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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 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
NASA NTRS1976

Missions to Titan /1983-2000/ - An analysis of orbiters and entry vehicles

Mission Analysis data is presented which forms a basis for planning future missions to Titan, the seventh moon of Saturn. Four Titan mission options are studied: orbiters, probes, penetrators and landers. The generated data supports these mission modes. A comprehensive launch and trajectory analysis of earth to Saturn opportunities from 1983 to 2000 is given. Direct ballistic and Delta VEGA trajectory modes are evaluated. Orbital insertion, orbital trim, entry vehicle deployment options are all studied in parametric detail.

Hendricks, T. C.↗
DOE OSTI2023

Assessing the National Off-Cycle Benefits of 2-Layer HVAC Technology Using Dynamometer Testing and a National Simulation Framework

Some CO2-reducing technologies have real-world benefits not captured by regulatory testing methods. This paper documents a two-layer heating, ventilation, and air-conditioning (HVAC) system that facilitates faster engine warmup through strategic increased air recirculation. The performance of this technology was assessed on a 2020 Hyundai Sonata. Empirical performance of the technology was obtained through dynamometer tests at Argonne National Laboratory. Performance of the vehicle across multiple cycles and cell ambient temperatures with the two-layer technology active and inactive indicated fuel consumption reduction in nearly all cases. A thermally sensitive powertrain model, the National Renewable Energy Laboratory's FASTSim Hot, was calibrated and validated against vehicle testing data. The developed model included the engine, cabin, and HVAC system controls. Validation of component thermal models and engine efficiency ensured accurate thermal dynamics, fuel consumption, and two-layer benefit. The real-world benefit of the two-layer technology was calculated by simulating the validated powertrain model across a representative test matrix comparing performance with and without the two-layer system. Simulation across the test matrix revealed a real-world representative benefit of 0.0835%. Analysis of test matrix results at the regional level revealed the most benefit in cold climates and rural regions. Mean results across cycle length sensitivity simulations revealed a larger real-world benefit of 0.0872%. These benefit values can be considered a more accurate assessment of real-world technology performance. Future work is planned to explore the requisite number of drive cycles to ensure the full technology benefit is captured.

2-layer↗
DOE OSTI2025

Understanding EV Charging Pain Points Through Deep Learning Analysis

Current and potential electric vehicle (EV) owners express concerns about the charging infrastructure, mentioning non-functional chargers, prolonged charging times, inconvenient charger locations, long wait times, and high costs as major barriers. Addressing these issues often requires analyzing actual vehicle charging data, which is typically proprietary and inconsistent due to diverse standards and protocols. To understand and improve the EV charging experience, customer reviews are typically used to identify common customer pain points (CPPs). However, there is not a comprehensive method to map customer reviews to a standardized set of CPPs. In collaboration with the National Charging Experience (ChargeX) Consortium, this study bridges these gaps by proposing a Systematic Categorization and Analysis of Large-scale EV-charging Reviews (SCALER) framework. SCALER is an integrated, deep learning framework that segments, actively labels, analyzes, and classifies EV charging customer reviews into six CPP categories. To test its effectiveness, we used SCALER to analyze over 72,000 reviews from customers charging various EV models on different networks across the United States. SCALER achieves a classification accuracy of 92.5%, with an F1 score exceeding 85.7%. By demonstrating real-world applications of SCALER, we enhance the industry’s ability to understand and address CPPs to improve the EV charging experience.

29 - ENERGY PLANNING, POLICY AND ECONOMY↗
DOE OSTI2021

Identifying Light-Duty Vehicle Travel from Large-Scale Multimodal Wearable GPS Data with Novelty Detection Algorithms

Identifying travel mode within travel survey data sets, especially light-duty vehicle (LDV) travel, is foundational, though nontrivial, to travel behavior analysis and fuel consumption estimation. Current travel mode detection approaches require well-sampled and balanced data sets with ground truth travel mode labels. They are rarely applied and validated on large-scale, real-world data sets, which may not satisfy the data requirements. This paper proposes an LDV travel mode detection model as a supplement to current travel mode detection methods, for the case when the training set is highly (and/or completely) unbalanced, to the extent that classical machine-learning approaches become difficult or impossible to deploy. The proposed model uses a novelty detection technique-one-class support vector machines (OCSVMs)-and a novel exhaustive feature extraction (EFE) technique on continuous time series data (i.e., Global Positioning System [GPS] speed profiles) for single-mode trip trajectories. Training and validation of the model are conducted on a large-scale, real-world data set. The proposed method accurately identifies LDV trips from a broad set of multimodal trips by leveraging a wealth of preexisting in-vehicle GPS travel data. Additional sensitivity analysis sheds light on the optimal training size, which will benefit applications limited by highly imbalanced data. The paper also discusses performance comparison with regular machine-learning approaches, the model's robustness, and the potential to extend the proposed model to multimodal prediction.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Intelligent driving passive pedal control

