Search NASA⌕ Search

SEARCH · Search NASA

Results for “battery cost”

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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Development of a high fidelity CFD model for solvent evaporation and transport in porous structure during battery electrode drying

An efficient battery manufacturing process is the key to the mass production of Electric Vehicles (EV), in which drying is one of the most energy-intensive steps significantly influencing the battery cell performance. An accurate 3D CFD model for drying is essential for predicting the drying mechanism and optimizing its parameters. By optimizing the drying process, it is possible to reduce energy consumption and cost during battery manufacturing, minimize binder loading and maximize active material loading to achieve superior electrochemical performances and facilitate wider and faster public adoption of EV. This project aims to optimize the drying process during electrode manufacturing by leveraging high-fidelity, porous electrode simulations for solvent evaporation. By optimizing this process, we seek to reduce energy consumption during battery manufacturing, while minimizing binder loading and maximizing active material loading, with the overall goal of enhancing electrical vehicle performance.

Horner, Jeffrey Scott [Sandia National Laboratorie↗
DOE OSTI2025

Do Mandates Deliver Cost Reductions for Energy Storage?

In 2013, California implemented a mandate directing the state’s investor-owned utilities to procure 1325 MW of energy storage, to help integrate nondispatchable renewable sources of energy and assist the state in meeting its environmental goals. This paper evaluates this policy’s impact of both battery deployment, and cost, finding that as of 2019, the state was effective in spurring nearly 500 MWh of battery storage deployment over what would have been installed in absence of the policy. This additive deployment would have the effect of reducing global battery cell costs by roughly $1.00/ kWh, based on learning by doing. To support these findings, we utilize both a difference in differences estimation, and a synthetic control analysis, both of which allow us to compare battery deployment in California, to deployment in other states. To pair deployment to cost reduction, we use a learning curve analysis, which links battery shipments to cell and storage block costs. For policymakers, these results provide evidence to the effectiveness of mandates in promoting storage deployment and help explain how these policies can induce downstream effects.

Boff, Daniel S.↗
DOE OSTI2021

A systematic solution to quantify economic values of vehicle grid integration

We report Vehicle-Grid-Integration (VGI) supplies one of the potential benefit extensions for electric vehicles (EVs) to make use of their parking time, which enables the EVs to provide grid services while still meeting consumer driving needs. However, the costs, benefits and risks of VGI still remain unclear, which limits the development of the VGI to promote the interaction between the EV and grid. In this study, we propose an integrated framework to quantify and utilize the aggregate flexibility of the EVs to supply the grid services in electricity markets. The integrated solution includes five sub-modules that cover end-to-end functionalities from individual EV energy consumption estimation to final monetary values calculation of providing grid services. Both wholesale market and local level charging management are formulated in the optimization module. A predictive control algorithm is proposed to allocate power to individual vehicles in real time, considering uncertainties from dispatch signal and travel behavior. Simulation results from 10,000 EVs indicate that the proposed optimization methods can significantly reduce the system cost in both wholesale market and retail market. Local tariff optimization reduces the electricity cost by 24.4% compared to uncontrolled charging. Wholesale market optimization results show that $\$$691 and $\$$255 revenues can be captured by each EV in ERCOT and CAISO markets per year, although with a conservative assumption on battery throughput cost at 0.16$\$$/kWh.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

Tin-based ionic chaperone phases to improve low temperature molten sodium–NaSICON interfaces

High temperature operation of molten sodium batteries impacts cost, reliability, and lifetime, and has limited the widespread adoption of these grid-scale energy storage technologies. Poor charge transfer and high interfacial resistance between molten sodium and solid-state electrolytes, however, prevents the operation of molten sodium batteries at low temperatures. In this study, in situ formation of tin-based chaperone phases on solid state NaSICON ion conductor surfaces is shown in this work to greatly improve charge transfer and lower interfacial resistance in sodium symmetric cells operated at 110 °C at current densities up to an aggressive 50 mA cm –2 . It is shown that static wetting testing, as measured by the contact angle of molten sodium on NaSICON, does not accurately predict battery performance due to the dynamic formation of a chaperone NaSn phase during cycling. This work demonstrates the promise of sodium intermetallic-forming coatings for the advancement of low temperature molten sodium batteries by improved mating of sodium–NaSICON surfaces and reduced interfacial resistance.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Wood Carbon Based Single-Atom Catalyst for Rechargeable Zn–Air Batteries

