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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
NASA NTRS2017

Drawbar Pull (DP) Procedures for Off-Road Vehicle Testing

As NASA strives to explore the surface of the Moon and Mars, there is a continued need for improved tire and vehicle development. When tires or vehicles are being designed for off-road conditions where significant thrust generation is required, such as climbing out of craters on the Moon, it is important to use a standard test method for evaluating their tractive performance. The drawbar pull (DP) test is a way of measuring the net thrust generated by tires or a vehicle with respect to performance metrics such as travel reduction, sinkage, or power efficiency. DP testing may be done using a single tire on a traction rig, or with a set of tires on a vehicle; this report focuses on vehicle DP tests. Though vehicle DP tests have been used for decades, there are no standard procedures that apply to exploration vehicles. This report summarizes previous methods employed, shows the sensitivity of certain test parameters, and provides a body of knowledge for developing standard testing procedures. The focus of this work is on lunar applications, but these test methods can be applied to terrestrial and planetary conditions as well. Section 1.0 of this report discusses the utility of DP testing for off-road vehicle evaluation and the metrics used. Section 2.0 focuses on test-terrain preparation, using the example case of lunar terrain. There is a review of lunar terrain analogs implemented in the past and a discussion on the lunar terrain conditions created at the NASA Glenn Research Center, including methods of evaluating the terrain strength variation and consistency from test to test. Section 3.0 provides details of the vehicle test procedures. These consist of a review of past methods, a comprehensive study on the sensitivity of test parameters, and a summary of the procedures used for DP testing at Glenn.

wheel↗
DOE OSTI2022

ARIES: NREL Off-Road Decarbonization and Energy Systems Integration Workshop - Challenges and Opportunities

This presentation about ARIES was given at the NREL Off-Road Decarbonization and Energy Systems Integration Workshop - Challenges and Opportunities. ARIES was designed to fill a significant gap: there is no research platform that can support the nation's transition to a decarbonized energy system. ARIES will demonstrate and de-risk a future energy system with more than 50% renewable generation by 2030, that is just, affordable, flexible, clean, secure, resilient, and reliable, even in the off-road transportation sector.

ARIES↗
DOE OSTI2022

Electrifying Road Trips to and from National Parks in the Western United States

We evaluate charging infrastructure requirement for electrified long-distance travels to/from national parks in the Western U.S. We conduct a high-resolution spatial and temporal analysis of road trips in the region, accounting for detailed travel volume and pattern, the type of electric vehicles, heterogeneous energy consumption rates depending on driving conditions, charging technology (e.g., power and speed), and charging behavior. The scope includes on-route (or way-point) charging as well as destination charging (in national parks). We estimate the locations and sizes of required charging stations in the entire Western U.S. to enable electrified road trips to/from national parks. We also examine environmental justice and energy equity aspects of projected charging infrastructure (for national parks) in the context of the overall vehicle electrification and charging infrastructure build-out.

ADVANCED PROPULSION SYSTEMS,ENERGY PLANNING, POLIC↗
DOE OSTI2026

Automatic Lane-Level Road Network Extraction from Aerial Imagery for Transportation Digital Twins

Accurate road networks are essential for credible traffic microsimulation and transportation digital twins, yet high-definition maps are often difficult to obtain due to limited availability, high cost, or proprietary restrictions. Some build networks from crowdsourced data, such as OpenStreetMap, but these sources often contain geometric and semantic inconsistencies. Others create networks manually, a process that is labor-intensive and difficult to scale. To address these limitations, this work presents an end-to-end pipeline that automatically extracts georeferenced, lane-level road networks from publicly available high-resolution satellite imagery and converts them into simulation-ready assets. The developed end-to-end pipeline has three primary modules: (1) A computer-vision-based module first detects directed lane geometries and intersection layouts. (2) A heuristic-based topology construction module then identifies approach and exit legs and establishes conflict-free lane-to-lane connections. (3) Finally, an automatic simulation-building module converts the extracted network into standard formats, e.g., OpenDRIVE, and generates routable SUMO networks. The framework supports both complete network construction from scratch and local-scale refinement of existing networks through lane-count correction, transition recovery, and geometric regularization. The proposed pipeline provides a practical pathway to generate traffic simulation networks from satellite imagery, significantly reducing manual reconstruction effort and enabling scalable, continuously updated transportation digital twins.

