Search NASA⌕ Search

SEARCH · Search NASA

Results for “Motor Research”

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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Heavy-Duty Vehicle Activity Updates for MOVES Using NREL Fleet DNA and CE-CERT Data

The U.S. Environmental Protection Agency's (EPA's) Motor Vehicle Emission Simulator (MOVES) is a publicly available tool used by researchers and policymakers to help understand motor vehicle emission sources at a national, county, and project level. Estimates of heavy-duty activity in the most recent version of the model at the time this work was conducted, MOVES2014, was identified as an area in need of improvement. The start activity in MOVES2014 is based on a limited and dated data set. In addition, MOVES2014 relies on drive cycles that represent on-network activity but do not account for idling activity that occurs on off-network roads, such as at a distribution center, while the truck is queuing or during loading and unloading. As a result, MOVES2014 may currently underestimate the number of starts and idle and soak time for heavy-duty trucks in real-world operation. The National Renewable Energy Laboratory (NREL) has previously leveraged its expansive Fleet DNA database of heavy-duty vehicles to idle and start activity for six of the nine heavy-duty vehicle source types of classes in the MOVES model. The data available in Fleet DNA from 416 conventional, diesel-powered vehicles provided activity estimates from more than 120,000 hours of operation throughout 14,682 vehicle days between October 2006 and January 2016. NREL calculated start fraction, starts per day, soak fraction, and idle fraction by hour of the day for each vehicle type, state, and vocation, and provided results in .CSV files that can be translated to MOVES table inputs. The idle and start activity from this initial analysis of Fleet DNA data was used to develop default idle and start data for heavy-duty vehicles in MOVES3. Satisfied with the results from the Fleet DNA data used for MOVES3, the EPA asked NREL to extend this start/soak/idle analysis using additional data from a larger number of vehicles for a potential future update to the MOVES model. Such a data set was achieved from a project led by the University of California at Riverside, College of Engineering, Center for Environmental Research & Technology (CE-CERT) and funded by California Air Resources Board. Specifically, this data set consists of 90 heavy-duty vehicles operated mainly in California, which can be separated into five of the nine heavy-duty vehicle classes in the MOVES model. In addition, the heavy-duty activity database collected by CE-CERT provided activity estimates from more than 44,000 hours of operation throughout 4,724 vehicle days between November 2014 and September 2016. This report details the analysis of the heavy-duty activity database collected from the University of California at Riverside by providing graphical analysis and context for the start, soak, and idle distributions. The comparison of the related results from both the Fleet DNA and CE-CERT data sets are documented as well.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2021

Fuel Property Effects on Knock Propensity and Thermal Efficiency in a Direct-Injection Spark-Ignition Engine

Engine knock remains one of the major barriers to further improvement in thermal efficiency of Direct-Injection Spark-Ignition (DISI) engines. While Research Octane Number and Motor Octane Number are often used as standard rating methods for knock resistance of fuels, the impacts of other fuel properties on knock propensity in modern engines such as heat of vaporization (HoV) and laminar flame speed (LFS) require better understanding in order to co-optimize fuels and engine designs to achieve higher thermal efficiency and lower CO2 emission. In the present study, computational fluid dynamics (CFD) is used to model a boosted DISI engine with a focus on knock prediction and fuel property effects. A level-set G-equation model is employed to capture turbulent premixed combustion, and is coupled with a transported Livengood-Wu (L-W) integral approach to predict autoignition in the unburnt region. A criterion associated with the L-W integral is developed to accurately predict knock onset and knock-limited spark-advance. This model is then applied to a sensitivity analysis of HoV and LFS on knock tendency and thermal efficiency. The pressure-temperature trajectory framework is applied and extended to study the fuel effects on auto-ignition process in the engine. An existing efficiency-based merit function, which is derived from experiments for boosted SI engines, is evaluated and improved based on the current CFD results.

DISI↗
DOE OSTI2021

End-gas autoignition fraction and flame propagation rate in laser-ignited primary reference fuel mixtures at elevated temperature and pressure