Low-cost and efficient oxygen reduction reaction (ORR)/oxygen evolution reaction (OER) bifunctional electrocatalysts are vital for the applications of rechargeable Zn-air batteries (ZABs). Given the high catalytic activity of single-atom catalysts (SACs), preparing SACs on a large scale for ZABs is desirable but remains challenging. Herein, in situ formation of single-atom Fe-N-C catalysts on plate wood-based porous carbon is achieved via a facile Lewis acid pretreatment and carbonization process. Lewis acid FeCl3 pretreatment on the cell wall of wood not only produces abundant microchannels but also successfully introduces atomically dispersed Fe-N active species into the hierarchical structure. Such uniformly dispersive SACs on the hierarchical structure enhance the ORR/OER performance and durability. A ZAB using the catalyst in the cathode shows a high power density (70.2 mW cm -2 , at quasi solid state) and long-term stability. This work provides a new path for the large-scale preparation of high-performance SACs.

25 ENERGY STORAGE↗
DOE OSTI2026

Storing Affordability: Battery Storage as an Asset to Reduce Data Center Cost Shifts

This report examines how battery energy storage systems (BESS) can help utilities accommodate large load growth while protecting affordability for existing ratepayers. Rapid growth in electricity demand from artificial intelligence (AI) data centers is straining the U.S. grid. Furthermore, many new data centers are entering rural markets, which could offer economic benefits but may also pose implementation challenges for smaller utilities. At the same time, retail electricity prices are increasing faster than inflation, elevating customer affordability as a key challenge. While data centers have not been the primary driver of increases in residential prices to date, they have pushed wholesale energy and capacity prices higher in several markets. Fundamental utility cost-allocation principles show that data center growth can be rate-positive for existing customers only if new peak demand grows faster than the costs a utility must incur to serve it. Several factors, including a utility’s degree of wholesale market exposure, forecast uncertainty and stranded-asset risk, and tariff design can determine the outcome of load growth on retail rates. Energy storage can make several affordability contributions in the face of this landscape of uncertainty and market volatility, including deferral of higher-cost grid investments through improved utilization of existing assets and flexibility of new large loads, insulation from volatile wholesale prices through peak shaving, and reliability support to address grid risks stemming from the behavior of AI data center loads. Different potential BESS deployment pathways—utility-scale front-of-the-meter systems, aggregated small-scale storage installations, and data center-sited behind-the-meter storage—are compared against each other and against conventional capacity alternatives. This framework is intended as a conceptual resource to utilities, particularly smaller public utilities with rural service territories, who may be considering the role that energy storage can play in insulating existing ratepayers from data center cost shifts.

25 ENERGY STORAGE↗
DOE OSTI2025

Optimal sizing of battery energy storage systems for peak shaving and demand response using a degradation-aware Bayesian Optimization-Mixed-Integer Linear Programming framework

The increasing integration of renewable energy and rising electricity demand highlight the importance of battery energy storage systems for peak shaving and demand response. Unlike prior approaches that overlook operational impacts on degradation, this study proposes a Bayesian Optimization–Mixed Integer Linear Programming framework for optimal battery energy storage system sizing. In this framework, Mixed Integer Linear Programming determines short-term scheduling while a calibrated electrochemical model iteratively evaluates degradation. The central hypothesis is that the framework can efficiently identify optimal sizes that yield realistic and economically robust outcomes. The method is tested across three scenarios: peak shaving, peak shaving with energy-reduction demand response, and peak shaving with power-reduction demand response. Results show that the framework converge to the optimum within 20 iterations out of 150 possible sizes. Under baseline conditions, the framework consistently selects the smallest feasible system, minimizing unnecessary degradation costs from oversized storage. Sensitivity analyses reveal that larger systems are favored as demand rates or incentives increase. Comparisons of demand response programs indicate that power-reduction demand response offers greater economic benefits than energy-reduction demand response, although demand savings from peak shaving remain the dominant contributor to overall performance. This study demonstrates that the proposed framework balances computational tractability with degradation fidelity, identifies critical economic thresholds for investment, and offers a practical, flexible tool to guide industrial stakeholders in cost-effective battery energy storage system deployment.

