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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

A Method of Optimal Control for Class 8 Vehicle Platoons Over Hilly Terrain

This work develops and implements an NMPC control system to facilitate fuel-optimal platooning of Class 8 vehicles over challenging terrain. Prior research has shown that Cooperative Adaptive Cruise Control (CACC), which allows multiple Class 8 vehicles to follow in close succession, can save between 3 and 8% in overall fuel consumption on flat terrain. However, on more challenging terrain, e.g. rolling hills, platooning vehicles can experience diminished fuel savings, and, in some cases, an increase in fuel consumption relative to individual vehicle operation. This research explores the use of Nonlinear Model Predictive Control (NMPC) with predefined route grade profiles to allow platooning vehicles to generate an optimal velocity trajectory with respect to fuel consumption. In order to successfully implement the NMPC system, a model relating vehicle velocity to fuel consumption was generated and validated using experimental data. Additionally, the predefined route grade profiles were created by using the vehicle's GPS velocity over the desired terrain. The real-time NMPC system was then implemented on a two-truck platoon operating over challenging terrain, with a reference vehicle running individually. The results from NMPC platooning are compared against fuel results from a classical proportional-integral-derivative (PID) headway control method. Furthermore, this comparison yields the comparative fuel savings and energy efficiency benefit of NMPC system. In the final analysis, significant fuel savings of greater than 14 and 20% were seen for the lead and following vehicles relative to their respective traditional cruise control and platooning architectures.

33 ADVANCED PROPULSION SYSTEMS↗
NASA NTRS1981

The design and development of a mixer compound exhaust system for a quiet clean general aviation turbofan

Lower engine fuel consumption has become a dominant factor in turbofan engine design due to rapidly increasing fuel costs. One engine component with a large impact on engine performance is the exhaust system. Previous exhaust system studies have demonstrated the significant exhaust system efficiency gains available through mixing of the core and bypass flows. Typically, a large, costly rig and engine program are required to develop and optimize these gains. The purpose of this paper is to present the results of the low-cost design system used for the quiet, clean general aviation turbofan mixer nozzle design and development. The scale model and full-scale engine test results confirm the predicted 3 to 5% reduction in cruise fuel consumption. This unique design system, which is based on integrating advanced three-dimensional viscous numerical methods with empirical optimization techniques, is summarized and detailed comparisons with test data are presented. The ability to accurately predict relative performance of mixer systems with substantially reduced development time and cost savings is demonstrated.

Blackmore, W. L.↗
NASA NTRS1980

Engine component improvement: Performance improvement, JT9D-7 3.8 AR fan

A redesigned, fuel efficient fan for the JT9D-7 engine was tested. Tests were conducted to determine the effect of the 3.8 AR fan on performance, stability, operational characteristics, and noise of the JT9D-7 engine relative to the current 4.6 AR Bill-of-Material fan. The 3.8 AR fan provides increased fan efficiency due to a more advanced blade airfoil with increased chord, eliminating one part span shroud and reducing the number of fan blades and fan exit guide vanes. Engine testing at simulated cruise conditions demonstrated the predicted 1.3 percent improvement in specific fuel consumption with the redesigned 3.8 AR fan. Flight testing and sea level stand engine testing demonstrated exhaust gas temperature margins, fan and low pressure compressor stability, operational suitability, and noise levels comparable to the Bill-of-Material fan.

Gaffin, W. O.↗
NASA NTRS1982

Rotorcraft convertible engines for the 1980s

Two rotorcraft studies were executed. The goal was to identify attractive techniques for implementing convertible powerplants for the ABC, Folded Tilt Rotor, and X-wing type high speed, high-L/D rotorcraft; to determine the DOC and fuel savings benefits achieved thereby; and to define research required to bring these powerplants into existence by the 1990's. These studies are reviewed herein and the different methods of approach are pointed out as well as the key findings. Fan shaft engines using variable inlet guide vanes or torque converters, and turboprop powerplants appear attractive. Savings in DOC and fuel consumption of over 15 percent are predicted in some cases as a result of convertible engine use rather than using separate engines for the thrust and the shaft functions. Areas of required research are fan performance (including noise), integrated engine/rotorcraft control, torque converters, turbine design, airflow for rotorcraft torque control, bleed for lift flow, and transmissions and clutches.

