Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “vehicle data”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Data Quality Assessment of Optiwatt Vehicle Telematics Data

In October 2024, the Idaho National Laboratory (INL) received data from Optiwatt (Compass Global, Inc.) describing the driving and charging behavior of electric vehicle (EV) drivers. The data shared had been collected from approximately 10,000 vehicles and included vehicle specifications, driving information like odometer readings at the beginning and end of origin-destination pairs (i.e., trips with identification of home for trip start and end for Tesla vehicles), and charging information such as charging energy consumed per charge session and if the charge occurred at home. The vehicle data were provided from 9 EV makes and 18 EV models, with production years ranging from 2012–2024, but more than 9,500 of the vehicles were Tesla EVs. The data includes more than six million trips and more than three million charging events that occurred between June 2023 to Aug 2024 and collected from California and the Eastern United States. The purpose of this report is to review the quality of the data received from Optiwatt and the feedback INL received from Optiwatt after data concerns were shared with them.

33 - ADVANCED PROPULSION SYSTEMS↗
NASA NTRS1978

State-of-the-art assessment of electric and hybrid vehicles

Data are presented that were obtained from the electric and hybrid vehicles tested, information collected from users of electric vehicles, and data and information on electric and hybrid vehicles obtained on a worldwide basis from manufacturers and available literature. The data given include: (1) information and data base (electric and hybrid vehicle systems descriptions, sources of vehicle data and information, and sources of component data); (2) electric vehicles (theoretical background, electric vehicle track tests, user experience, literature data, and summary of electric vehicle status); (3) electric vehicle components (tires, differentials, transmissions, traction motors, controllers, batteries, battery chargers, and component summary); and (4) hybrid vehicles (types of hybrid vehicles, operating modes, hybrid vehicles components, and hybrid vehicles performance characteristics).

Source record↗
NASA NTRS1986

Mission and space vehicle sizing data for a chemical propulsion/aerobraking option

This paper presents sizing data for various combinations of Mars missions and chemical-propulsion/aerobraking vehicles. Data is compared for vehicles utilizing opposition (2-year mission) and conjunction (3-year mission) trajectories for 1999 and 2001 opportunities, for various sizes of vehicles. Payload capabilities for manned and unmanned missions vehicles and for propulsive-braking and aerobraking cases are shown. The effect of scaling up a reference vehicle Is compared to the case of utilizing two identical vehicles, for growth In payload capability. The rate of cumulative build up of weight on the surface of Mars is examined for various mission/vehicle combinations, and is compared to the landed-weight requirements for sortie missions, moving-base missions, and fixed-base missions. Also, the required buildup of weight in low Earth orbit (LEO) for various mission/vehicle combinations Is presented and discussed.

John Butler↗
NASA NTRS1988

A manned Mars artificial gravity vehicle

Data are presented on an artificial-gravity vehicle that is being designed for a manned Mars mission, using a 'split-mission' concept, in which an unmanned cargo vehicle is sent earlier and stored in a Mars orbit for a rendezvous with a manned vehicle about 1.5 years later. Special attention is given to the vehicle trajectory and configuration, the tether design, and the vehicle weight and launch requirements. It is shown that an artificial-G vehicle for a manned Mars missions is feasible technically and programmatically. Using an artificial-G vehicle instead of a zero-G vehicle for the piloted portion of a split mission provides physiological and human-factor-related benefits, does not eliminate requirements for zero-G countermeasures research (since zero-G is an abort mode), and could possibly reduce some life science activities. Diagrams are included.

Schultz, David N.↗
DOE OSTI2024

FedFleet 2024: Federal Fleet Boot Camp - Federal Motor Vehicle Fleet Data Reporting [Slides]

This presentation is intended as a 15-minute overview of federal motor vehicle fleet data reporting using the Federal Automotive Statistical Tool, presented as part of a half-day pre-conference workshop led by GSA's Office of Government-wide Policy for federal fleet managers at FedFleet 2024. This presentation covers what FAST is, what types of information agencies report through FAST, and where fleet managers can turn for assistance with fleet data reporting. FAST is a web-based information system sponsored by GSA's Office of Government-wide Policy and DOE's Federal Energy Management Program to collect information about the US federal government's fleet of motor vehicles; FAST is developed, maintained, and supported by DOE's Idaho National Laboratory (INL).

99 GENERAL AND MISCELLANEOUS↗
NASA NTRS2014

Methods of Real Time Image Enhancement of Flash LIDAR Data and Navigating a Vehicle Using Flash LIDAR Data

A method for creating a digital elevation map ("DEM") from frames of flash LIDAR data includes generating a first distance R(sub i) from a first detector i to a first point on a surface S(sub i). After defining a map with a mesh THETA having cells k, a first array S(k), a second array M(k), and a third array D(k) are initialized. The first array corresponds to the surface, the second array corresponds to the elevation map, and the third array D(k) receives an output for the DEM. The surface is projected onto the mesh THETA, so that a second distance R(sub k) from a second point on the mesh THETA to the detector can be found. From this, a height may be calculated, which permits the generation of a digital elevation map. Also, using sequential frames of flash LIDAR data, vehicle control is possible using an offset between successive frames.

