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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Future Cost Benefits Analysis for Electrified Vehicles from Advances Due to U.S. Department of Energy Targets

The U.S. Department of Energy’s Vehicle Technologies Office (DOE-VTO) supports research and development (R&D), as well as deployment of efficient and sustainable transportation technologies, that will improve energy efficiency and fuel economy and enable America to use less petroleum. To accelerate the creation and adoption of new technologies, DOE-VTO has developed specific targets for a wide range of powertrain technologies (e.g., engine, battery, electric machine, lightweighting, etc.). This paper quantifies the impact of VTO R&D on vehicle energy consumption and cost compared to expected historical improvements across vehicle classes, powertrains, component technologies and timeframes. We have implemented a large scale simulation process to develop and simulate tens of thousands of vehicles on U.S. standard driving cycles using Autonomie, a vehicle simulation tool developed by Argonne National Laboratory. Results demonstrate significant additional reductions in both cost and energy consumption due to the existence of VTO R&D targets compared to predicted historical trends. It is observed that, over time, the fuel consumption of different electrified vehicles is expected to decrease by 40–50% and a reduction of 45–55% for vehicle manufacturing costs owing to significant improvements through various VTO R&D targets.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Total cost of ownership of vehicle electrification and fuel switching options for light-duty and heavy-duty vehicles

Projecting the transition from combustion engines to battery-based powertrains is complex becuase it involves numerous interdependent decisions. This study estimates total cost of ownership (TCO) to assess the economic viability of powertrain electrification, focusing exclusively on advances in vehicle and fuel technologies. Under two bounding technology-progress scenarios, we develop vehicle designs and fuel cost trajectories, which serve as inputs to TCO projections for selected classes from 2021 to 2050. We analyzed a small sport utility vehicle (SUV) to represent the light-duty vehicle (LDV) sector, and four medium- and heavy-duty vehicle (MHDV) classes: Class 6 box delivery, Class 8 drayage, Class 8 long-haul, and Class 8 transit bus. For each class, we compared the TCO of battery electric vehicles (BEVs) and fuel cell hybrid electric vehicles (FCHEVs) against conventional internal combustion engine vehicles (ICEVs). The results show that modern ICEVs generally have lower TCO; however, BEVs and FCHEVs could match or have lower TCOs than ICEVs over time, depending on technological progress. In LDVs, BEV300 is projected to deliver the lowest TCO by 2050, particularly under the high-progress scenario. In MHDVs, both BEVs and FCHEVs could become more cost-competitive than ICEVs by 2050 in the high-progress case. Beyond these results, the findings suggest further investigation is warranted for BEV charging infrastructure, FCHEV hydrogen refueling infrastructure, and MHDV charging strategies. In conclusion, these factors could reduce the fuel-cost share of TCO and enhance the competitiveness of BEVs and FCHEVs relative to ICEVs.

Battery electric vehicle↗
DOE OSTI2021

Energy, greenhouse gas, and water life cycle analysis of lithium carbonate and lithium hydroxide monohydrate from brine and ore resources and their use in lithium ion battery cathodes and lithium ion batteries

Life cycle analyses (LCAs) were conducted for battery-grade lithium carbonate (Li 2 CO 3 ) and lithium hydroxide monohydrate (LiOH·H 2 O) produced from Chilean brines (Salar de Atacama) and Australian spodumene ores. The LCA was also extended beyond the production of Li 2 CO 3 and LiOH·H 2 O to include battery cathode materials as well as full automotive traction batteries to observe the effect that the lithium production pathways had on these end products. The LCA here covers material, water, and energy flows associated with lithium acquisition; lithium concentration; production of lithium chemicals, battery cathode powders, and batteries; and associated transportation activities along the supply chain. Based on battery cathode material, the difference in lithium source represents a difference of up to 20% for NMC811 cathode greenhouse gases (GHGs) and up to 45% for NMC622 cathode GHGs. For full batteries, this represents a difference of up to 9% for NMC811 batteries and 20% for NMC622 batteries. Production of Li 2 CO 3 from brine-based resources had less life cycle GHG emissions and freshwater consumption per tonne of Li 2 CO 3 than Li 2 CO 3 from ore-based resources. And LiOH·H 2 O produced from brine-based lithium also had less life cycle GHG emissions and freshwater consumption per tonne of LiOH·H 2 O than LiOH·H 2 O from ore-based resources.