Eisenberg, J. D.↗
NASA NTRS2017

Point-Mass Aircraft Trajectory Prediction Using a Hierarchical, Highly-Adaptable Software Design

A highly adaptable and extensible method for predicting four-dimensional trajectories of civil aircraft has been developed. This method, Behavior-Based Trajectory Prediction, is based on taxonomic concepts developed for the description and comparison of trajectory prediction software. A hierarchical approach to the "behavioral" layer of a point-mass model of aircraft flight, a clear separation between the "behavioral" and "mathematical" layers of the model, and an abstraction of the methods of integrating differential equations in the "mathematical" layer have been demonstrated to support aircraft models of different types (in particular, turbojet vs. turboprop aircraft) using performance models at different levels of detail and in different formats, and promise to be easily extensible to other aircraft types and sources of data. The resulting trajectories predict location, altitude, lateral and vertical speeds, and fuel consumption along the flight path of the subject aircraft accurately and quickly, accounting for local conditions of wind and outside air temperature. The Behavior-Based Trajectory Prediction concept was implemented in NASA's Traffic Aware Planner (TAP) flight-optimizing cockpit software application.

Karr, David A.↗
DOE OSTI2021

Future Cost Benefits Analysis for Electrified Vehicles from Advances Due to U.S. Department of Energy Targets

The U.S. Department of Energy’s Vehicle Technologies Office (DOE-VTO) supports research and development (R&D), as well as deployment of efficient and sustainable transportation technologies, that will improve energy efficiency and fuel economy and enable America to use less petroleum. To accelerate the creation and adoption of new technologies, DOE-VTO has developed specific targets for a wide range of powertrain technologies (e.g., engine, battery, electric machine, lightweighting, etc.). This paper quantifies the impact of VTO R&D on vehicle energy consumption and cost compared to expected historical improvements across vehicle classes, powertrains, component technologies and timeframes. We have implemented a large scale simulation process to develop and simulate tens of thousands of vehicles on U.S. standard driving cycles using Autonomie, a vehicle simulation tool developed by Argonne National Laboratory. Results demonstrate significant additional reductions in both cost and energy consumption due to the existence of VTO R&D targets compared to predicted historical trends. It is observed that, over time, the fuel consumption of different electrified vehicles is expected to decrease by 40–50% and a reduction of 45–55% for vehicle manufacturing costs owing to significant improvements through various VTO R&D targets.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Real-Time Ecodriving Control in Electrified Connected and Autonomous Vehicles Using Approximate Dynamic Programing

Connected and automated vehicles (CAVs), particularly those with a hybrid electric powertrain, have the potential to significantly improve vehicle energy savings in real-world driving conditions. In particular, the ecodriving problem seeks to design optimal speed and power usage profiles based on available information from connectivity and advanced mapping features to minimize the fuel consumption over an itinerary. This paper presents a hierarchical multilayer model predictive control (MPC) approach for improving the fuel economy of a 48 V mild-hybrid powertrain in a connected vehicle environment. Approximate dynamic programing (DP) is used to solve the receding horizon optimal control problem, whose terminal cost is approximated with the base policy obtained from the long-term optimization. The controller was tested virtually (with deterministic and Monte Carlo simulation) across multiple real-world routes, demonstrating energy savings of more than 20%. The controller was then deployed on a test vehicle equipped with a rapid prototyping embedded controller. In-vehicle testing confirm the energy savings obtained in simulation and demonstrate the real-time ability of the controller.

Automation & Control Systems↗
NASA NTRS1981

Effect of time-dependent flight loads on turbofan engine performance deterioration

An analytic evaluation of the dynamic effects of two flight load conditions of the JT9D-7/747 propulsion system is conducted. Predicted performance changes associated with a once-per-flight vertical gust and a typical revenue service landing are calculated. The predicted dynamic load effects on thrust specific fuel consumption are found to be negligible. The results indicate that the quasi-steady state approach to flight loads modeling is adequate to investigate the factors important to the deterioration process.

