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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 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 OSTI2024

Optimal Electrification Using Renewable Energies: Microgrid Installation Model with Combined Mixture k-Means Clustering Algorithm, Mixed Integer Linear Programming, and Onsset Method

Optimal planning and design of microgrids are priorities in the electrification of off-grid areas. Indeed, in one of the Sustainable Development Goals (SDG 7), the UN recommends universal access to electricity for all at the lowest cost. Several optimization methods with different strategies have been proposed in the literature as ways to achieve this goal. This paper proposes a microgrid installation and planning model based on a combination of several techniques. The programming language Python 3.10 was used in conjunction with machine learning techniques such as unsupervised learning based on K-means clustering and deterministic optimization methods based on mixed linear programming. These methods were complemented by the open-source spatial method for optimal electrification planning: onsset. Four levels of study were carried out. The first level consisted of simulating the model obtained with a cluster, which is considered based on the elbow and k-means clustering method as a case study. The second level involved sizing the microgrid with a capacity of 40 kW and optimizing all the resources available on site. The example of the different resources in the Togo case was considered. At the third level, the work consisted of proposing an optimal connection model for the microgrid based on voltage stability constraints and considering, above all, the capacity limit of the source substation. Finally, the fourth level involved a planning study of electrification strategies based mainly on microgrids according to the study scenario. The results of the first level of study enabled us to obtain an optimal location for the centroid of the cluster under consideration, according to the different load positions of this cluster. Then, the results of the second level of study were used to highlight the optimal resources obtained and proposed by the optimization model formulated based on the various technology costs, such as investment, maintenance, and operating costs, which were based on the technical limits of the various technologies. In these results, solar systems account for 80% of the maximum load considered, compared to 7.5% for wind systems and 12.5% for battery systems. Next, an optimal microgrid connection model was proposed based on the constraints of a voltage stability limit estimated to be 10% of the maximum voltage drop. The results obtained for the third level of study enabled us to present selective results for load nodes in relation to the source station node. Finally, the last results made it possible to plan electrification using different network technologies and systems in the short and long term. The case study of Togo was taken into account. The various results obtained from the different techniques provide the necessary leads for a feasibility study for optimal electrification of off-grid areas using microgrid systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Development of Integrated Mechanical Pods

This presentation highlights early wins, updated progress, and upcoming developments on ‘national-scale shared development platform’ for rapid prototyping, testing and validation of various integrated Mechanical Pod solutions and form factors. Such pod solutions consist of a set of all-electric heat pump mechanical equipment that have integrated functionalities through built-in controls, with heating, cooling, hot water, ventilation (including energy recovery), electrical management, and battery storage within a single package. The presentation draws inspiration from the success of bathroom pods in the US modular construction industry, UK’s efforts with unitizing mechanical systems as ‘utility cupboards’, and VEIC’s early wins in design-build of all-electric Mechanical Pod solutions in Vermont. The presentation includes researchers and partners involved with NREL in Design for Manufacturing and Assembly (DfMA), Virtual Design and Construction (VDC), and digital twin based process optimization modeling of integrated Mechanical Pod solutions. The presentation aims to highlight early wins from such a platform and how various physical and virtual tools are currently being employed as part of NREL’s ongoing multi-year project funded by US DOE. Streamlined procurement, coordination, installation, and O&M of Mechanical Pods such that the majority of work is delegated to the off-site modular factory implies monetary savings. Such a seemingly basic shift in location of the construction process leads to great reduction in complexity, first cost, lead time, and waste, and greater opportunities for innovative compartmentalization and integration of mechanical systems appropriately sized for each apartment or hotel guest room. However, past studies on unitized combination systems show that high installation costs, maintenance issues, challenges with system integration, limitations in existing electrical infrastructure, and lack of architecturally appealing solutions are key barriers. NREL and partners aim to address key barriers through DfMA approach, rapid prototyping and testing, and digital twin process optimization modeling. The presentation is also a call for interested entities to partner with NREL as part of the national-scale development platform, help drive both product and process innovation, and encourage open source sharing of learnings. Learning objectives include (1) learn about the vision of national-scale shared development platform for process-product innovation on integrated mechanical pod solutions and how to get involved, (2) gain an understanding of the components of an all-electric, high performance home, design characteristics and equipment included in an all-electric mechanical pod, integration of mechanical systems within a modular factories’ assembly line, and the system’s commissioning, operation and maintenance. The pre-planning and coordination with the factory and sub-contractors are also highlighted, (3) gain an understanding of using process modeling tools to quantify resource-constrained performance of operations (such as integration of energy efficiency strategies) to manufacture modules of varying design, (4) gain insights on virtual design, rapid prototyping, and emulated testing of various form factors across different climatic conditions. The need for such preliminary testing with open source sharing of learnings will also be highlighted.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2013