Guo, Hetian [University of Georgia, Athens] (ORCID↗
DOE OSTI2026

APSO-enhanced algebraic derivative estimation approach for real-time traffic flow prediction on critical road sections during wildfire evacuation

In rapid-onset disaster scenarios such as wildfires, evacuation traffic often significantly deviates from historical patterns, rendering conventional data-driven forecasting methods less effective. To address this challenge, we propose an improved algebraic derivative estimation (ADE) incorporating particle swarm optimization (PSO) for real-time traffic flow prediction. Our approach dynamically adjusts the ADE prediction time window at each step by minimizing a cost function based on the mean and variance of accumulated forecasting errors within the window, thereby balancing bias and variability. We evaluate the method using traffic data from the January 2025 California wildfires, focusing on key road segments critical for large-scale evacuations. The results demonstrate that our approach surpasses established machine learning and deep learning models—XGBoost, LSTM, and GRU—in predictive accuracy and maintains high computational efficiency. Notably, the proposed method eliminates the need for offline model training. Moreover, rapid PSO-based tuning enables real-time deployment, which provides a crucial advantage in scenarios where evacuation timings and road closures change dynamically. In conclusion, these findings highlight the benefits of the PSO-enhanced ADE framework for emergency traffic management, where rapid, data-sparse forecasts are essential for effective evacuation planning.

Algebraic derivative estimation↗
DOE OSTI2024

A Vision–based Robust $\mathcal{H}$ ∞ Gain Scheduling Longitudinal and Lateral Following Controller for Autonomous Vehicles on Urban Curved Roads

Implementing advanced driver assistance systems (ADAS) in congested and intricate urban traffic scenarios poses significant challenges. To address the frequent stop–and–go motions exhibited by autonomous vehicles (AVs) navigating urban roads with changes in curvature, we propose a vision–based robust $\mathcal{H}$ ∞ adaptive cruise control system (ACC) for longitudinal control, plus a lane keeping assist system (LKAS) for lateral control. For the vision-based ACC, a weighted probability objective function for the vehicle following behavior is formulated. We incorporate $\mathcal{H}$ ∞ performance and gain scheduling techniques to mitigate the impact of uncertainty in visual sensor measurements. Furthermore, the optimal time headway is scheduled based on the velocity to ensure traffic flow efficiency and safety during the vehicle following process. For the LKAS, we introduce a road curvature estimation method that integrates lane and vehicle dynamics information to obtain the lateral and heading offsets. Next, the design criterion of the observer–based robust gain scheduling lateral motion controller is established by linear matrix inequality (LMI). Here, a series of experiments conducted within a camera–in–loop platform validate the proposed method.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

EVI-RoadTrip™: Electric Vehicle Infrastructure for Road Trips [SWR-22-17]

The EVI-RoadTrip™ tool offers high-resolution refueling network design and analysis to inform electric vehicle (EV) charging infrastructure development for road trips or long-distance travels. EVI-RoadTrip helps infrastructure planners, analysts, and decision makers evaluate EV energy consumption and corresponding charging demands along the routes-between origin and destination. It considers the projected location and characteristics of charging stations, potential electric grid impacts, and required infrastructure improvements. Strategically located charging stations for long-distance travel are critical to enabling the widespread adoption of EVs by allowing them to travel further beyond city or town boundaries. Sophisticated analysis and planning can identify the points (e.g., corridors) that may require increased availability of EV charging stations to support electrified road trips.

Wood, Eric↗
DOE OSTI2020

Modeling the External Effects of Air Taxis in Reducing the Energy Consumption of Road Traffic

Air taxis are currently being demonstrated. Few studies have quantified their external effects in reducing on-road vehicle fuel consumption. The hypothesis of this paper is that air taxis may divert some drivers away from congested traffic corridors, improve traffic speed and fuel economy, and reduce congestion-induced energy consumption. A model is developed that links several key components: mode choice, the relationship between travel demand and traffic speeds, the relationship between traffic speeds and fuel economies, and the heterogenous value of travel time. It is applied to the route from downtown Los Angeles to Los Angeles International Airport, where at peak hours 38,200 vehicles attempt to use the route that has an hourly capacity of 17,200 vehicles. The model estimates that, with conservative assumptions and near-term technologies, diverting 3.2% of the traffic to air taxis could produce a 15% reduction in traffic vehicle fuel use. With optimistic assumptions and mature technologies, the study estimates that diverting 20% of traffic could reduce the traffic vehicle fuel use by about 74%. The key insight is that if a small share of congested travelers switched to air taxis, motivated by private benefits of time savings, significant external benefits for other road travelers (time savings and fuel savings) and to society (reduced energy use and emissions), would ensue creating a win-win-win outcome. Overall, these estimates (which are not intended as predictions because of the stated limitations) strongly suggest the need to consider the external energy effect in future cost-benefit analyses of air taxi technologies.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Soil Temperature and Moisture within the Kougarok Fire Complex, Kougarok Road Mile Marker 86, Seward Peninsula, Alaska, 2019-2023

