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DOE OSTI2022

Greenhouse gases, Regulated Emissions, and Energy use in Technologies Model ® (2022 .Net)

To fully evaluate energy and emission impacts of advanced vehicle technologies and new transportation fuels, the fuel cycle from wells to wheels and the vehicle cycle through material recovery and vehicle disposal need to be considered. Sponsored by the U.S. Department of Energy's Office of Energy Efficiency and Renewable Energy (EERE), Argonne has developed a full life-cycle model called GREET (Greenhouse gases, Regulated Emissions, and Energy use in Technologies). It allows researchers and analysts to evaluate various vehicle and fuel combinations on a full fuel-cycle/vehicle-cycle basis. The first version of GREET was released in 1996. Since then, Argonne has continued to update and expand the model. GREET.Net provides the user with an easy to use and fully graphical toolbox to perform life cycle analysis simulations of alternative transportation fuels and vehicle technologies in a matter of a few clicks. It provides a comprehensive, life-cycle-based approach to compare the energy use and emissions of conventional and advanced vehicle technologies. The tool includes the data of both fuel-cycle (fuel production and vehicle operation) and vehicle-cycle (vehicle material recovery and production, vehicle component fabrication, vehicle assembly, and vehicle disposal/recycling). This public domain model is available free of charge for anyone to use.

Wang, Michael↗

DOE OSTI2023

Greenhouse gases, Regulated Emissions, and Energy use in Technologies Model ® (2023 .Net)

Wang, Michael↗

DOE OSTI2020

FY2019 Materials Annual Progress Report

The Materials Technology Program supports the Vehicle Technologies Office’s (VTO’s) mission to help consumers and businesses reduce their transportation energy costs while meeting or exceeding vehicle performance expectations. The propulsion materials research portfolio seeks to develop higher performance materials that can withstand increasingly extreme environments and address the future properties needed for a variety of high-efficiency powertrain types, sizes, fueling concepts, and combustion modes. The lightweight materials research portfolio enables improvements in fuel economy by providing properties that are equal to or better than traditional materials at a lower weight. Because it takes less energy to accelerate a lighter object, replacing cast-iron and traditional steel components with lightweight materials such as advanced high-strength steels, magnesium (Mg) alloys, aluminum (Al) alloys, and fiber-reinforced polymer composites can directly reduce a vehicle’s fuel consumption. By 2025, Materials Technology research activities seek to enable a 25% weight reduction of the glider for light-duty (LD) vehicles including body, chassis, and interior as compared to a 2015 baseline at no more than a $5/lb-saved increase in cost.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2026

Data Driven Approach to Public Opinion Mining on Autonomous Vehicles: Sentiment Analysis of Social Media Comments Using Large Language Models

In the realm of online identity, social media has emerged as a rich and dynamic source of user-generated content, making it an invaluable resource for understanding public sentiment on a wide range of topics. Individuals often share their raw emotions and candid opinions on these platforms without fear of judgment or backlash. In this study, we conduct a sentiment analysis on user comments collected from various online platforms, with a specific focus on discussions surrounding autonomous vehicles. Leveraging the capabilities of large language models (LLMs), we classify each comment into one of five sentiment categories: Very Negative, Negative, Neutral, Positive, and Very Positive. Our approach demonstrates the effectiveness of LLMs in capturing nuanced contextual sentiment, offering a scalable and state-of-the-art alternative to traditional manual annotation methods. The results reveal key trends and insights into public perception, enabling a deeper understanding of how autonomous vehicle technologies are received by the online community. Our findings underscore the dynamic nature of public sentiment, which is shaped not only by advances in autonomous vehicle technology but also by contextual events such as regulatory developments, political adjustment and safety incidents.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2021