Optimal Sizing of Energy Storage and Photovoltaic Power Systems for Demand Charge Mitigation (Poster)

Commercial facility utility bills are often a strong function of demand charges -- a fee proportional to peak power demand rather than total energy consumed. In some instances, demand charges can constitute more than 50% of a commercial customer's monthly electricity cost. While installation of behind-the-meter solar power generation decreases energy costs, its variability makes it likely to leave the peak load -- and thereby demand charges -- unaffected. This then makes demand charges an even larger fraction of remaining electricity costs. Adding controllable behind-the-meter energy storage can more predictably affect building peak demand, thus reducing electricity costs. Due to the high cost of energy storage technology, the size and operation of an energy storage system providing demand charge management (DCM) service must be optimized to yield a positive return on investment (ROI). The peak demand reduction achievable with an energy storage system depends heavily on a facility's load profile, so the optimal configuration will be specific to both the customer and the amount of installed solar power capacity. We explore the sensitivity of DCM value to the power and energy levels of installed solar power and energy storage systems. An optimal peak load reduction control algorithm for energy storage systems will be introduced and applied to historic solar power data and meter load data from multiple facilities for a broad range of energy storage system configurations. For each scenario, the peak load reduction and electricity cost savings will be computed. From this, we will identify a favorable energy storage system configuration that maximizes ROI.

14 SOLAR ENERGY↗
DOE OSTI2026

Advancing Concentrating Solar Thermal Modeling Using System Advisor Model (SAM)

Concentrating solar thermal (CST) technologies play a critical role in enabling dispatchable power and high-temperature industrial heat applications. Accurate and flexible modeling tools are essential for evaluating system performance, guiding technology research and development, and informing investment decisions. The National Laboratory of the Rockies's System Advisor Model (SAM) is a widely used techno-economic simulation platform for CST systems, providing detailed performance and financial modeling capabilities for multiple CST system configurations. SAM integrates physics-based performance models with financial analysis to simulate the behavior of complex energy systems under realistic operating conditions. For CST technologies (including tower, parabolic trough, and linear Fresnel), SAM enables hourly simulations using site-specific weather data that ensure feasible operating conditions and convergence of mass and energy between core system components (i.e., solar field, receiver, thermal energy storage, and power cycle). These capabilities allow researchers and developers to evaluate annual energy production, capacity factors, levelized cost of energy (LCOE), and system dispatch strategies. A key advantage of SAM lies in its flexibility for parametric analysis and large-scale computational studies. Users can vary system design parameters such as heliostat field layout, receiver dimensions, thermal energy storage capacity, power block sizing, and installation cost assumptions to investigate their impact on system performance and financial metrics. When combined with automated scripting through LK, SDKTool, or Python interfaces, SAM enables high-throughput simulation workflows that support sensitivity analysis, technology benchmarking, and optimization studies. These approaches are particularly valuable for next-generation CST concepts, where design spaces are large and system interactions are complex. Another important capability of SAM is its support for dispatch optimization and thermal energy storage modeling, which are central to the value proposition of CST technologies. The ability to simulate integrated storage and flexible power generation allows researchers to explore strategies that maximize grid value, improve capacity utilization, and enhance integration with variable resources such as photovoltaic and wind generation. This poster will present an overview of SAM's thermal system modeling capabilities including concentrating solar. Additionally, we will highlight new feature developments including: 1) implementing Google's OR-Tools optimization platform for faster and more robust dispatch optimization, 2) developing a new power load following controller for modeling behind-the-meter applications, 3) enabling direct modeling of CSP-PV hybrid systems with the inclusion of battery storage, and 4) developing a multi-receiver falling particle Gen3 system model.