25 ENERGY STORAGE↗
NASA NTRS2019

Li-O2 Batteries for NASA Electric Aircraft (LiON)

Li-Air batteries are a unique fit for electric aircraft due to their high theoretical energy densities and their potential to leverage on-board oxygen systems. We will investigate novel "electrolyte engineering" concepts integrating computation, material fabrication and cell/pack design to obtain Li-Air batteries with high energy densities, rechargeability and safety.

Lawson, John↗
DOE OSTI2022

Breakdown of Electric Vehicle Supply Equipment Installation Costs

The plug-in electric vehicles (PEVs) market is receiving help from the current political climate, incentives at the federal and state levels, excessive cost of petroleum fuel, growing focus on climate solutions, increasing investment and direction by automobile manufacturers and increased awareness through media reports and advertising. Increasingly, the transportation industry, in both the United States and many other countries, is aimed at electric motive energy where practical. Increased investment in research and development have led to increasing vehicle range and lower battery costs; both of which have been deterrents in the past. The increasing demand for PEVs (consisting of the battery electric vehicle [BEV] and plug-in hybrid electric vehicle [PHEV], is challenged by the need for charging infrastructure to support these vehicles. The BEV relies totally on the on-board battery to supply the motive energy while the PHEV utilizes its battery and an installed internal combustion engine (ICE). The maximum benefit is achieved by using the battery power as much as possible. This arrangement requires the use of battery charging equipment, known as electric vehicle supply equipment (EVSE).

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

Clean Energy Transition for Transportation Systems: Modeling Implications

Transportation is currently the least-diversified energy demand sector, with over 90% of energy use coming from petroleum. As a result, transportation recently became the largest source of GHG emissions in the U.S. and mobility needs for passenger and freight are growing rapidly. However, after over a century of petroleum dominance, new disruptive technologies and business models offer a pathway to decarbonize the sector. Transportation is at a turning point. On the horizon lies a future where affordable and abundant renewable electricity can be used to power cost-competitive battery electric vehicles (EVs) and produce energy-dense low-carbon fuels enabling to fully decarbonize transportation systems across all modes. Exploring the clean energy transition for the multitude of different transportation systems requires new analytical modeling and approaches. This talk reviewed current work at the National Renewable Energy Laboratory (NREL) to develop and use innovative tools and analytics approaches to inform the transformation to a sustainable mobility future and the integration of transportation systems with the broader energy sector.

ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2026

Drive Cycles, Battery Pack Scaling, and Usage Considerations for Long-Haul and Regional-Haul Electric Trucks

Electrifying Class-8 heavy-duty trucks presents a promising opportunity to enhance energy efficiency and reduce freight transport costs. Battery electric trucks (BETs), once considered niche, are gaining traction due to advancements in battery technology and cost reductions. However, accurately predicting battery lifespan under realistic usage conditions remains a key challenge. Understanding battery failure mechanisms and their links to design, operation, and management is essential for developers and fleet operators. This study introduces a method to develop simplified, lab-testable dynamic stress test (DST) cycles for regional and long-haul Class-8 BETs, derived from real-world diesel truck usage. These DSTs enable benchmarking of battery technologies, identification of aging stressors, and optimization of battery design, life, and cost. The approach supports evaluation of key metrics such as levelized cost of driving and total cost of ownership, aiding fair comparisons and adoption decisions. We also propose feasible battery pack sizes that meet current driving demands with strategic charging, and a method to scale pack-level DSTs to cell-level cycles for lab-based testing. These tools facilitate tradeoff analysis across battery chemistries, pack sizing, and charging strategies, while offering means to get insights into battery aging under realistic conditions-ultimately supporting informed BET deployment decisions.