Batteries↗
DOE OSTI2023

Parametric Study of Lithium-Ion Batteries using BatPaC (Final Report)

The Battery Performance and Cost Model (BatPaC) is a tool developed by Argonne National Laboratory to design lithium-ion battery (LIB) packs for automotive applications. The material demand and design specifications are used to estimate the cost of manufacturing the battery pack in a large volume production plant (5-50 GWh/year). With the option to select from various electrode chemistries and materials with their associated properties and prices, the resultant battery pack mass, volume, and cost can vary considerably. This report is the result of a parametric sensitivity study that helps identify the key parameters and prices that affect the battery metrics – the specific energy (Wh/kg) and the pack cost ($/kWh). The study was conducted with LiNi 0.6 Mn 0.2 Co 0.2 O 2 (NMC622) and graphite (G) electrodes as the baseline materials used in a battery pack for a 300-mile range battery electric vehicle (BEV300) and a 50-mile range plug-in hybrid electric vehicle (PHEV50).

25 ENERGY STORAGE↗
DOE OSTI2025

Documenting 15 Years of Reductions in U.S. Solar Photovoltaic System Costs

The U.S. Department of Energy's (DOE) Solar Energy Technologies Office (SETO) has played a key role in reducing PV system costs by supporting essential and high-impact research, development, and deployment (RD&D) activities. SETO's efforts go beyond improving technology and hardware innovations to tackle soft costs like installation labor, permitting, and customer acquisition. This holistic focus ensures that solar energy remains a viable, scalable solution for combating climate change and achieving the nation's clean energy goals. This National Renewable Energy Laboratory's (NREL) report highlights over a decade of transformative advancements in PV system technology and its cost reductions from 2010 to 2024, documenting a remarkable trajectory in line with the goals set forth by SETO. By analyzing benchmark configurations across different photovoltaic (PV) sectors over years, this work provides industry stakeholders with a comprehensive understanding of cost trends and their impact on Levelized Cost of Energy (LCOE) targets established under the 2010 SunShot Initiative.

14 SOLAR ENERGY↗
DOE OSTI2021

Impact of Hybrid Energy Storage System (HESS) Topologies on Performance: Exploration for Hydropower Hybrids

We investigate the technical performance of six HESS topologies integrated with run-of-river (ROR) hydropower to provide frequency support. We choose ROR hydropower because there are 23 GW of installed ROR hydropower in the U.S. and integrating these plants with energy storage could boost their contribution to grid services. We focus on HESSs composed of batteries and ultracapacitors because batteries are cost effective for storing energy but degrade more quickly as a function of cycling. In contrast, ultracapacitors can be cycled millions of times and are cost effective for quick injections of power. We find that active HESS topologies demonstrate the best overall improvement to grid frequency during a contingency while adhering to the power ramping limits of the HESS devices. Future work will investigate other services to identify if one HESS topology performs best for all services of interest or, more likely, different HESS topologies are best suited for specific services.

13 HYDRO ENERGY↗
DOE OSTI2023

Accelerating Battery Simulations by Using High Performance Computing and Opportunities with Machine Learning

The US Department of Energy (DOE) estimates that the battery pack cost of $60 per kilowatt-hour while increasing the driving range to over 300 miles and vehicle charging under 15 min or less would enable mass penetration of electric vehicles in the USA by 2030. These projections are based on the currently available high-density cell chemistry combined with a system level design and optimized electrodes. Electrodes for current state-of-the-art lithium-ion cell technology are fabricated from electrode slurry comprising of active material, polymeric binder, and conductive diluent such as carbon black that are coated on metal current collectors such as copper and aluminum. Given these challenging requirements for development of electrical energy storage devices for future transportation needs, a predictive simulation capability which can accelerate design by considering performance and safety implications of different geometry, materials, and chemistry choices is required. In this chapter, we discuss our state-of-the-art three-dimensional modeling framework, providing examples on battery performance and safety simulations. We also present approaches to use machine learning in the context of large datasets that are becoming available.