Knock in spark-ignited (SI) engines is initiated by autoignition of the unburned gasses upstream of spark-ignited, propagating, turbulent premixed flames. Knock propensity of fuel/air mixtures is typically quantified using research octane number (RON), motor octane number (MON), or methane number (MN; for gaseous fuels), which are measured using single-cylinder, variable compression ratio engines. In this study, knock propensity of SI fuels was quantified via observations of end-gas autoignition (EGAI) in unburned gasses upstream of laser-ignited, premixed flames at elevated pressures and temperatures in a rapid compression machine. Stoichiometric primary reference fuel (PRF; n-heptane/isooctane) blends of varying reactivity (50 ≤ PRF ≤ 100) were ignited using an Nd:YAG laser over a range of temperatures and pressures, all in excess of 545 K and 16.1 bar. Laser ignition produced outwardly-propagating premixed flames. High-speed pressure measurements and schlieren images indicated the presence of EGAI. The fraction of the total heat release attributed to EGAI (i.e., EGAI fraction) varied with fuel reactivity (i.e., octane number) and the time-integrated temperature of the end-gas prior to ignition. Flame propagation rates, which were measured using schlieren images, were only weakly correlated with octane number but were affected by turbulence caused by variation in piston timing. Under conditions of low turbulence, measured flame propagation rates approached one-dimensional premixed laminar flame speed computations performed at the same conditions. Experiments were simulated with a three-dimensional CONVERGE™ model using reduced chemical kinetics (121 species, 538 reactions). The simulations accurately captured the measured flame propagation rates, as well as the variation in EGAI fraction with fuel reactivity and time-integrated end-gas temperature. The simulations also revealed low-temperature heat release as well as formaldehyde and hydrogen peroxide formation in the end-gas upstream of the propagating flame, which increased the temperature and degree of chain branching in the end-gas, ultimately leading to EGAI.

42 ENGINEERING↗
DOE OSTI2023

Uncertainty quantification of a deep learning fuel property prediction model

Deep learning models are being widely used in the field of combustion. Given the black-box nature of typical neural network based models, uncertainty quantification (UQ) is critical to ensure the reliability of predictions as well as the training datasets, and for a principled quantification of noise and its various sources. Deep learning surrogate models for predicting properties of chemical compounds and mixtures have been recently shown to be promising for enabling data-driven fuel design and optimization, with the ultimate goal of improving efficiency and lowering emissions from combustion engines. In this study, UQ is performed for a multi-task deep learning model that simultaneously predicts the research octane number (RON), Motor Octane Number (MON), and Yield Sooting Index (YSI) of pure components and multicomponent blends. The deep learning model is comprised of three smaller networks: Extractor 1, Extractor 2, and Predictor, and a mixing operator. The molecular fingerprints of individual components are encoded via Extractor 1 and Extractor 2, the mixing operator generates fingerprints for mixtures/blends based on linear mixing operation, and the predictor maps the fingerprint to the target properties. Two different classes of UQ methods, Monte Carlo ensemble methods and Bayesian neural networks (BNNs), are employed for quantifying the epistemic uncertainty. Combinations of Bernoulli and Gaussian distributions with DropConnect and DropOut techniques are explored as ensemble methods. All the DropConnect, DropOut and Bayesian layers are applied to the predictor network. Aleatoric uncertainty is modeled by assuming that each data point has an independent uncertainty associated with it. The results of the UQ study are further analyzed to compare the performance of BNN and ensemble methods. Although this study is confined to UQ of fuel property prediction, the methodologies are applicable to other deep learning frameworks that are being widely used in the combustion community.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

A 100+ RON Gasoline Blendstock for High Efficiency, Low Emission Vehicles Engines - CRADA 493 (Final Report)

This study aimed at demonstrating production of a 100+RON gasoline fraction from a linear olefins feedstock to help improve further the viability and flexibility of the Pacific Northwest National Laboratory/ LanzaTech alcohol-to-jet (ATJ) patented process that converts ethanol from LanzaTech’s syngas fermentation process to low aromatic jet-range iso-paraffins. To achieve a high RON gasoline and ultimately a 100+RON, the technical approach consisted of converting the linear olefins into an iso-olefins rich mixture and then oligomerizing the iso-olefins rich mixture into high RON compounds in a single bed loaded with an acid catalyst that allows conversion at low reaction temperature. Three families of acid catalysts labeled as type A, B and C were investigated for the single-bed conversion of linear olefins into high RON gasoline range compounds. The effects of the nature of the catalyst, acid sites concentration and operating conditions were investigated. Fuel properties measurements and engine testing were conducted for the most promising catalyst. For type A catalysts, we demonstrated that the conversion increases with the increase of the Brönsted acid site concentration and that lower reaction temperature favors the formation of desired highly branched compounds. The highest dRON obtained with type A catalyst was equal to 94 (from NMR and IQT). Type B catalysts appear very effective for producing dimethyl-olefins compounds when operating at low reaction temperature (i.e., < 100°C). The highest dRON obtained with type B catalyst was equal to 92. The results suggest that type B catalysts are less favorable to internal conversion of linear olefins into iso-olefins compared to type A catalysts which leads to the formation of a gasoline blendstock with a lower dRON. A Type C catalyst that is less commonly used for production of gasoline range compounds from linear olefins was investigated due to its ability to favor conversion of linear olefins into iso-olefins. Compared to type A and type B catalyst, type C favors the formation of highly branched compounds (i.e., with 3+ methyl groups) in the gasoline range. Indeed, a gasoline blendstock containing about 33 wt.% of highly branched compounds was produced with type C catalyst while maintaining a high linear olefins conversion (i.e., 70%). A large quantity of this gasoline blendstock was produced and fuel properties measurements including engine testing for Research Octane Number (RON), Motor Octane Number (MON) and octane sensitivity (S) were conducted. A high RON = 97, MON = 82.7, S =14.3, AKI = 90 and HoV = 334.1kJ/kg were measured. While a RON of 100 was not achieved, the fuel properties of the gasoline blendstock are very acceptable as compared to current premium gasoline. Overall, these results highlight the potential for producing a high RON/ premium gasoline blendstock starting from a linear olefins feedstock.