FY2020 Materials Annual Progress Report

The Materials Technology subprogram supports the Vehicle Technologies Office’s (VTO’s) mission to accelerate the deployment of clean energy technology toward achieving net-zero emissions in the transportation sector. The Propulsion Materials research portfolio seeks to develop higher performance materials that can withstand increasingly extreme environments and address the future properties needed for a variety of high-efficiency powertrain types, sizes, fueling concepts, and combustion modes. The Lightweight Materials research portfolio enables improvements in fuel economy by providing properties that are equal to or better than traditional materials at a lower weight. Because it takes less energy to accelerate a lighter object, replacing cast-iron (Fe) and traditional steel components with lightweight materials—such as advanced high-strength steels (AHSS), magnesium (Mg) alloys, aluminum (Al) alloys, and fiber-reinforced polymer composites—can directly reduce a vehicle’s fuel consumption. By 2025, the Materials Technology research activities seek to enable a 25% weight reduction of the glider for light-duty (LD) vehicles including body, chassis, and interior as compared to a 2015 baseline at no more than a $5/lb-saved increase in cost.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2023

The Convergence of Vehicle Electrification and Automation - Enabling Sustainable Automated Mobility Districts

The transportation industry is entering a new frontier with three major simultaneous transformations: electrification, automation, and on-demand services. All three directly affect the same spaces of vehicle technology, infrastructure, and system operational performance. Further, each area of change adds its own driving forces of complexity to the others' design challenges. This paper explores these transformations, framing the implications for vehicle technology and infrastructure and their impact on operating concepts and strategies, which in turn impact the sustainability of the transportation infrastructure in the built environment. Specifically, this paper examines battery-electric vehicles operating in a fully automated fleet within an "automated mobility district" (AMD) setting with multiple on-demand services. From this examination, the paper assesses the implications for transportation electrification, comparing and contrasting traditional fixed-route services with those of on-demand transit and automated transit networks, including the trade-offs between vehicle range (battery capacity), charging parameters, power availability, and operations predictability with respect to policy and infrastructure configurations. The paper also addresses the configuration and management of boarding and alighting zones (also called pickup and drop-off zones), and the need for complementary infrastructure intelligence at intersections and curbs. Finally, conclusions are drawn with respect to the system integration and analysis needs for AMDs regarding resilience and sustainability of mobility infrastructure.

ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2021

Household Transportation Energy Affordability by Region and Socioeconomic Factors

Transportation fuel is an important component of household budgets, as 3.3% of total household expenditures are for vehicle fuel nationwide and over 50% of annual household expenditures on energy are for transportation. These average values vary geographically, and higher energy cost burdens are faced by households with lower incomes. Defining transportation energy affordability burden as the percentage of annual household income spent on vehicle fuel, this study aims to quantify affordability as a function of household characteristics and geography. Here, through analysis at the census tract level, this study (i) projects annual household vehicle miles traveled (VMT) based on demographic factors using machine-learning techniques, (ii) estimates local differences in vehicle fuel economy and fuel price, and (iii) quantifies resulting transportation energy affordability by census tract. This study found that the average burden by tract varies from 0.15% to 8%. The variation in affordability can be largely explained by income level and vehicle fuel efficiency. Suburban and rural households spend more on transportation energy compared with urban households because of the usage of less fuel-efficient vehicle technologies and higher annual VMT. Lower-income groups have a wide distribution of the percentage of income spent on transportation energy, 1.2% to 8%, whereas the range for the highest income group ($125,000+) is from 0.15% to 3.9%. This detailed transportation energy affordability analysis provides a better understanding of regional variations in household travel behavior, helps to determine where fuel-efficient vehicle technologies are more likely to be used, and improves estimates of vehicle ownership costs.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2025

Device- and System-Level Thermal Packaging for Electric-Drive Technologies (Final Technical Report)

Final Technical ReportThis project aimed to research, develop, and test electric traction drive system technology for use in vehicle applications that are capable of meeting the targets set by the Department of Energy Vehicle Technologies Office. The project is categorized into three major thrusts: Bonding interfaces for packaging, thermal management of electric vehicle (EV) power inverters, and electric motor thermal management. Device- and System-Level Thermal Packaging for Electric-Drive Technologies project aimed to develop, analyze, and validate transformative approaches in thermal management and packaging for power electronics and electric motor systems, with the ultimate goal of enhancing power density, efficiency, and reliability in electrified transportation platforms.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2021