14 SOLAR ENERGY↗
DOE OSTI2023

An AFM study of Zn/MnO 2 Co-deposition (ORISE Internship Report)

With the growing demand for rechargeable batteries, the aqueous Zn-ion battery has shown promise as a cheaper and safer alternative to modern Li-ion batteries. Meanwhile, for developing batteries with optimal charge transfer, electrodes with interpenetrating geometries have been explored to minimize the distance traveled by ions in the electrolyte. Creating a Zn-ion battery with interpenetrating electrodes may allow for more efficient cycling, but requires the co-deposition of anode and cathode materials. Because of the highly sensitive nature of electrodeposition, the presence of additional ions may have an impact on the success and homogeneity of cathode/anode deposition, possibly preventing the proper function of an interpenetrating Zn battery. This study examined the effects of added ions on Zn deposition through in situ Atomic Force Microscopy with the goal of determining whether the co-deposition of Zn and MnO 2 is a viable option for electrodes with interpenetrating geometries. Solutions of 1M ZnSO 4 and 1M ZnSO 4 + 0.1M C 4 H 6 MnO 4 were made to simulate normal and co-deposition conditions. Layers of Zn were electrodeposited onto a Cu microelectrode at a current density of 10mA cm -2 with intermittent AFM imaging after 50 deposited monolayers. The presence of manganese acetate (C 4 H 6 MnO 4 ) was found to decrease Zn nucleation size on the Cu UME, suggesting the presence of C 4 H 6 MnO 4 would not negatively impact the co-deposition of Zn and MnO 2 .

25 ENERGY STORAGE↗
DOE OSTI2015

Ultra-High Temperature ContinuousReactors based on Electro-thermal FluidizedBed Concept

This paper presents the results of research and development in high-temperature (i.e. 2,000- 3,000ºС) continuous furnaces operating on the principle of electro-thermal fluidized bed for the purification of recycled, finely sized carbon materials. The basis of this fluidized bed furnace is specific electrical resistance and a new correlation has been developed to predict specific electrical resistance for the natural graphite-based precursors entering the fluidized bed reactor This correlation has been validated with the data from a fully functional pilot furnace whose throughput capacity is 10 kg per hour built as part of this work. Data collected in the course of graphite refining experiments demonstrated that difference between the calculated and measured values of specific electrical resistance of fluidized bed does not exceed 25%. It was concluded that due to chaotic nature of electro-thermal fluidized bed reactors this discrepancy is acceptable. The fluid mechanics of the three types of operating regimes, have been described. The numerical relationships obtained as part of this work allowed proposing an algorithm for selection of technological operational modes with large- scale high-temperature furnaces rated for throughputs of several tons of product per hour. Optimizations proposed now allow producing natural graphite-based end product with the purity level of 99.98+ wt%C which is the key passing criteria for applications in the advanced battery markets.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Selecting the Best Graphite for Long-Life, High-Energy Li-Ion Batteries

Here, most lithium-ion batteries still rely on intercalation-type graphite materials for anodes, so it is important to consider their role in full cells for applications in electric vehicles. Here, we systematically evaluate the chemical and physical properties of six commercially-available natural and synthetic graphites to establish which factors have the greatest impact on the cycling stability of full cells with nickel-rich LiNi0.8Mn0.1Co0.1O2 (NMC811) cathodes. Electrochemical data and post-mortem characterization explain the origin of capacity fade. The NMC811 cathode shows large irreversible capacity loss and impedance growth, accounting for much of full cell degradation. However, six graphite anodes demonstrate significant differences with respect to structural change, surface area, impedance growth, and SEI chemistry, which impact overall capacity retention. We found long cycle life correlated most strongly with stable graphite crystallite size. In addition, graphites with lower surface area generally had higher coulombic efficiencies during formation cycles, which led to more stable long-term cycling. The best graphite screened here enables a capacity retention around 90% in full pouch cells over extensive long-term cycling compared to only 82% for cells with the lowest performing graphite. The results show that optimal graphite selection improves cycling stability of high energy lithium-ion cells.

