessary for acceptable take-off weight. In conclusion, cost parity requires increase in FCS lifetime, LH 2 cost reduction, and improved FCS specific power.

Catalyst durability↗
DOE OSTI2026

Are Capacity and Energy Loss Equivalent Metrics for Battery Aging Reporting?

Battery aging in research publications and manufacturer specification sheets for individual cells is commonly reported as capacity (Ah) versus cycle number. However, the key measured quantity in battery-powered devices is energy (Wh), which is derived from integrating capacity with voltage. In this work, we compare the rate of capacity and energy loss across a wide range of Li-ion single-cell cycling studies with different positive electrode chemistries, charge–discharge rates, and temperatures. We find that the relative rate of discharge energy loss varies with cycling conditions. For many cells cycled under moderate conditions, the rate of discharge energy fade is only slightly faster than the rate of discharge capacity fade. However, some cells demonstrated up to a 15% decline in cycle count when 80% energy retention rather than 80% capacity retention was used as the end-of-life metric. These results highlight the importance of reporting cell aging based on energy fade to avoid overestimating battery lifetime in full systems.

batteries↗
DOE OSTI2021

Geometric Optimization of an Electrochemical Purification Cell to Prevent Corrosion in CSP Plants During Operation

When exposed to moisture or oxygen, molten chloride salts produce corrosive impurities which degrade containment alloys. As a result, this can significantly decrease the lifetime and increase costs of molten-salt-based systems. To overcome this barrier, we designed and modeled an electrochemical purification cell to remove the corrosive impurity MgOH+. Various reactor architectures, including constant stirred tank reactors (CSTRs) and plug flow reactors (PFRs) were investigated. Steady-state thermoelectric properties were evaluated, allowing assessment of the effects of structure and design parameters such as flow rate, cell length, and cross-sectional area of molten salt. The results suggest that our design could most effectively increase reliability and decrease costs of molten-chloride-salt-based systems by protecting them during continuous operation using an annular plug flow reactor.

chloride salts↗
DOE OSTI2022

Mitigating cerium migration for perfluorosulfonic acid membranes using organic ligands

Improving the electrochemical stability of proton exchange membranes is a pressing priority for heavy-duty fuel cell vehicles. The lifetime of the most widely used perfluorosulfonic acid membranes is limited by reactive free radicals generated inside the system. Cerium has been found to reduce the chemical degradation of the membranes. However, cerium migration during fuel cell operation limits the chemical durability enhancement effect expected from the radical scavenging activity of cerium. Here we investigate a wide range of organic immobilizers for cerium, measuring their suitability concerning cerium retention, radical scavenging activity, and fuel cell performance. Further, we report that partially fluorinated phosphonic acids enhance cerium retention up to 45 times and reduce fluoride emission rate by 38% compared to the commercial Nafion™ XL membrane pre-impregnated with cerium. The energetics of cerium-phosphonic acid complex systems by density functional theory calculations rationalizes effective cerium immobilization.

25 ENERGY STORAGE↗