BATPAC--VERSION 5.0

Argonne National Laboratory has worked on electrochemical energy storage for several decades. The focus on lithium-ion chemistries started in the early 1990s, developing new materials, synthesis methods, and performance characterizations. Sponsored by the U.S. Department of Energy, Energy Efficiency and Renewable Energy, Vehicle Technologies Office (DOE-EERE-VTO), Argonne has led with many advances. The experimental activities were complemented with multi-scale modeling that ranged from the atomic to the system (manufacturing processes and automobiles) level. The Battery Performance and Cost (BatPaC) model is a calculation method based on Microsoft¿ Office Excel spreadsheets that have been developed at Argonne for estimating the performance and manufacturing cost of lithium-ion batteries for electric-drive vehicles including hybrid-electrics (HEV), plug-in hybrids (PHEV) and pure electrics. The effort is being funded by the Vehicle Technology Office (VTO), which is part of the Energy Efficiency and Renewable Energy (EERE) office of the U.S. Department of Energy (USDOE). BatPaC was first developed in 2007, was subsequently peer-reviewed, and it has served Argonne researchers and the greater battery community in studying the impact of material properties on performance at the pack level. With further developments, the model now allows the design of cells and battery packs for automotive applications, to meet performance requirements (power, energy, recharge time), and estimates the cost of manufacturing the designed batteries. Since the cost depends on the materials he design, and the manufacturing process, this bottom-up model/tool enables the user to study their effects. Designed or the lithium-ion cell and battery researcher, BatPaC helps answer many questions by being 1.Transparent in the assumptions made and the method of calculation 2.Capable of designing a battery specifically for the requirements of an application 3.Constrained by the physical limitations that govern battery performance 4. A bottom-up calculation approach to account for every cost factors. BatPaC predicts the impact of promising materials (and their properties) on the performance metrics relevant for the different applications. Researchers can use the specific capacities and the half-cell voltages of a particular set of electrode materials to calculate the mass and volume of a cell to develop a model incorporating the properties of all the other materials in the cell and the design of the cell enclosure. These calculations not only reveal the impact of an improved material but also enable researchers to calculate the material properties that would be needed to meet the performance criteria of a full battery pack. With this information, researchers can provide he battery industry with realistic expectations that will help it more successfully advance novel battery technologies an Applications.

AHMED, SHABBIR↗

DOE OSTI2020

Greenhouse gases, Regulated Emissions, and Energy use in Technologies Model ® (2020 Excel)

To fully evaluate energy and emission impacts of advanced vehicle technologies and new transportation fuels, the fuel cycle from wells to wheels and the vehicle cycle through material recovery and vehicle disposal need to be considered. Sponsored by the U.S. Department of Energy's Office of Energy Efficiency and Renewable Energy (EERE), Argonne has developed a full life-cycle model called GREET (Greenhouse gases, Regulated Emissions, and Energy use in Technologies). It allows researchers and analysts to evaluate various vehicle and fuel combinations on a full fuel-cycle/vehicle-cycle basis. The first version of GREET was released in 1996. Since then, Argonne has continued to update and expand the model. GREET is developed as a multidimensional spreadsheet model in Microsoft Excel. It provides a comprehensive, life-cycle-based approach to compare the energy use and emissions of conventional and advanced vehicle technologies. It includes two sub-models named Fuel-Cycle Model (GREET 1, contains data on fuel cycles and vehicle operations) and Vehicle-Cycle Model (GREET 2, evaluates the energy and emission effects associated with vehicle material recovery and production, vehicle component fabrication, vehicle assembly, and vehicle disposal/recycling). This public domain model is available free of charge for anyone to use.

Wang, Michael↗

DOE OSTI2021

Greenhouse gases, Regulated Emissions, and Energy use in Technologies Model ® (2021 Excel)

To fully evaluate energy and emission impacts of advanced vehicle technologies and new transportation fuels, the fuel cycle from wells to wheels and the vehicle cycle through material recovery and vehicle disposal need to be considered. Sponsored by the U.S. Department of Energy's Office of Energy Efficiency and Renewable Energy (EERE), Argonne has developed a full life-cycle model called GREET (Greenhouse gases, Regulated Emissions, and Energy use in Technologies). It allows researchers and analysts to evaluate various vehicle and fuel combinations on a full fuel-cycle/vehicle-cycle basis. The first version of GREET was released in 1996. Since then, Argonne has continued to update and expand the model. GREET is developed as a multidimensional spreadsheet model in Microsoft Excel. It provides a comprehensive, life-cycle-based approach to compare the energy use and emissions of conventional and advanced vehicle technologies. It includes two sub-models named Fuel-Cycle Model (GREET 1, contains data on fuel cycles and vehicle operations) and Vehicle-Cycle Model (GREET 2, evaluates the energy and emission effects associated with vehicle material recovery and production, vehicle component fabrication, vehicle assembly, and vehicle disposal/recycling). This public domain model is available free of charge for anyone to use.