02 PETROLEUM↗
DOE OSTI2020

Prediction of Research/Motor Octane Number and Octane Sensitivity Using Artificial Neural Networks

Octane sensitivity (OS), dfined as the research octane number (RON) minus the motor octane number (MON) of a given fuel, has gained interest among researchers due to its apparent ffect on knocking conditions in internal combustion engines. Compounds with a high OS enable higher efficiencies, especially with respect to advanced compression ignition engines. RON/MON must be experimentally tested to determine OS; however, the experimental methods utilized require a substantial amount of time, a significant monetary investment, and specialized equipment. To this end, predictive computational models trained with existing experimental data and molecular properties would allow for the preemptive screening of compounds prior to performing these experiments. The present work proposes two methods for predicting the OS of a given compound: using artficial neural networks (ANNs) trained with quantitative structure-property relationship (QSPR) descriptors to predict RON and MON individually to compute OS from RON/MON predictions (derived octane sensitivity, dOS), and using an ANN trained with QSPR descriptors to directly predict OS. ANNs trained to predict RON and MON achieved test set root-mean-square errors (RMSEs) of 10.499 and 7.551 respectively. dOS calculations were found to have a test set RMSE of 6.432 while predicting OS directly resulted in a test set RMSE of 7.019, showing it is more bene cial to obtain OS from RON/MON predictions than predicting it directly. Furthermore, relationships between individual QSPR descriptors and RON/MON/OS are discussed, highlighting correlations between specfic molecular features and these properties.

09 BIOMASS FUELS↗
DOE OSTI2024

Effect of Cyclo-Pentane Impurities on the Autoignition Reactivity and Properties of a Gasoline Surrogate Fuel

Surrogate fuels that reproduce the characteristics of full-boiling range fuels are key tools to enable numerical simulations of fuel-related processes and ensure reproducibility of experiments by eliminating batch-to-batch variability. Within the PACE initiative, a surrogate fuel for regular-grade E10 (10%vol ethanol) gasoline representative of a U.S. market gasoline, termed PACE-20, was developed and adopted as baseline fuel for the consortium. Although extensive testing demonstrated that PACE-20 replicates the properties and combustion behavior of the full-boiling range gasoline, several concerns arose regarding the purity level required for the species that compose PACE-20. This is particularly important for cyclo-pentane, since commercial-grade cyclo-pentane typically shows 60%–85% purity. Here, in the present work, the effects of the purity level of cyclo-pentane on the properties and combustion characteristics of PACE-20 were studied. Chemical kinetic simulations were performed to predict the effects of cyclo-pentane impurities on the properties, octane rating, and autoignition reactivity under homogeneous charge compression-ignition conditions of PACE-20. From the numerical results, cyclo-pentane with 85% purity or higher is required to reasonably match both the research octane number and motor octane number of the target gasoline. Finally, homogeneous charge compression-ignition engine simulations show that impurities have only a modest effect on reactivity at naturally aspirated conditions, but cyclo-pentane purity is critical to properly replicate the pressure dependency of the reactivity.

33 ADVANCED PROPULSION SYSTEMS↗
NASA NTRS1972

Research on combustion instability and application to solid propellant rocket motors. II.

Review of the current state of analyses of combustion instability in solid-propellant rocket motors, citing appropriate measurements and observations. The work discussed has become increasingly important, both for the interpretation of laboratory data and for predicting the transient behavior of disturbances in full-scale motors. Two central questions are considered - namely, linear stability and nonlinear behavior. Several classes of problems are discussed as special cases of a general approach to the analysis of combustion instability. Application to motors, and particularly the limitations presently understood, are stressed.