Vanek, Michael D.↗
NASA NTRS2018

The Evolution of Payload Data Capabilities on the Commercial Visiting Vehicles that Service the International Space Station

In 2008, NASA awarded the first contracts to U.S. commercial companies to deliver cargo and supplies to the International Space Station (ISS). These contracts, called the first phase of Commercial Resupply Services (CRS1), were awarded to Space Exploration Technologies (SpaceX) and Orbital Sciences. Under the CRS1 contracts, commercial visiting vehicles not only provide a couple tons of cargo to the ISS each mission, but they also provide the ability for payloads to be transferred to the ISS in an active, powered state. Prior to the start of the CRS1 program, most vehicles that serviced the ISS transported science experiments as passive cargo. Therefore, the CRS1 program through offering frequent flight opportunities with powered payload transport capability ushered in a new era in which NASA and payload developers could reimagine operational concepts for payloads during the transit phase to and from the ISS. To take advantage of this powered payload transport capability, NASA first added requirements under the CRS1 program for the commercial vehicles to provide telemetry monitoring services for pressurized payloads to give payload developers situational awareness during the transport phase. Since then, payload developer use-cases for visiting vehicle data services during free-flight have evolved with each new commercial visiting vehicle contract to cover a variety of payload monitoring and control abilities. Additional commercial contracts include the Commercial Crew Transportation Capability (CCtCap) contracts that were awarded to SpaceX and Boeing, and the second phase of Commercial Resupply Services (CRS2) contracts that were awarded to SpaceX, Orbital ATK (formerly Orbital Sciences), and Sierra Nevada Corporation. Commercial crew flights will commence in 2018, and the first flight under the CRS2 program is currently planned for 2019.

Wiggins, Lindsay M.↗
DOE OSTI2023

RX-ADS: Interpretable Anomaly Detection Using Adversarial ML for Electric Vehicle CAN Data

Recent year has brought considerable advancements in Electric Vehicles (EVs) and associated infrastructures/ communications. Intrusion Detection Systems (IDS) are widely deployed for anomaly detection in such critical infrastructures. This paper presents an Interpretable Anomaly Detection System (RX-ADS) for intrusion detection in CAN protocol communication in EVs. Contributions include: 1) window based feature extraction method; 2) deep Autoencoder based anomaly detection method; and 3) adversarial machine learning based explanation generation methodology. The presented approach was tested on two benchmark CAN datasets: OTIDS and Car Hacking. The anomaly detection performance of RX-ADS was compared against the state-of-the-art approaches on these datasets: HIDS and GIDS. The RX-ADS approach presented performance comparable to the HIDS approach (OTIDS dataset) and has outperformed HIDS and GIDS approaches (Car Hacking dataset). Further, the proposed approach was able to generate explanations for detected abnormal behaviors arising from various intrusions. Furthermore, these explanations were later validated by information used by domain experts to detect anomalies. Other advantages of RX-ADS include: 1) the method can be trained on unlabeled data; 2) explanations help experts in understanding anomalies and root course analysis, and also help with AI model debugging and diagnostics, ultimately improving user trust in AI systems.

42 ENGINEERING↗
NASA NTRS2015

Thermal Protection Test Bed Pathfinder Development Project

In order to increase thermal protection capabilities for future reentry vehicles, a method to obtain relevant test data is required. Although arc jet testing can be used to obtain some data on materials, the best method to obtain these data is to actually expose them to an atmospheric reentry. The overprediction of the Orion EFT-1 flight data is an example of how the ground test to flight traceability is not fully understood. The RED-Data small reentry capsule developed by Terminal Velocity Aerospace is critical to understanding this traceability. In order to begin to utilize this technology, ES3 needs to be ready to build and integrate heat shields onto the RED-Data vehicle. Using a heritage Shuttle tile material for the heat shield will both allow valuable insight into the environment that the RED-Data vehicle can provide and give ES3 the knowledge and capability to build and integrate future heat shields for this vehicle.

Snapp, Cooper↗
NASA NTRS1983

Launch vehicle aerodynamic data base development comparison with flight data

The aerodynamic development plan for the Space Shuttle integrated vehicle had three major objectives. The first objective was to support the evolution of the basic configuration by establishing aerodynamic impacts to various candidate configurations. The second objective was to provide continuing evaluation of the basic aerodynamic characteristics in order to bring about a mature data base. The third task was development of the element and component aerodynamic characteristics and distributed air loads data to support structural loads analyses. The complexity of the configurations rendered conventional analytic methods of little use and therefore required extensive wind tunnel testing of detailed complex models. However, the ground testing and analyses did not predict the aerodynamic characteristics that were extracted from the Space Shuttle flight test program. Future programs that involve the use of vehicles similar to the Space Shuttle should be concerned with the complex flow fields characteristics of these types of complex configurations.