25 ENERGY STORAGE↗
DOE OSTI2023

LiH formation and its impact on Li batteries revealed by cryogenic electron microscopy

Little is known about how evolved hydrogen affects the cycling of Li batteries. Hypotheses include the formation of LiH in the solid-electrolyte interphase (SEI) and dendritic growth of LiH. Here, we discover that LiH formation in Li batteries likely follows a different pathway: Hydrogen evolved during cycling reacts to nucleate and grow LiH within already deposited Li metal, consuming active Li. We provide the evidence that LiH formed in Li batteries electrically isolates active Li from the current collector that degrades battery capacity. We detect the coexistence of Li metal and LiH also on graphite and silicon anodes, showing that LiH forms in most Li battery anode chemistries. Last, we find that LiH has its own SEI layer that is chemically and structurally distinct from the SEI on Li metal. Our results highlight the formation mechanism and chemical origins of LiH, providing critical insight into how to prevent its formation.

25 ENERGY STORAGE↗
DOE OSTI2026

Substitution or Shared Utilization? Intrahousehold Vehicle Use in Mixed-Powertrain Households

While previous research has focused heavily on understanding the factors deriving alternative fuel vehicle adoption rates, there remains a significant gap in understanding how households distribute mileage across different powertrains. This study utilizes data from the 2022 Next Generation National Household Travel Survey to investigate vehicle miles traveled within a sample of 150 plug-in electric vehicle (PEV)-owning households (in which at least one battery electric vehicle is present), characterizing how different powertrains are integrated into daily mobility. Leveraging a Seemingly Unrelated Regression (SUR) framework the study jointly models the utilization of PEVs, hybrid electric vehicles (HEV), and internal combustion engine vehicles (ICEVs) while accounting for household-level substitution effects. The results provide evidence of an asymmetric substitution effect. In households with mixed-powertrain configurations, the ICEV captures a substantially higher share of household miles (compared with the PEV), acting as a utility sponge. Conversely, the model identifies specific socioeconomic and geographic cohorts that prioritize PEV as the primary household workhorse, indicating a systematic sorting effect. Although the sample size limits broader generalizability, these findings suggest that PEVs are used for frequent, specific routine-intensive roles, whereas the ICEV remains a specialized utility vehicle. These insights highlight distinct intrahousehold vehicle use behaviors that are often obscured by aggregate fleetwide statistics.

25 ENERGY STORAGE↗
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↗
NASA NTRSDate not supplied

Battery Cell-to-Pack Scaling Trends for Electric Aircraft

Battery pack gravimetric energy density is one of the most important, yet often miss- estimated design parameters for sizing all-electric aircraft. Proper accounting for thermal, structural, and operational safety margins are frequently lost when extrapolating performance from the cell level to the aircraft level. This paper summarizes the relevant engineering and certification details needed to better account for the penalties associated when assembling battery packs. The relationship between the cell and pack energy density is not linear, as is often assumed. Furthermore, the relationship varies depending on pack requirements, cell chemistry, and architecture. Parametric, high-fidelity models are used to determine optimal battery pack sizes over a range of conditions to better quantify technology scaling effects.

Battery Electric Aircraft↗
NASA NTRSDate not supplied

Battery Cell-to-Pack Scaling Laws for Electric Aircraft

Battery pack gravimetric energy density is one of the most important, yet often miss-estimated design parameters for sizing all-electric aircraft. Proper accounting for thermal, structural, and operational safety margins are frequently lost when extrapolating performance from the cell level to the aircraft level. This paper summarizes the relevant engineering and certification details needed to better account for the penalties associated when assembling battery packs. The relationship between the cell and pack energy density is not linear, as is often assumed. Furthermore, the relationship varies depending on pack requirements, cell chemistry, and architecture. Parametric, high-fidelity models are used to determine optimal battery pack sizes over a range of conditions to better quantify technology scaling effects.