Culick, F. E. C.↗
NASA NTRS1975

Analysis and correction of ground reflection effects in measured narrowband sound spectra using cepstral techniques

Ground reflections generate undesirable effects on acoustic measurements such as those conducted outdoors for jet noise research, aircraft certification, and motor vehicle regulation. Cepstral techniques developed in speech processing are adapted to identify echo delay time and to correct for ground reflection effects. A sample result is presented using an actual narrowband sound pressure level spectrum. The technique can readily be adapted to existing fast Fourier transform type spectrum measurement instrumentation to provide field measurements/of echo time delays.

Miles, J. H.↗
NASA NTRS1975

Analysis and correction of ground reflection effects in measured narrowband sound spectra using cepstral techniques

Ground reflections generate undesirable effects on acoustic measurements such as those conducted outdoors for jet noise research, aircraft certification, and motor vehicle regulation. This paper shows how cepstral techniques developed in speech processing can be adapted to identify the echo delay time and to correct for ground reflection effects. A sample result is presented using an actual narrowband sound pressure level spectrum. The technique can readily be adapted to existing fast Fourier transform type spectrum measurement instrumentation to provide field measurement of echo time delays.

Miles, J. H.↗
NASA NTRS1977

Prosthetic EMG control enhancement through the application of man-machine principles

An area in medicine that appears suitable to man-machine principles is rehabilitation research, particularly when the motor aspects of the body are involved. If one considers the limb, whether functional or not, as the machine, the brain as the controller and the neuromuscular system as the man-machine interface, the human body is reduced to a man-machine system that can benefit from the principles behind such systems. The area of rehabilitation that this paper deals with is that of an arm amputee and his prosthetic device. Reducing this area to its man-machine basics, the problem becomes one of attaining natural multiaxis prosthetic control using Electromyographic activity (EMG) as the means of communication between man and prothesis. In order to use EMG as the communication channel it must be amplified and processed to yield a high information signal suitable for control. The most common processing scheme employed is termed Mean Value Processing. This technique for extracting the useful EMG signal consists of a differential to single ended conversion to the surface activity followed by a rectification and smoothing.

Simcox, W. A.↗
NASA NTRS2003

Flywheels Upgraded for Systems Research

With the advent of high-strength composite materials and microelectronics, flywheels are becoming attractive as a means of storing electrical energy. In addition to the high energy density that flywheels provide, other advantages over conventional electrochemical batteries include long life, high reliability, high efficiency, greater operational flexibility, and higher depths of discharge. High pulse energy is another capability that flywheels can provide. These attributes are favorable for satellites as well as terrestrial energy storage applications. In addition to energy storage for satellites, the several flywheels operating concurrently can provide attitude control, thus combine two functions into one system. This translates into significant weight savings. The NASA Glenn Research Center is involved in the development of this technology for space and terrestrial applications. Glenn is well suited for this research because of its world-class expertise in power electronics design, rotor dynamics, composite material research, magnetic bearings, and motor design and control. Several Glenn organizations are working together on this program. The Structural Mechanics and Dynamics Branch is providing magnetic bearing, controls, and mechanical engineering skills. It is working with the Electrical Systems Development Branch, which has expertise in motors and generators, controls, and avionics systems. Facility support is being provided by the Space Electronic Test Engineering Branch, and the program is being managed by the Space Flight Project Branch. NASA is funding an Aerospace Flywheel Technology Development Program to design, fabricate, and test the Attitude Control/Energy Storage Experiment (ACESE). Two flywheels will be integrated onto a single power bus and run simultaneously to demonstrate a combined energy storage and 1-degree-of-freedom momentum control system. An algorithm that independently regulates direct-current bus voltage and net torque output will be experimentally demonstrated.

Jansen, Ralph H.↗
NASA NTRS2008

A Cryogenic High-Power-Density Bearingless Motor for Future Electric Propulsion

The NASA Glenn Research Center (GRC) is developing a high-power-density switched-reluctance cryogenic motor for all-electric and pollution-free flight. However, cryogenic operation at higher rotational speeds markedly shortens the life of mechanical rolling element bearings. Thus, to demonstrate the practical feasibility of using this motor for future flights, a non-contact rotor-bearing system is a crucial technology to circumvent poor bearing life that ordinarily accompanies cryogenic operation. In this paper, a bearingless motor control technology for a 12-8 (12 poles in the stator and 8 poles in the rotor) switched-reluctance motor operating in liquid nitrogen (boiling point, 77 K (-196 C or -321 F)) was presented. We pushed previous disciplinary limits of electromagnetic controller technique by extending the state-of-the-art bearingless motor operating at liquid nitrogen for high-specific-power applications. The motor was levitated even in its nonlinear region of magnetic saturation, which is believed to be a world first for the motor type. Also we used only motoring coils to generate motoring torque and levitation force, which is an important feature for developing a high specific power motor.