25 ENERGY STORAGE↗
DOE OSTI2019

Highly Stable Oxygen Electrodes Enabled by Catalyst Redistribution through an In Situ Electrochemical Method

Here, in this work, for the first time an in situ electrochemical pretreatment approach to fabricate a highly reversible oxygen electrode with redistributed ultrafine RuO 2 catalysts on a carbon nanotube (CNT) matrix is reported. The optimally pretreated RuO 2 /CNT oxygen electrodes demonstrate an extremely stable cycling life, 800 times with non-Li metal anode, under a capacity-limited protocol of 800 mAh g −1 in an ether-based electrolyte in an O 2 environment. The highly stable activity of ultrafine RuO 2 catalysts in oxygen reduction and evolution processes originates from the synergetic effect of greatly reduced size of catalyst (<2 nm) and uniform redistribution of catalyst particles after the in situ electrochemical pretreatment process. The pretreatment method discovered in this work can not only significantly enhance the activity/efficiency of the catalysts used for air electrodes but can also be widely applied to other electro-catalysis systems.

25 ENERGY STORAGE↗
DOE OSTI2020

Electrode Mesoscale as a Collection of Particles: Coupled Electrochemical and Mechanical Analysis of NMC Cathodes

Battery electrodes are composed of polydisperse particles and a porous, composite binder domain. These materials are arranged into a complex mesostructure whose morphology impacts both electrochemical performance and mechanical response. We present image-based, particle-resolved, mesoscale finite element model simulations of coupled electrochemical-mechanical performance on a representative NMC electrode domain. Beyond predicting macroscale quantities such as half-cell voltage and evolving electrical conductivity, studying behaviors on a per-particle and per-surface basis enables performance and material design insights previously unachievable. Voltage losses are primarily attributable to a complex interplay between interfacial charge transfer kinetics, lithium diffusion, and, locally, electrical conductivity. Mesoscale heterogeneities arise from particle polydispersity and lead to material underutilization at high current densities. Particle-particle contacts, however, reduce heterogeneities by enabling lithium diffusion between connected particle groups. While the porous composite binder domain (CBD) may have slower ionic transport and less available area for electrochemical reactions, its high electrical conductivity makes it the preferred reaction site late in electrode discharge. Mesoscale results are favorably compared to both experimental data and macrohomogeneous models. This work enables improvements in materials design by providing a tool for optimization of particle sizes, CBD morphology, and manufacturing conditions.

42 ENGINEERING↗
DOE OSTI2022

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

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

25 ENERGY STORAGE↗
DOE OSTI2018

In Situ Monitoring of the Growth of Nickel, Manganese, and Cobalt Hydroxide Precursors during Co-Precipitation Synthesis of Li-Ion Cathode Materials

The electrochemical performance of cathode materials for Li-ion batteries depends on the morphology of the material, which, in turn, depends on the synthesis conditions. Very few studies have focused on the impact of process conditions on the final morphology of the cathode particles and analyzed the growth during synthesis. In this paper, the evolution of nickel, manganese, and cobalt hydroxide precursor, Ni 1/3 Mn 1/3 Co 1/3 (OH) 2 , is investigated using a combination of in situ and ex situ techniques during the commonly-used coprecipitation process. These include in situ wide angle X-ray scattering, in-situ ultra-small angle X-ray scattering and ex situ particle size analysis. The growth rate of crystalline Ni 1/3 Mn 1/3 Co 1/3 (OH) 2 primary particle is found to be almost constant, consistent with a mathematical analysis of process. The growth of the Ni 1/3 Mn 1/3 Co 1/3 (OH) 2 secondary particle and its particle size distribution revealed different growth stages for samples prepared at different pH. These techniques are complimented with scanning electron microscopy and electrochemical testing to track the morphology and performance of the hydroxide particle and the subsequent calcined LiNi 1/3 Mn 1/3 Co 1/3 O 2 cathode active material. This study presents insights into the synthesis process and provides a deeper understanding to aid in process optimization.