Allu, Srikanth↗
DOE OSTI2024

Self‐Templated 3D Sulfide‐Based Solid Composite Electrolyte for Solid‐State Sodium Metal Batteries

Abstract Rechargeable solid‐state sodium metal batteries (SSMBs) experience growing attention owing to the increased energy density (vs Na‐ion batteries) and cost‐effective materials. Inorganic sulfide‐based Na‐ion conductors also possess significant potential as promising solid electrolytes (SEs) in SSMBs. Nevertheless, due to the highly reactive Na metal, poor interface compatibility is the biggest obstacle for inorganic sulfide solid electrolytes such as Na 3 SbS 4 to achieve high performance in SSMBs. To address such electrochemical instability at the interface, new design of sulfide SE nanostructures and interface engineering are highly essential. In this work, a facile and straightforward approach is reported to prepare 3D sulfide‐based solid composite electrolytes (SCEs), which utilize porous Na 3 SbS 4 (NSS) as a self‐templated framework and fill with a phase transition polymer. The 3D structured SCEs display obviously improved interface stability toward Na metal than pristine sulfide. The assembled SSMBs (with TiS 2 or FeS 2 as cathodes) deliver outstanding electrochemical cycling performance. Moreover, the cycling of high‐voltage oxide cathode Na 0.67 Ni 0.33 Mn 0.67 O 2 (NNMO) is also demonstrated in SSMBs using 3D sulfide‐based SCEs. This study presents a novel design on the self‐templated nanostructure of SCEs, paving the way for the advancement of high‐energy sodium metal batteries.

Guo, Xiaolin↗
DOE OSTI2021

TEMPO allegro: liquid catholyte redoxmers for nonaqueous redox flow batteries

Redoxmers are organic active molecules storing energy in redox flow batteries (RFBs). Liquid redoxmers represent an extreme scenario where maximum concentration may be achieved by minimizing supporting solvents, thus maximizing the energy density of RFBs. Herein, a series of (2,2,6,6-tetramethylpiperidin-1-yl)oxyl (TEMPO)-based high potential (catholyte) liquid redoxmers, TEMPO-EG1, TEMPO-EG2, and TEMPO-EG3, were developed by incorporating polyethylene glycol (PEG) chains. Such modifications not only afford dramatic physical changes from solid to liquid and full miscibility in acetonitrile, but also impact the redox behavior. DFT calculations indicate that the incorporated PEG chains impact the charge distribution, which may account for the electrochemical changes. Importantly, compared to our previous liquid catholytes, the new redoxmers exhibit lower viscosity, which is desired for enhancing high concentration cycling performance. Furthermore, by using a hybrid flow cell, TEMPO-EG1 demonstrated more than 70% capacity retention over 100 cycles at 0.1 M and 66% capacity retention at 0.5 M, affording excellent cyclability at various concentrations. The study exemplifies how molecular engineering tuned the rheological properties of redoxmers, such as viscosity, to improve the high concentration cycling performance of RFBs, which may represent a promising avenue for a high energy density and low-cost flow battery system.

25 ENERGY STORAGE↗
DOE OSTI2024

Cost Analysis and Projections for U.S.-Manufactured Automotive Lithium-ion Batteries

This document reports on a study conducted to estimate the cost of U.S-produced automotive battery packs for model years (MY) 2023 to 2035, using Argonne National Laboratory’s BatPaC tool. The costs were estimated by designing batteries for several classes of vehicles for four discrete model years (2023, 2026, 2030, and 2035), where a representative battery technology and material prices are selected based on information available today. Correlations were developed from the four discrete years to enable annual pack cost estimates as a function of pack size (kWh) and model year. A consolidated cost curve was then developed that includes battery size, technology by model year, and the anticipated sales volumes of each class of vehicles over the years. This cost curve estimates the volume-averaged, U.S.-manufactured battery pack cost of PHEVs and BEVs in the United States to be $\$140$/kWh for the model year 2023, which will reduce to $\$86$/kWh in MY2035. Applying tax credits from section 45X of the Inflation Reduction Act can further reduce the average pack cost to as low as $\$56$/kWh in MY2029. The report also includes several sensitivity studies that investigate the effect of pack production volume, material prices, fast charge requirements, and labor rates.