Choi, Benjamin↗
NASA NTRS2012

Overheating Anomalies during Flight Test Due to the Base Bleeding

In this paper we present the results of the analytical and numerical studies of the plume interaction with the base flow in the presence of base out-gassing. The physics-based analysis and CFD modeling of the base heating for single solid rocket motor performed in this research addressed the following questions: what are the key factors making base flow so different from that in the Shuttle [1]; why CFD analysis of this problem reveals small plume recirculation; what major factors influence base temperature; and why overheating was initiated at a given time in the flight. To answer these questions topological analysis of the base flow was performed and Korst theory was used to estimate relative contributions of radiation, plume recirculation, and chemically reactive out-gassing to the base heating. It was shown that base bleeding and small base volume are the key factors contributing to the overheating, while plume recirculation is effectively suppressed by asymmetric configuration of the flow formed earlier in the flight. These findings are further verified using CFD simulations that include multi-species gas environment both in the plume and in the base. Solid particles in the exhaust plume (Al2O3) and char particles in the base bleeding were also included into the simulations and their relative contributions into the base temperature rise were estimated. The results of simulations are in good agreement with the temperature and pressure in the base measured during the test.

base bleeding↗
DOE OSTI2024

Next Generation High Efficiency Boosted Engine Concept

This report summarizes a collaborative research project between Ford Motor Company, FEV North America, and Oak Ridge National Laboratory to develop a next-generation, high-efficiency, boosted spark-ignited engine. The goal was to achieve a 23% improvement in fuel economy and a 15% reduction in engine weight compared to a 2016 Ford F150. The team utilized advanced technologies including a high compression ratio, cooled exhaust gas recirculation (EGR), early intake valve closing, and a novel active pre-chamber ignition system. The final engine prototype met the fuel economy goal and demonstrated a 4.3% weight reduction, with further opportunities identified to reach the full 15% target.

Fuel economy↗
NASA NTRS2003

All-Optical Micro Motors Based on Moving Gratings in Photosensitive Media

This research effort was a feasibility study of the concept of an all-optical micro motor with a rotor driven by a traveling wave. The wave was a result of a photo induced surface deformation of a photosensitive material produced by a traveling holographic grating. Two phases modulated coherent optical beams were used to generate the grating in two types of photosensitive materials. The materials that were studied were photorefractive crystals and thin polymer films. Theoretical studies were performed on lithium niobate giving predictions of deformations of the order of nanometers. The experimental deformation size was also on the order of nanometers. The deformations were deep enough to provide conditions for the implementation of the all-optical motor using lithium niobate. We also were able to align micron-size dielectric particles along the holographic gratings by means of the periodic electric forces generated by the grating. These forces can also move the particles along the surface if the grating is moving. We then turned our attention on thin films and obtained a deformation visible on the order of 100 microns. An experimental breadboard demonstration of a prototype was done in the summer of 2001 at Glenn Research Center (GRC). The demonstration included the movement of clocks mechanical workings by an optically driven motor based on a polymer film. The application of this technology can be adapted to government as well as industrial uses. One such project is to make a chemical sensor for the detection of hazardous chemicals. The thin polymer film is highly suited for this purpose since a marker dye could be easily placed on the film in order to detect chemical compounds. This system could be a self-regulating chemical monitoring system used on launches of the space shuttle or locations where hazardous chemicals are present. The project provided support for two black minority graduate students targeting MS and PhD degrees in Applied Optics.

Adamovsky, Gregory↗
NASA NTRS1971

Technology for low cost solid rocket boosters.

A review of low cost large solid rocket motors developed at the Lewis Research Center is given. An estimate is made of the total cost reduction obtainable by incorporating this new technology package into the rocket motor design. The propellant, case material, insulation, nozzle ablatives, and thrust vector control are discussed. The effect of the new technology on motor cost is calculated for a typical expandable 260-in. booster application. Included in the cost analysis is the influence of motor performance variations due to specific impulse and weight changes. It is found for this application that motor costs may be reduced by up to 30% and that the economic attractiveness of future large solid rocket motors will be improved when the new technology is implemented.

Ciepluch, C.↗