Cathode precursor↗
DOE OSTI2020

Flexible Grid-Based Electrolysis Hydrogen Production for Fuel Cell Vehicles Reduces Costs and Greenhouse Gas Emissions

Hydrogen fuel cell electric vehicles (FCEVs) have been proposed as an option for lowering carbon dioxide (CO 2 ) and pollutants emissions from the transportation sector, when implemented in combination with green hydrogen production methods such as water electrolysis powered by renewable electricity. FCEVs also have the added advantages of high specific energy density and rapid refueling, two important challenges that battery electric vehicles have not yet fully overcome. Moreover, flexible operation of electrolysis could support the grid and lower electricity costs. In this paper, we simulate time-varying FCEV hydrogen refueling demand for light, medium- and heavy-duty vehicles met using electrolysis systems distributed throughout the Western U.S. power system. We find that by oversizing electrolyzers the resulting load flexibility results in different hydrogen generation temporal profiles, average electricity costs, renewable curtailment levels, and CO2 emissions. Our results indicate that increasing hydrogen production flexibility lowers hydrogen and electricity generation cost and CO 2 emissions, but there is a tradeoff between lowering operational cost and increasing electrolyzer capital cost, yielding a minimum total system cost at a size corresponding to between 80% and 90% annual capacity factor assuming a future electrolyzer cost of $300/kW.

25 ENERGY STORAGE↗
DOE OSTI2018

Synthesis and Properties of Single-Crystalline Na 4 Si 24

We present that Na 4 Si 24 is the precursor to Si 24 , a recently discovered allotrope of silicon. With a quasidirect band gap near 1.3 eV, Si 24 has potential to transform silicon-based optoelectronics including solar energy conversion. However, the lack of large, pure crystals has prevented the characterization of intrinsic properties and has delayed deposition-based metastable growth efforts. Here, we report an optimized synthesis methodology for single-crystalline Na 4 Si 24 with crystals approaching the millimeter-size scale with conditions near 9 GPa and 1123 K. Single-crystal diffraction was used to confirm the open-framework structure, and Na atoms remain highly mobile within the framework channels, as determined by electrical conductivity and electron energy loss spectroscopy measurements. In conclusion, an epitaxial relationship between Na 4 Si 24 and diamond cubic silicon (DC-Si), observed through high-resolution transmission electron microscopy, is proposed to facilitate the growth of high-quality Na 4 Si 24 crystals from DC-Si wafers mixed with metallic Na and could provide a viable path forward for scaling efforts of Na 4 Si 24 and Si 24 .

36 MATERIALS SCIENCE↗
DOE OSTI2022

Expert perspectives on the wind plant of the future

Abstract Wind power technology has changed rapidly in recent years. Technology innovation, evolving power markets, and competing land and ocean uses continue to influence the design and operation of wind turbines and plants. Anticipating these trends and their impact on future facilities can inform commercial strategies and research priorities. Drawing from a recent survey of 140 of the world's foremost wind experts, we identify expectations of future wind plant design in 2035, both for onshore and offshore wind. Experts anticipate continued growth in turbine size, to 5.5 (onshore) and 17 MW (offshore), with plants located in increasingly less favorable wind and siting regimes. They expect plant sizes of 1,100 MW for fixed‐bottom and 600 MW for floating offshore wind. Experts forecast enhanced grid‐system value from wind through significant to widespread use of larger rotors, hybrid projects with batteries and hydrogen production, and more. To explain experts' perspectives on future plant design and operation, we identify five mechanisms: economies of unit, plant, and resource scale; grid‐system value economies; and production efficiencies. We characterize learning effects as a moderating influence on the strength of these mechanisms. In combination, experts predict that these design choices support levelized cost of energy reductions of 27% (onshore) and 17%–35% (floating and fixed‐bottom offshore) by 2035 compared to today, while enhancing wind energy's grid service offerings. Our findings provide a much‐needed benchmark for representing future wind technologies in power sector models and address a critical research gap by explaining the economics behind wind energy design choices.