Wang, Michael↗

DOE OSTI2022

Greenhouse gases, Regulated Emissions, and Energy use in Technologies Model ® (2022 Excel)

To fully evaluate energy and emission impacts of advanced vehicle technologies and new transportation fuels, the fuel cycle from wells to wheels and the vehicle cycle through material recovery and vehicle disposal need to be considered. Sponsored by the U.S. Department of Energy's Office of Energy Efficiency and Renewable Energy (EERE), Argonne has developed a full life-cycle model called GREET (Greenhouse gases, Regulated Emissions, and Energy use in Technologies). It allows researchers and analysts to evaluate various vehicle and fuel combinations on a full fuel-cycle/vehicle-cycle basis. The first version of GREET was released in 1996. Since then, Argonne has continued to update and expand the model. GREET is developed as a multidimensional spreadsheet model in Microsoft Excel. It provides a comprehensive, life-cycle-based approach to compare the energy use and emissions of conventional and advanced vehicle technologies. It includes two sub-models named Fuel-Cycle Model (GREET 1, contains data on fuel cycles and vehicle operations) and Vehicle-Cycle Model (GREET 2, evaluates the energy and emission effects associated with vehicle material recovery and production, vehicle component fabrication, vehicle assembly, and vehicle disposal/recycling). This public domain model is available free of charge for anyone to use.

Wang, Michael↗

DOE OSTI2023

Greenhouse gases, Regulated Emissions, and Energy use in Technologies Model ® (2023 Excel)

To fully evaluate energy and emission impacts of advanced vehicle technologies and new transportation fuels, the fuel cycle from wells to wheels and the vehicle cycle through material recovery and vehicle disposal need to be considered. Sponsored by the U.S. Department of Energy's Office of Energy Efficiency and Renewable Energy (EERE), Argonne has developed a full life-cycle model called GREET (Greenhouse gases, Regulated Emissions, and Energy use in Technologies). It allows researchers and analysts to evaluate various vehicle and fuel combinations on a full fuel-cycle/vehicle-cycle basis. The first version of GREET was released in 1996. Since then, Argonne has continued to update and expand the model. GREET is developed as a multidimensional spreadsheet model in Microsoft Excel. It provides a comprehensive, life-cycle-based approach to compare the energy use and emissions of conventional and advanced vehicle technologies. It includes two sub-models named Fuel-Cycle Model (GREET 1, contains data on fuel cycles and vehicle operations) and Vehicle-Cycle Model (GREET 2, evaluates the energy and emission effects associated with vehicle material recovery and production, vehicle component fabrication, vehicle assembly, and vehicle disposal/recycling). This public domain model is available free of charge for anyone to use.

Wang, Michael↗

DOE OSTI2022

A Comprehensive Simulation Study to Evaluate Future Vehicle Energy and Cost Reduction Potential