Hamilton, J. T.↗
DOE OSTI2025

Electric Vehicle Charging Data Falsification Attacks Utilizing Behavioral Models

A charging station (CS) and its associated electric vehicle supply equipment (EVSE) and charging electric vehicle (EV) interactions are potential targets for data falsification attacks since CSs are typically unmanned public facilities that are connected to the internet and EVs incorporate the vulnerable CAN bus network, which are both susceptible to remote attacks. The research question being addressed is how is the EV owner and CS negatively affected by CAN bus EV battery current sensor and battery temperature sensor data falsification attacks. Negative effects include economic losses from reduced life span of the battery, battery thermal runaway and fire (and potential loss of surrounding structure), and reduced utilization of the CS due to delayed departure time (longer charging times).

25 ENERGY STORAGE↗
NASA NTRS2013

Aerodynamic Reconstruction Applied to Parachute Test Vehicle Flight Data Analysis

The aerodynamics, both static and dynamic, of a test vehicle are critical to determining the performance of the parachute cluster in a drop test and for conducting a successful test. The Capsule Parachute Assembly System (CPAS) project is conducting tests of NASA's Orion Multi-Purpose Crew Vehicle (MPCV) parachutes at the Army Yuma Proving Ground utilizing the Parachute Test Vehicle (PTV). The PTV shape is based on the MPCV, but the height has been reduced in order to fit within the C-17 aircraft for extraction. Therefore, the aerodynamics of the PTV are similar, but not the same as, the MPCV. A small series of wind tunnel tests and computational fluid dynamics cases were run to modify the MPCV aerodynamic database for the PTV, but aerodynamic reconstruction of the flights has proven an effective source for further improvements to the database. The acceleration and rotational rates measured during free flight, before parachute inflation but during deployment, were used to con rm vehicle static aerodynamics. A multibody simulation is utilized to reconstruct the parachute portions of the flight. Aerodynamic or parachute parameters are adjusted in the simulation until the prediction reasonably matches the flight trajectory. Knowledge of the static aerodynamics is critical in the CPAS project because the parachute riser load measurements are scaled based on forebody drag. PTV dynamic damping is critical because the vehicle has no reaction control system to maintain attitude - the vehicle dynamics must be understood and modeled correctly before flight. It will be shown here that aerodynamic reconstruction has successfully contributed to the CPAS project.

Cassady, Leonard D.↗
NASA NTRS1993

Preliminary analysis of the JAPE ground vehicle test data with an artificial neural network classifier

Remotely sensing and classifying military vehicles in a battlefield environment have been the source of much research over the past 20 years. The ability to know where threat vehicles are located is an obvious advantage to military personnel. In the past active methods of ground vehicle detection such as radar have been used, but with the advancement of technology to locate these active sensors, passive sensors are preferred. Passive sensors detect acoustic emissions, seismic movement, electromagnetic radiation, etc., produced by the target and use this information to describe it. Deriving the mathematical models to classify vehicles in this manner has been, and is, quite complex and not always reliable. However, with the resurgence of artificial neural network (ANN) research in the past few years, developing models for this work may be a thing of the past. Preliminary results from an ANN analysis to the tank signatures recorded at the Joint Acoustic Propagation Experiment (JAPE) at the US Army White Sands Missile Range, NM, in July 1991, are presented.

Larsen, Nathan F.↗
NASA NTRS2018

HYPERS Software Development

Providing software support for HYPERS and creating internal tools. NASA has a long and decorated history of spaceflight innovation and achievements. The next great endeavor is NASA’s Journey to Mars, which will be achieved with the Space Launch System (SLS) and Orion capsule. Developing and testing these systems is no easy feat. Commercial-off-the-shelf (COTS) tools do not always provide enough functionality for engineers to do their job efficiently, making internal custom-made tools is necessary to meet the expected launch date. The purpose of this internship was to provide software support to the Storable Propellants and Hydraulic Systems Branch, specifically the Hypergolics Software (HYPERS) team. This included developing tools to parse unique measurements from the vehicle into the format specified by the HYPERS team. Displays were also created per requirements. Another major component of this internship was to create an intuitive interactive offline graphing application. The current tool for plotting vehicle data does not have all the functionality and features that HYPERS would like. By inputting a vehicle data file, the application plots the data based on the time range and components the user would like to view. After the graph is generated, the user is able to zoom in, pan horizontally, add comments, hover over data points, and take a snapshot of the current state of the graph. These additional features will help engineers quickly investigate the relationship between vehicle components through data visualization.

Internal Tools↗
NASA NTRS2011

Generation of the Ares I-X Flight Test Vehicle Aerodynamic Data Book and Comparison To Flight

A 3.5-year effort to characterize the aerodynamic behavior of the Ares I-X Flight Test Vehicle (AIX FTV) is described in this paper. The AIX FTV was designed to be representative of the Ares I Crew Launch Vehicle (CLV). While there are several differences in the outer mold line from the current revision of the CLV, the overall length, mass distribution, and flight systems of the two vehicles are very similar. This paper briefly touches on each of the aerodynamic databases developed in the program, describing the methodology employed, experimental and computational contributions to the generation of the databases, and how well the databases and underlying computations compare to actual flight test results.

Bauer, Steven X.↗