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This dataset contains telemetry data from the 220EV box truck as provided by the manufacturer, Dana. Data are recorded in a time series interval of 1 second. Recorded data contain odometer reading (kilometers), axle speed, state of charge of the battery, and cabin heater setting.
Capturing real-world data is critical to reducing the barriers to technology advancement for commercial vehicles. FleetREDI’s insights provide detailed duty cycle information and highlight unique aspects of the given dataset. Each insight delivers a quick look at the collected data by summarizing the operation and identifying key findings of the initial analysis. This FleetREDI insight explores propane and diesel Class 6 mail delivery trucks. Propane-powered commercial vehicles can achieve the same duty cycles and match the power, acceleration, and cruising speeds of conventionally fueled vehicles. The primary goal of the project was to demonstrate alternative fuel vehicles in a mail transport application and evaluate the viability of propane as a cost-effective alternative to conventional diesel trucks. 
This dataset contains telemetry data from the 220EV box truck as provided by the manufacturer, Dana. Data are recorded in a time series interval of 1 second. Recorded data contain odometer reading (kilometers), axle speed, state of charge of the battery, and cabin heater setting.
Capturing real-world data is critical to reducing the barriers to technology advancement for commercial vehicles. FleetREDI’s insights provide detailed duty cycle information and highlight unique aspects of the given dataset. Each insight delivers a quick look at the collected data by summarizing the operation and identifying key findings of the initial analysis. This FleetREDI insight explores propane and diesel Class 6 mail delivery trucks. Propane-powered commercial vehicles can achieve the same duty cycles and match the power, acceleration, and cruising speeds of conventionally fueled vehicles. The primary goal of the project was to demonstrate alternative fuel vehicles in a mail transport application and evaluate the viability of propane as a cost-effective alternative to conventional diesel trucks. 
This dataset contains telemetry data from the 220EV box truck as provided by the manufacturer, Dana. Data are recorded in a time series interval of 1 second. Recorded data contain odometer reading (kilometers), axle speed, state of charge of the battery, and cabin heater setting.
Capturing real-world data is critical to reducing the barriers to technology advancement for commercial vehicles. FleetREDI’s insights provide detailed duty cycle information and highlight unique aspects of the given dataset. Each insight delivers a quick look at the collected data by summarizing the operation and identifying key findings of the initial analysis. This FleetREDI insight explores propane and diesel Class 6 mail delivery trucks. Propane-powered commercial vehicles can achieve the same duty cycles and match the power, acceleration, and cruising speeds of conventionally fueled vehicles. The primary goal of the project was to demonstrate alternative fuel vehicles in a mail transport application and evaluate the viability of propane as a cost-effective alternative to conventional diesel trucks. 
This dataset contains telemetry data from the 220EV box truck as provided by the manufacturer, Dana. Data are recorded in a time series interval of 1 second. Recorded data contain odometer reading (kilometers), axle speed, state of charge of the battery, and cabin heater setting.
Capturing real-world data is critical to reducing the barriers to technology advancement for commercial vehicles. FleetREDI’s insights provide detailed duty cycle information and highlight unique aspects of the given dataset. Each insight delivers a quick look at the collected data by summarizing the operation and identifying key findings of the initial analysis. This FleetREDI insight explores propane and diesel Class 6 mail delivery trucks. Propane-powered commercial vehicles can achieve the same duty cycles and match the power, acceleration, and cruising speeds of conventionally fueled vehicles. The primary goal of the project was to demonstrate alternative fuel vehicles in a mail transport application and evaluate the viability of propane as a cost-effective alternative to conventional diesel trucks. 
This dataset contains telemetry data from the 220EV box truck as provided by the manufacturer, Dana. Data are recorded in a time series interval of 1 second. Recorded data contain odometer reading (kilometers), axle speed, state of charge of the battery, and cabin heater setting.
For more than 20 years, Argonne National Laboratory’s Vehicle & Mobility Systems Department has assessed how R&D investments by the U.S. Department of Energy’s Transportation Technologies Office and Alternative Fuels and Feedstocks Office affect vehicle energy use and cost. The analyses are performed using Autonomie, Argonne’s full-vehicle simulation tool for energy consumption, performance, and cost. The study covers five time frames ranging from present day through 2050, with more than 30 vehicle classes and applications (10 light duty and >20 medium and heavy duty), as well as six powertrain configurations (conventional, start-stop, hybrid electric vehicle, plug-in hybrid electric vehicle, battery-electric vehicle, and fuel cell electric vehicle) and five fuels (gasoline, diesel, natural gas, hydrogen, and electricity). Low and high technology uncertainty scenarios have been considered to capture a realistic range of outcomes. The resulting datasets include the assumptions used (i.e., efficiency, $/kWh), vehicle-level data (power, energy, weight, and cost), and outputs such as energy consumption, manufacturer’s suggested retail price, and total cost of ownership. These data are critical to stakeholders working in transportation, technology assessment, and long-term R&D planning.