Daily averages of soil temperature and moisture measured once every hour at different heights located at Intensive Monitoring Stations within the Kougarok Fire Complex, Kougarok Road Mile Marker 86 site. Data were retrieved annually from 2019-2023. Package contains 21 *.CSV data files plus a file level metadata *.CSV, data dictionary *.CSV, data file inventory *.CSV, and sensor location site map *.JPG. Data files have header rows, NaN fields indicate invalid or missing data, and negative vertical offsets are above ground.The Kougarok tundra fire complex (KFC) is located north of Nome and the Kigluaik Mountains, near Quartz Creek and the Kougarok River. The site is accessed by foot from the end of the Nome-Taylor Highway (mile marker 86; also called the Kougarok or Beam Road). The KFC burned in six major fires in the decades since 1950 (Alaska Interagency Coordination Center, unpublished data). Lightning ignited five of these fires (1971, 1997, 2015, and 2019) and one was human caused (2002). The mosaic of overlapping fire scars allows for the study of repeat fires in the tundra which, until recently, was not a common phenomenon outside the boreal forest in Alaska. Our reference unburned tundra fire site is south of the KFC located at mile marker 80 of the Nome-Taylor Highway.The two most recent fires are the Mingvk Lake (2015; 21,698 acres burned from 7/27/2015 to 9/28/2015) and Garfield Creek (2019; 422 acres burned from 7/31/2019 to 8/20/19). The Mingvk Lake fire scar includes areas that burned 1-4x (1971, 1997, 2002), while the entirety of the Garfield Creek fire scar has burned 2x previously (1971, 2002).Previous research at the KFC focused on permafrost (Liljedahl et al. 2007; Narita et al. 2015; Iwahana et al. 2016; Tsuyuzaki, Iwahana, and Saito 2017) and vegetation (Narita et al. 2015; Hollingsworth et al. 2021) response to fire. The central Seward Peninsula is characterized by continuous permafrost with a thickness of 15 to 30 m and a mean active layer thickness of 56 cm (Hinzman et al. 2003). Sloping hills with mixed shrub–tussock tundra and tussock tundra vegetation in the uplands are characteristic of the region. Three micrometeorological towers near the Kougarok field site recorded a mean annual temperature of −2.4°C, mean January temperature of −23.1°C, mean July temperature of +11°C, and mean summer rainfall (June–August) of 94 mm from 2000 to 2006 (Liljedahl et al. 2007).The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

AmeriFlux US-BRG Bayles Road Grassland Tower

This is the AmeriFlux version of the carbon flux data for the site US-BRG Bayles Road Grassland Tower. Site Description - The Bayles Road grassland tower is situated in an experimental field incorporated within the Indiana University Research and Teaching Preserve. The field was historically covered by bottomland hardwood forest and later maintained for plant genetics studies. Intermixed species of grasses, sedges, and forbs are currently maintained with occasional mowing.

Novick, Kimberly↗
DOE OSTI2021

Off-Road Vehicle Energy-Saving Potential

The U.S. Department of Energy’s (DOE’s) Vehicle Technology Office (VTO) has played a critical role in enabling electrification and reducing fuel consumption in the automotive sector. However, the off-road vehicle sector accounts for 8% of transportation fuel, and that share is likely to increase over time as onroad vehicles move towards electrification. DOE can again play a key role in the off-road vehicle market by providing tools that can be used by academia and the industry to evaluate the impact of advanced technologies. The need for a pre-competitive simulation tool was also identified during a 2019 DOE-led workshop at Argonne National Laboratory that included OEMs and suppliers to this market. Autonomie, a powerful and robust system simulation tool for vehicle energy consumption and performance analysis, was developed by Argonne National Laboratory in collaboration with General Motors. Its application covers energy consumption and performance analysis throughout the entire vehicle development process by leveraging its plug-and-play powertrain and vehicle model architecture and development environment

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Individual Electro-Hydraulic Drives for Off-Road Vehicles (Final Report)

This document constitutes the final report of the project titled “Individual Electro-Hydraulic Drives for Off-Road Vehicles” (DOE award # DE-EE0008334). The project started May 1st 2018 and ended May 31st 2022. There were three budget periods (BPs) that, considering no-cost extension made throughout the project, had following periods: BP1 – Preliminary design: 05/01/2018 – 07/31/2019; BP2 – Initial implementation: 08/01/2019 – 01/31/2021; BP3 – Technology demonstration: 02/01/2021 – 05/31/2022. The main objective of the project was to develop and demonstrate an electro-hydraulic technology that, with respect to current state of the art solutions for off-road vehicles, can: 1. Lower power consumption of the fluid power system up to 70%; 2. Reduce noise emissions and vibration; 3. Allow for zero emission operation of the vehicle (engine off operation); 4. Enable “smart actuators” operating as modern “plug & play” elements with integrated control and self-diagnostic functions.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