17 WIND ENERGY↗
DOE OSTI2014

Seniority-based coupled cluster theory

Doubly occupied configuration interaction (DOCI) with optimized orbitals often accurately describes strong correlations while working in a Hilbert space much smaller than that needed for full configuration interaction. However, the scaling of such calculations remains combinatorial with system size. Pair coupled cluster doubles (pCCD) is very successful in reproducing DOCI energetically, but can do so with low polynomial scaling (N{sup 3}, disregarding the two-electron integral transformation from atomic to molecular orbitals). We show here several examples illustrating the success of pCCD in reproducing both the DOCI energy and wave function and show how this success frequently comes about. What DOCI and pCCD lack are an effective treatment of dynamic correlations, which we here add by including higher-seniority cluster amplitudes which are excluded from pCCD. This frozen pair coupled cluster approach is comparable in cost to traditional closed-shell coupled cluster methods with results that are competitive for weakly correlated systems and often superior for the description of strongly correlated systems.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Energy Consumption and Cost Reduction of Future Light-Duty Vehicles through Advanced Vehicle Technologies: A Modeling Simulation Study Through 2050

The U.S. Department of Energy’s (DOE’s) Vehicle Technologies Office (VTO) and Hydrogen and Fuel Cell Technologies Office (HFTO) aim to develop sustainable, affordable and efficient technologies for transportation of goods and people. Translating investments in advanced transportation component technologies and powertrains to estimate vehicle-level fuel savings potential is critical for understanding DOE’s impact. In this work, we simulated technologies funded by VTO and HFTO for light duty vehicles. The simulations were performed across: Multiple powertrain configurations (i.e., conventional, power-split, extended-range electric vehicle, battery electric drive, and fuel-cell vehicles), Vehicle classes (i.e., compact car, midsize car, small sport utility vehicle [SUV], midsize SUV, and pickup trucks); and Fuels (i.e., gasoline, diesel, hydrogen, and battery electricity). These various technologies are assessed for six different timeframes: laboratory years 2015, 2020, 2025, 2030, and 2045. A delay of 5 years is assumed between laboratory year and model year (year technology is introduced into production). Finally, uncertainties are included for both technology performance and cost aspects by considering two cases: Low case, aligned with DOE technology manager estimates of expected original equipment manufacturer (OEM) improvements based on regulations, business as usual; and High case, aligned with aggressive technology advancements based on R&D targets developed through support by VTO & HFTO. These scenarios are not intended as predictions of future performances. The energy and cost impact of different technologies were estimated using Autonomie (www.autonomie.net), Argonne vehicle system simulation tool. Autonomie is a state-of-the-art vehicle system simulation tool used to assess the energy consumption, performance and cost of multiple advanced vehicle technologies across classes (from light to heavy duty), powertrains (from conventional to HEVs, FCEVs, PHEVs and BEVs), components and control strategies. Autonomie is packaged with a complete set of vehicle models for a wide range of vehicle classes, powertrain configurations and component technologies, including vehicle level and component level controls. These controls were developed and calibrated using dynamometer test data. Autonomie has been used to support a wide range of studies including analyzing various component technologies, sizing powertrains components for different vehicle requirements, comparing the benefits of powertrain configurations, optimizing both heuristic and route based vehicle energy control and predicting transportation energy use when paired with a traffic modeling tool such as POLARIS. This report documents the assumptions and estimates the vehicle-level energy consumption benefits and associated technology costs for the various types of light duty vehicles. All details of vehicle assumptions and simulation results are available in the spreadsheets accompanying this report.

33 ADVANCED PROPULSION SYSTEMS↗