Under the umbrella of EERE’s Office of Sustainable Transportation, the U.S. Department of Energy’s (DOE) Vehicle Technologies Office (VTO) and Hydrogen and Fuel Cell Technologies Office (HFTO) seek to develop sustainable, affordable, and efficient technologies for transportation of goods and people. Translating investments in advanced transportation component technologies and powertrains to estimate the potential for vehicle-level fuel savings is critical to understanding DOE’s impact and success in this mission For this study, Argonne National Laboratory (Argonne) simulated technologies funded by VTO and HFTO for light-duty vehicles across the following: Powertrain configurations (conventional, power-split hybrid electric vehicle, extended-range electric vehicle, battery electric drive, and fuel-cell vehicles); Vehicle classes (compact car, mid-size car, small sport utility vehicle [SUV], mid-size SUV, and pickup truck); Fuels (gasoline, diesel, natural gas, hydrogen, and battery electricity). We assessed each technology for five different timeframes: laboratory years 2015 (reference), 2020, 2025, 2030, and 2045. We assumed a delay of 5 years between laboratory year and model year (i.e., the year the technology is introduced into production). Finally, we included uncertainties for both technology performance and cost by considering two cases (note that these cases are not intended as predictions of future performance): Low case , aligned with DOE technology manager estimates of expected original equipment manufacturer (OEM) improvements based on business as usual regulatory and market environments; High case , aligned with aggressive technology advancements based on research and development (R&D) targets developed through support by VTO and HFTO. We estimated the energy and cost impact of different technologies using Autonomie (Argonne undated), a state-of-the-art vehicle system simulation tool developed by Argonne and used to assess the energy consumption, performance, and cost of multiple advanced vehicle technologies. The tool comprises a complete set of vehicle models to assess impacts across a wide range of classes (from light- to heavy-duty), powertrain configurations (from conventional to hybrid electric vehicles [HEVs], fuel cell electric vehicles [FCEVs], plug-in hybrid electric vehicles [PHEVs], and battery electric vehicles [BEVs]), components, and control strategies, including vehicle-level and component-level controls developed and calibrated using dynamometer test data. Autonomie has been used to support a wide range of studies: analyzing various component technologies, sizing powertrain components to meet 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 made and the vehicle-level energy consumption benefits and associated technology costs estimated for various types of light-duty vehicles. Details regarding vehicle assumptions and simulation results are available in the spreadsheets accompanying this report.

08 HYDROGEN↗

DOE OSTI2020

Energy Prediction of the Chicago Metropolitan Area Using Distributed Transportation MBSE Framework

Energy consumption impact of vehicle powertrain is traditionally assessed using standard and regulatory drive cycles. In this paper, energy consumption is determined by studying all the trips occurring in the Chicago Metropolitan Area in a 24 hour period. The data is generated by combining Polaris, an agent based traffic flow model with SVTrip, a stochastic model that generates 1 Hz vehicle speed profiles and Autonomie, a detailed vehicle level modeling tool used to predict fuel consumption. Different scenarios are constructed to define trips for different timeframes and assumptions. Vehicle fleet distribution, vehicle technologies and automation levels are applied to represent an appropriate vehicle fleet for each scenario. Analysis of energy consumption is then discussed with a particular emphasis on the impact of powertrain technology and vehicle types.

Autonomie↗

DOE OSTI2022

Exploring the potential of hydrogen in decarbonizing China's light-duty vehicle market

The Chinese government has pledged to achieve overall carbon neutrality by 2060. Currently, the transportation sector contributes to about 10% of total greenhouse gas (GHG) emissions in China. Hence, China has created a well-defined energy vehicle development strategy to reduce GHG emissions from the transportation sector, further expanding into hydrogen vehicle technologies. In this study, the Transportation Energy Analysis Model (TEAM) investigates the potential of hydrogen internal combustion engine vehicles (H2- ICEVs) and fuel cell vehicles (FCEVs) as a reliable pathway towards the government's aspiration of carbon neutrality in the transportation sector. According to TEAM, by adopting FCEVs and H2-ICEVs in the vehicle market, hydrogen demand could reach 25% of the total light-duty transportation energy demand in 2050. Consequently, this will lead to an annual reduction of more than 35 million tons GHG compared to only counting on the electrification pathway in the decarbonization task. Besides, FCEVs would take longer to penetrate the light-duty vehicle market compared to H2-ICEVs, as the current fuel cell technology still requires much improvement to attain a competitive vehicle cost of production.

Life cycle analysis↗

DOE OSTI2022

Vehicle and Mobility Technologies 2021 Annual Impact Report

Research and development at the National Renewable Energy Laboratory supports the U.S. Department of Energy's Vehicle Technologies Office in advancing efficient and sustainable transportation technologies that will improve energy efficiency, fuel economy, and mobility energy productivity, and will enable America to achieve a resilient, secure, clean, and affordable transportation future.

ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2022

Vehicle and Mobility Technologies 2022 Annual Impact Report

ADVANCED PROPULSION SYSTEMS↗