A method for assignment of vehicle control includes receiving route data indicating a route between a starting location of a vehicle and a destination location, and determining an optimal vehicle configuration for the route based on a target vehicle speed and a hybrid torque split. The method further includes receiving a driver requested torque value and determining a passive pedal torque value based on the route data and vehicle powertrain data. The method further includes selectively assigning control of the vehicle to a vehicle system or to a driver of the vehicle based on the driver requested torque value and the passive pedal torque value.

Aggoune, Karim↗
DOE OSTI2024

A Stochastic Framework for Estimating Load Profiles at EV Fast Charging Stations

This paper formulates a methodology for estimating the average daily load profiles of EV fast charging stations over a planning horizon of five to ten years. The developed methodology uses historic vehicle registration data, state-level EV adoption targets, seasonal driving patterns, local demographics, competition, and traffic volume information to predict average station usage. Through Monte Carlo simulations, an average daily load profile is obtained for each month in the planning horizon, and prediction uncertainty is quantified. The proposed framework will facilitate the accurate estimation of energy and demand costs incurred by the charging station over the planning period, thereby informing return-on-investment calculations.

Biswas, Shuchismita↗
DOE OSTI2021

Python Library For Vehicular Emission Estimation

PyEmission is a Python library for estimation of vehicular emissions and fuel consumption. This tool covers a wide range of light duty motor vehicles including passenger car, SUV, passenger truck, and light commercial truck. The tool only takes second-by-second driving cycle and vehicle characteristics data as inputs and generate results of vehicular emissions (CO2, CO, NOx, and HC) and fuel consumption.

Rahman, MamunurMD↗
DOE OSTI2026

IPC-Fusion (Infrastructure Perception and Control (IPC): Multisensor Data Fusion Software) [SWR-25-153]

As part of the National Laboratory of the Rockies' (NLR’s) Infrastructure Perception and Control Laboratory, the IPC-Fusion toolkit provides a probabilistic, scalable, multi-sensor fusion framework that integrates (late-stage fusion) heterogeneous object detection data from traffic sensors to enable robust, real-time tracking of roadway occupants. The algorithmic design of the toolkit is motivated by the need for creating a digital twin of traffic at the edge in a scalable and affordable manner. The software operates by combining object-level measurements (such as position and velocity) from a suite of sensors (such as radar, lidar, camera) using Kalman filtering and probabilistic data association techniques to overcome individual sensor limitations and achieve superior tracking performance in complex traffic zones. The framework addresses key challenges including heterogeneous measurement uncertainties, asynchronous data streams, varying spatiotemporal data resolutions, robust data association, and adaptive object lifecycle management. Validated on real-world traffic intersection data including vehicles and pedestrians, IPC-Fusion demonstrates enhanced tracking reliability across scenarios involving occlusions, sensor failures, and varying traffic densities, supporting the broader IPC initiative's goal of transforming transportation infrastructure through advanced perception capabilities for intelligent transportation systems, traffic safety applications, and autonomous vehicle support.

Sandhu, Rimple [National Laboratory of the Rockies↗
DOE OSTI2020

INTERFUEL: EPAct 2005 Section 701 Waiver and Compliance Process [Slides]

This presentation presents an overview of the coming changes to how federal agencies with motor vehicles and which are subject to requirements for alternative fuel use under Energy Policy Act of 2005 Section 701 will request waivers, if needed, from that requirement. The presentations provides an overview of the requirement, how those waivers have been requested in recent history, why the process is changing, and the implications of those changes for relevant federal agencies. The presentation is intended for delivery via WebEx at the June 10, 2020 meeting of the DOE-sponsored INTERFUEL working group.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2026

NLR Core Modeling & Decision Support Capabilities: FASTSim, RouteE, T3CO & OpenPATH

This project is part of the program area to develop and improve core capabilities for the Energy-Efficient Mobility Systems (EEMS) program that enable research, development and deployment of advanced mobility solutions and enhance the EEMS Program's ability to address system-level transportation challenges. Advancements to the Future Automotive Systems Technology Simulator (FASTSim), Route Energy Prediction Model (RouteE), Transportation Technology Total Cost of Ownership (T3CO) and Open Platform for Agile Trip Heuristics (OpenPATH) core capabilities under this project supports the overall EEMS Program goals to effectively evaluate energy and mobility impacts of future transportation technologies and services, and to identify the most promising pathways to reduce transportation costs and environmental harms, and to improve mobility access. This presentation was prepared for the 2026 Annual Merit Review of this project.