Laboratory Accelerated Cyclic Corrosion Testing and On-Road Corrosion Testing of AA6××× Coupled to Carbon Fiber-Reinforced Plastics

Structures made from a combination of aluminum alloy (AA) and carbon fiber-reinforced plastic (CFRP) are susceptible to galvanic corrosion of the AA in harsh atmospheric conditions, such as might exist for closure panels in automotive applications. It is important to understand the galvanic corrosion behavior of these materials under laboratory conditions as that might allow prediction of performance in real environments. This work tested specially designed AA6×××-CFRP coupons, including AA6111 and AA6022, connected to CFRP made from two different carbon fiber fabrics (twill and random) with the aim of understanding the corrosion behaviors in a laboratory cyclic exposure chamber and during on-road exposure. The extent of corrosion was assessed by galvanic current measurements, optical profilometry, cross-sectional area analysis, and microscopic analysis. Based on the results, it was determined that the corrosion susceptibilities and morphologies observed in CFRP/AA couples tested in an environmental chamber for 12 weeks were in correspondence with those of the coupons subjected to on-road testing for 1 y in Columbus, OH.

Materials Science↗
NASA NTRS1972

Real-time Optical Alignment and Diagnostic System (ROADS)

The ultimate and most frequent usage of ROADS will be the alignment of subassemblies (collector and collimator) prior to their installation in a chamber. The system as designed has inherent associated capabilities well applied to acceptance testing of the No. 4 mirror, prediction of in-chamber performance, generation of a catalog of test results and other data, providing data for the plotting of isointensity lines, and other applications which are discussed. The ROADS system will collect, process, display, analyze, and retain data as required for components, partial subassemblies, complete subassemblies, complete modules, and multimodular arrays.

Source record↗
NASA NTRS1975

Comparison of human driver dynamics in simulators with complex and simple visual displays and in an automobile on the road

As part of a comprehensive program exploring driver/vehicle system response in lateral steering tasks, driver/vehicle system describing functions and other dynamic data have been gathered in several milieu. These include a simple fixed base simulator with an elementary roadway delineation only display; a fixed base statically operating automobile with a terrain model based, wide angle projection system display; and a full scale moving base automobile operating on the road. Dynamic data with the two fixed base simulators compared favorably, implying that the impoverished visual scene, lack of engine noise, and simplified steering wheel feel characteristics in the simple simulator did not induce significant driver dynamic behavior variations. The fixed base vs. moving base comparisons showed substantially greater crossover frequencies and phase margins on the road course.

Mcruer, D. T.↗
NASA NTRS1979

Laboratory study of annoyance to combined airplane and road-traffic noise

The annoyance of noise, which consisted of both separate and combined airplane and road-traffic noises, was studied. The subjects judged each session as to how annoyed they were in the simulated living room laboratory environment and as to how annoyed they were if they heard the noise in their home during day, evening, and night periods. The airplane noises, for equal session levels were judged significantly more annoying than the road traffic noises for the separate sessions. For the combined sessions, an interaction was found between the airplane noise and traffic noise levels, which was not adequately assessed by the total energy concept. Significant differences were found between the projected home responses for the day, evening, and night periods.

Powell, C. A.↗
NASA NTRS1978

User experience with on-road electric vehicles in the U.S.A. and Canada

Approximately 3000 on-road electric passenger cars and delivery vans are now in use in the U.S.A. and Canada. The owners and operators of almost one-third of these vehicles have been surveyed directly in an attempt to determine the suitability of commercially sold electric vehicles for real on-road jobs. This paper is primarily concerned with the analysis of the engineering aspects of the user experience with electric vehicles, i.e., mileage and application, failure modes and rates, energy economy, maintenance requirements, life cycle costs, and vehicle performance characteristics. It is concluded that existing electric vehicles can perform satisfactorily in applications that have limited performance requirements, particularly in terms of range.

Sandberg, J. J.↗
NASA NTRS1983

Comparison of road load simulator test results with track tests on electric vehicle propulsion system

A special-purpose dynamometer, the road load simulator (RLS), is being used at NASA's Lewis Research Center to test and evaluate electric vehicle propulsion systems developed under DOE's Electric and Hybrid Vehicle Program. To improve correlation between system tests on the RLS and track tests, similar tests were conducted on the same propulsion system on the RLS and on a test track. These tests are compared in this report. Battery current to maintain a constant vehicle speed with a fixed throttle was used for the comparison. Scatter in the data was greater in the track test results. This is attributable to variations in tire rolling resistance and wind effects in the track data. It also appeared that the RLS road load, determined by coastdown tests on the track, was lower than that of the vehicle on the track. These differences may be due to differences in tire temperature.

Dustin, M. O.↗