Understanding how new vehicle technologies affect fuel economy and energy use is critical to the regulatory work performed by the U.S. Department of Transportation’s National Highway Traffic Safety Administration (NHTSA), which sets Corporate Average Fuel Economy (CAFE) standards under the Energy Policy and Conservation Act of 1975. In order to support this work, Argonne National Laboratory uses Autonomie, a full-vehicle simulation tool, to evaluate advanced powertrain architectures and their effects on vehicle energy consumption and performance. A wide range of vehicle classes has been assessed (i.e., internal combustion engine vehicles, hybrid electric vehicles, plug-in hybrid electric vehicles, battery-electric vehicles, and fuel cell electric vehicles), as well as the effects of various technology improvements such as lightweighting, aerodynamic refinements, and low-rolling-resistance tires. Simulations have been run across multiple drive cycles to capture fuel and electricity use under realistic operating conditions. The resulting datasets include detailed vehicle-level results, model assumptions, and validation reports, all of which have been made publicly available through NHTSA in support of the 2023 notice of proposed rulemaking covering light-duty vehicles for model years 2027 to 2035. These data are critical to stakeholders working in fuel economy regulation, vehicle technology assessment, and energy policy analysis.
Access to high-quality, independent vehicle test data is critical to advancing energy-efficient transportation research. The Downloadable Dynamometer Database (D3) is a public repository of dynamometer test data on advanced-technology vehicles, generated at the Advanced Mobility Technology Laboratory (AMTL) at Argonne National Laboratory and hosted by the Transportation and Power Systems Division. The database has been made available to support researchers, students, and professionals engaged in energy-efficient vehicle research, development, and education. A wide range of vehicle categories has been tested (i.e., alternative fuel vehicles, conventional gasoline and diesel vehicles, all-electric vehicles, hybrid electric vehicles, and plug-in hybrid electric vehicles), as well as various drive cycles and test conditions documented in the accompanying D3 user presentation. Stakeholders can select a vehicle type, identify a vehicle of interest, and download the associated test data for use in their own analyses. Data downloaded from D3 must be accompanied by the required attribution: "This data is from the Downloadable Dynamometer Database and was generated at the Advanced Mobility Technology Laboratory (AMTL) at Argonne National Laboratory." These data are critical to vehicle modeling, validation, technology assessment, and educational use.
This file provides nationally aggregated summary statistics to characterize the daily operations of medium- and heavy-duty vehicles. It provides typical daily driving distances, domicile dwell durations, and one version of potential normalized electric vehicle depot charging load curves. The methodology to create these data was designed with national representativeness in mind, and the data are suitable for national analysis.
As vehicle electrification expands from the light-duty sector to include larger commercial medium- and heavy-duty vehicles, businesses need to decide if electrification is appropriate for their fleets. A key factor in this decision will be the total cost of ownership for on-road electric Class 8 tractors compared to their combustion counterparts. This report examines the breakeven price of electricity for electric Class 8 tractor charging to address its importance in the total cost of ownership for the operation of an electrified fleet and to account for the inherent differences of higher-power charging. To understand the likely cost of delivered energy--in this report the breakeven price--to charge electric tractors, this study followed an analysis framework that considers a wide range of factors to estimate the breakeven price to charge at various station types. This requires an estimation of electric vehicle adoption trajectories and analysis of real-world fleet data to assess energy needs of heavy-duty electric tractors and to determine expected charging station demand over time. Station demand informs the level of electric vehicle supply equipment (EVSE) deployment that is necessary at each station type, as well as the site utilization and anticipated load profiles. Then, by accounting for a wide range of capital investments, operating costs, and other expenses, a breakeven price of energy is determined.
Although more established for light-duty vehicles (LDVs), advancements in electric vehicle (EV) charging technology are being made in the medium- and heavy-duty (MD/HD) sector. Progress is also being made with the electrification of MD/HD vehicles, including transit buses, school buses, MD trucks, and HD trucks. The diverse set of operational requirements and duty cycles for each vocation, as well as the range in the size of fleets, present unique charging and infrastructure requirements. This report focuses on charging requirements for MD/HD vehicles and synergies with LDV infrastructure. This analysis leans toward the qualitative rather than quantitative because relevant model inputs are in development and will not be established for a few years, as EV deployments are more mature in the LDV sectors than MD/HD. The report begins with an overview of MD/HD vehicle classes and types of charging, including depot and residential charging, among others (Section 2). Section 3 analyzes the home bases (overnight dwell locations) of existing MD/HD vehicles, with an emphasis on depot and residential home bases, and discusses implications for charging infrastructure. Section 4 discusses the key characteristics for determining if, when, and where MD/HD vehicles can leverage LDV charging infrastructure rather than requiring dedicated chargers. These considerations include electricity demand, connectors, physical space requirements, payment considerations, and impacts on the grid. Section 5 summarizes shared characteristics for MD/HD vehicles that are appropriate for near-term electrification and includes a summary of the outlook of the electric MD/HD vehicle market. The conclusion (Section 6) summarizes the report's findings and outlines areas for future research.
A Report on Actions for Medium- and Heavy-Duty Vehicle Energy and Emissions Innovation (the MHDV Plan) summarizes strategies and actions to substantially reduce emissions in the U.S. commercial on-road medium- and heavy-duty vehicle (MHDV) sector. This includes all on-road vehicles over 8,500 pounds used for commercial purposes. The intended audience of this report are industry and stakeholders who will take on the suite of actions needed to drive forward MHDV emissions reduction and decarbonization in a sustainable and economic way.
Final report produced as part of grant awarded to National Grid. The final report is a roadmap of 39 prioritized sites. These sites would create a minimum viable network of charging infrastructure, enabling the electrification of trucks across the Northeast