33 ADVANCED PROPULSION SYSTEMS↗
NASA NTRS1966

Postflight Evaluation of Atlas-Centaur AC-6 (Launched August 11, 1965)

The sixth Atlas Centaur vehicle (AC-6) was successfully launched from the Eastern T e s t Range, Complex 36B, on August 11, 1965, at 0931:04.430 EST. A 2084-pound dynamic model of the Surveyor payload was placed in a simulated lunar transfer trajectory. Vehicle systems operated satisfactorily and all the flight objectives were accomplished. Lift-off within 4 seconds of the window opening demonstrated the launch-on-time capability of the vehicle were accurately compensated for by the Centaur guidance system. the Surveyor model into a near-perfect lunar transfer trajectory would have resulted in an impact of the moon without a midcourse correction. To hit the precise target area on the lunar surface, the required correction would have been 4.25 meters per second, which is well within the spacecraft capability. Normal thrust and impulse levels were obtained with both the A t l a s and Centaur propulsion systems. However, a sizeable thrust overshoot on startup of the Centaur engines has not been resolved. A propellant-utilization system used for the first time on the Centaur, accurately controlled the fuel and oxidant consumption. The turnaround and retrothrust maneuver were performed without incident. Relatively high longitudinal modal excitations and lateral payload excitations were obtained at lift-off; these high perturbations are believed t o be related t o the launcher holddown arms. Nominal temperatures were recorded for both the external vehicle skin and the payload compartment; however, abnormally low temperatures were measured in the forward equipment area, which may have resulted from leakage of cold helium purge gas. All vehicle electrical systems performed satisfactorily; the only difficulty with the RF systems was obtained with the C-band transponder. of the vehicle instrumentation yielded valid data. The AC-6 vehicle was constructed with several new lightweight designs including the forward bulkhead, thrust barrel, interstage adapter and tank skin thickness reduction from 0.016 t o 0.014 inch. No deficiencies were observed in any of these new structural elements.

Source record↗
NASA NTRS1976

Baseline test data for the EVA electric vehicle

Two electric vehicles from Electric Vehicle Associates were evaluated for ERDA at the Transportation Research Center of Ohio. The vehicles, loaded to a gross vehicle weight of 3750 pounds, had a range of 56.3 miles at a steady speed of 25 mph and a 27.4 miles range during acceleration-deceleration tests to a top speed of 30 mph. Energy consumption varied from 0.48 kw-hr/mi. to 0.59 kw-hr/mi.

Harhay, W. C.↗
NASA NTRS1978

Characterization of the non axial thrust generated by large solid propellant rocket motors in three axis stabilized ascent

Nonaxial thrusts produced by solid rocket motors during three-axis stabilized attitude control have been determined from ascent experience on twenty three Burner II, Burner IIA and Block 5D-1 upper stage vehicles. A data base representing four different rocket motor designs (three spherical and one extended spherical) totaling twenty five three-axis stabilized firings is generated. Solid rocket motor time-varying resultant and lateral side force vector magnitudes, directions and total impulses, and roll torque couple magnitudes, directions, and total impulses are tabulated in the appendix. Population means and three sigma deviations are plotted. Existing applicable ground test side force and roll torque magnitudes and total impulses are evaluated and compared to the above experience data base. Within the spherical motor population, the selected AEDC ground test data consistently underestimated experienced motor side forces, roll torques and total impulses. Within the extended spherical motor population, the selected AEDC test data predicted experienced motor side forces, roll torques, and total impulses, with surprising accuracy considering the very small size of the test and experience populations.

Kosmann, W. J.↗
NASA NTRS1980

Mated vertical ground vibration test

The Mated Vertical Ground Vibration Test (MVGVT) was considered to provide an experimental base in the form of structural dynamic characteristics for the shuttle vehicle. This data base was used in developing high confidence analytical models for the prediction and design of loads, pogo controls, and flutter criteria under various payloads and operational missions. The MVGVT boost and launch program evolution, test configurations, and their suspensions are described. Test results are compared with predicted analytical results.

Ivey, E. W.↗