25 ENERGY STORAGE↗
DOE OSTI2024

Comprehensive evaluation of commercially scalable atomic-layer-deposited alumina coating impact on full cell battery performance across varied test conditions

Atomic Layer Deposition (ALD) has emerged as a strategic enhancement method for lithium-ion battery (LIB) materials offering potential benefits and durability benefits for industrial battery production. However, the translation from laboratory achievements to commercial-scale applications has been limited. Here, this study aims to bridge this gap by comprehensively evaluating the effects of commercially scalable Al 2 O 3 ALD coatings using full pouch cell performance as a means to assess the ALD impact. We utilized large-scale slot-die coating techniques to ensure consistent electrode quality and tested four configurations of pouch cells to analyze the individual effects of ALD coating on anode and cathode electroactive materials. Our extensive testing matrix included long-term cycling, fast discharge, fast charge, leakage current, and high voltage tests. While at lower C-rates (<~1C), the influence of Al 2 O 3 coatings on cell performance is not significant. Fast charging conditions reveal that the anode ALD coating significantly enhances performance via a passivating effect, while on the cathode, it is detrimental, potentially due to increased resistance of the thin interfacial layer formed during the ALD processing. Leakage current and high-voltage tests show that the application of ALD coatings on either anode or cathode effectively minimizes side reactions at the electrode-electrolyte interface. Additionally, ALD coatings significantly mitigate concentrated and localized lithium plating on the anodes. These insights provide a valuable understanding of the potential of ALD technologies in LIB manufacturing to tailor cell performance, paving the way for safer, more efficient, and cost-effective battery solutions.

25 ENERGY STORAGE↗
DOE OSTI2023

Stabilizing lattice oxygen redox in layered sodium transition metal oxide through spin singlet state

Abstract Reversible lattice oxygen redox reactions offer the potential to enhance energy density and lower battery cathode costs. However, their widespread adoption faces obstacles like substantial voltage hysteresis and poor stability. The current research addresses these challenges by achieving a non-hysteresis, long-term stable oxygen redox reaction in the P3-type Na 2/3 Cu 1/3 Mn 2/3 O 2 . Here we show this is accomplished by forming spin singlet states during charge and discharge. Detailed analysis, including in-situ X-ray diffraction, shows highly reversible structural changes during cycling. In addition, local CuO 6 Jahn-Teller distortions persist throughout, with dynamic Cu-O bond length variations. In-situ hard X-ray absorption and ex-situ soft X-ray absorption study, along with density function theory calculations, reveal two distinct charge compensation mechanisms at approximately 3.66 V and 3.99 V plateaus. Notably, we observe a Zhang-Rice-like singlet state during 3.99 V charging, offering an alternative charge compensation mechanism to stabilize the active oxygen redox reaction.

25 ENERGY STORAGE↗
DOE OSTI2023

Optimizing Fast Charging and Wetting in Lithium-Ion Batteries with Optimal Microstructure Patterns Identified by Genetic Algorithm

To sustain the high-rate current required for fast charging electric vehicle batteries, electrodes must exhibit sufficiently high effective ionic diffusion. Additionally, to reduce battery manufacturing costs, wetting time must decrease. Both of these issues can be addressed by structuring the electrodes with mesoscale pore channels. However, their optimal spatial distribution, or patterns, is unknown. Herein, a genetic algorithm has been developed to identify these optimal patterns using a CPU-cheap proxy distance-based model to evaluate the impact of the added pore networks. Both coin-cell and pouch cell form factors have been considered for the wetting analysis, with their respective electrolyte infiltration mode. Regular hexagonal and mud-crack-like patterns, respectively, for fast charging and fast wetting were found to be optimal and have been compared with pre-determined, easier to manufacture, patterns. The model predicts that using cylindrical channels arranged in a regular hexagonal pattern is ∼6.25 times more efficient for fast charging as compared to grooved lines with both structuring strategies being restricted to a 5% electrode total volume loss. The model also shows that only a very limited electrode volume loss (1%–2%) is required to dramatically improve the wetting (5–20 times) compared to an unstructured electrode.

25 ENERGY STORAGE↗