Battery Electric Aircraft↗
DOE OSTI2023

Joint optimization of electric bus charging infrastructure, vehicle scheduling, and charging management

High upfront costs of vehicles and charging infrastructure as well as the lack of knowledge related to infrastructure planning and electric bus system operation are major obstacles to the implementation of battery electric buses (BEBs). To tackle the obstacles and promote BEB adoption, a comprehensive optimization framework was developed to address the combined charging infrastructure planning, vehicle scheduling, and charging management problem for BEB systems, with the goal to minimize the total cost of ownership. The problem was formulated as a mixed-integer non-linear problem. A genetic algorithm-based approach was then proposed to solve the problem. Last, three alternative scenarios based on a sub-transit network in Salt Lake City, Utah, were analyzed and compared with the optimal scenario results in the numerical experiments. Our comparison results demonstrate the effectiveness of the proposed model and solution algorithm in determining a cost-efficient planning strategy for BEB systems.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2023

Estimating the electric vehicle charging demand of multi-unit dwelling residents in the United States

Abstract Early battery electric vehicle (EV) adopters can access home chargers for reliable charging. As the EV market grows, residents of multi-unit dwellings (MUDs) may face barriers in owning EVs and charging them without garage or parking availability. To investigate the mechanisms that can bridge existing disparities in home charging and station deployment, we characterized the travel behavior of MUD residents and estimated their EV residential charging demand. This study classifies the travel patterns of MUD residents by fusing trip diary data from the National Household Travel Survey and housing features from the American Housing Survey. A hierarchical agglomerative clustering method was used to cluster apartment complex residents’ travel profiles, considering attributes such as dwell time, daily vehicle miles traveled (VMT), income, and their residences’ US census division. We propose a charging decision model to determine the charging station placement demand in MUDs and the charging energy volume expected to be consumed, assuming that MUD drivers universally operate EVs in urban communities. Numerical experiments were conducted to gain insight into the charging demand of MUD residents in the US. We found that charging availability is indispensable for households that set out to meet 80% state of charge by the end of the day. When maintaining a 20% comfortable state of charge the entire day, the higher the VMT are, the greater the share of charging demand and the greater the energy use in MUD chargers. The upper-income group requires a greater share of MUD charging and greater daily kWh charged because of more VMT.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Projecting California Light-Duty Vehicle Attributes (2019-2035)

In this report, we estimated a set of future vehicle attribute scenarios for new light-duty vehicles for the California market using the Automotive Deployment Options Projection Tool (ADOPT). ADOPT starts simulations with all existing vehicle makes and models and endogenously creates new vehicle models over time based on assumed technology improvements and market conditions. For this study, we simulated four scenarios with varied technology, policy, and electric vehicle infrastructure assumptions. We aggregated simulation results into up to 30 vehicle classes (covering size and price classifications) for each powertrain, for six powertrains. We simulated model years 2019 to 2035. We present results for four vehicle attributes: vehicle acceleration, fuel economy (including electric and gasoline for plug-in hybrid electric vehicles [PHEVs]), vehicle range, and vehicle purchase price. We also present results showing the estimated number of vehicle models available in each vehicle class over time. In the Mid scenario, which contains conditions between our most conservative and most optimistic assumptions for emerging electric and hydrogen technologies, we observe improvements in acceleration, range (for battery-electric vehicles [BEVs]), and vehicle purchase price for electric and hydrogen powertrains. In some cases, we project that consumer preferences lead to trade-offs between vehicle attributes, such as reduced fuel economy in exchange for improved acceleration. Conventional vehicles show modest improvements in fuel economy in these scenarios due to the high numbers of BEV and PHEV sales, which reduce the improvements required in conventional vehicles to meet fleet fuel economy standards. In scenarios with advanced technology assumptions (including reduced battery price and improved energy density), we observe further improvements in BEV range and price relative to the improvements in the Mid scenario.

33 ADVANCED PROPULSION SYSTEMS↗