Lewis, B. L.↗
DOE OSTI2021

A Hybrid Heavy-Duty Diesel Power System for Off-Road Applications - Concept Definition

A multi-year Power System R&D project was initiated with the objective of developing an off-road hybrid heavy-duty concept diesel engine with front end accessory drive-integrated energy storage. This off-road hybrid engine system is expected to deliver 15-20% reduction in fuel consumption over current Tier 4 Final-based diesel engines and consists of a downsized heavy-duty diesel engine containing advanced combustion technologies, capable of elevated peak cylinder pressures and thermal efficiencies, exhaust waste heat recovery via SuperTurbo™ turbocompounding, and hybrid energy recovery through both mechanical (high speed flywheel) and electrical systems. The first year of this project focused on the definition of the hybrid elements using extensive dynamic system simulation over transient work cycles, with hybrid supervisory controls development focusing on energy recovery and transient load assist, in Caterpillar’s DYNASTY™ software environment. Three key off-road applications were the focus of the hybrid concept definition with an aim of understanding the system’s modular capability for the diverse off-road heavy-duty market. Core engine performance 1D and 3D simulations isolated the efficiency contributions from the downsized engine, turbocompounding, and in-cylinder thermal barrier coatings. A fuel consumption improvement range of 14 to 24% was predicted, resulting in successful project progression to the design and experimental validation phase. Furthermore, an overview of the experimental engine and hybrid system status concludes the discussion along with the multi-year project’s next steps.

33 ADVANCED PROPULSION SYSTEMS↗
NASA NTRS2015

Taxi Time Prediction at Charlotte Airport Using Fast-Time Simulation and Machine Learning Techniques

Accurate taxi time prediction can be used for more efficient runway scheduling to increase runway throughput and reduce taxi times and fuel consumptions on the airport surface. This paper describes two different approaches to predicting taxi times, which are a data-driven analytical method using machine learning techniques and a fast-time simulation-based approach. These two taxi time prediction methods are applied to realistic flight data at Charlotte Douglas International Airport (CLT) and assessed with actual taxi time data from the human-in-the-loop simulation for CLT airport operations using various performance measurement metrics. Based on the preliminary results, we discuss how the taxi time prediction accuracy can be affected by the operational complexity at this airport and how we can improve the fast-time simulation model for implementing it with an airport scheduling algorithm in real-time operational environment.

Lee, Hanbong↗
NASA NTRS2005

Performance Cycle Analysis of a Two-Spool, Separate-Exhaust Turbofan With Interstage Turbine Burner

This paper presents the performance cycle analysis of a dual-spool, separate-exhaust turbofan engine, with an Interstage Turbine Burner serving as a secondary combustor. The ITB, which is located at the transition duct between the high- and the low-pressure turbines, is a relatively new concept for increasing specific thrust and lowering pollutant emissions in modern jet engine propulsion. A detailed performance analysis of this engine has been conducted for steady-state engine performance prediction. A code is written and is capable of predicting engine performances (i.e., thrust and thrust specific fuel consumption) at varying flight conditions and throttle settings. Two design-point engines were studied to reveal trends in performance at both full and partial throttle operations. A mission analysis is also presented to assure the advantage of saving fuel by adding ITB.

Liew, K. H.↗
NASA NTRS1958

Experimental Behavior of Pentaborane-Air Combustion Products During Expansion in a Convergent Divergent Nozzle

In order to evaluate the post combustion behavior of boric oxide, pentaborane-air mixtures, burned to completion at a combustor pressure of 3 atmospheres, were expanded through a 7.1-inch-long convergent-divergent nozzle having a 4-inch-diameter throat and an exit-to-throat area ratio of 1.68. The experimentally determined thrust performance was in good agreement with the ideal equilibrium performance at stagnation temperatures of 3300 deg R and lower. The boric oxide vapor at the combustor exit required about 400 F deg supercooling before any condensed phase was observed. For a given thrust, fuel consumption was as much as 20 percent greater than predicted from vapor-pressure data for combustor outlet temperatures i n the vicinity of 3600 deg R. A similar result could be expected in full-scale engines, since the test combustor provided an unusually long dwell time and a highly turbulent environment. During the expansion process, the vapor (when present) did not condense to the extent predicted for an equilibrium expansion process. Moreover, condensation was observed only i n the form of small, abrupt phase changes i n the subsonic flow near the throat. Friction, due to liquid boric oxide films on the nozzle surfaces, was negligible when the surface temperature was above 800 F.

PENTABORANE↗
DOE OSTI2025

Scalability analysis of heavy-duty gas turbines using data-driven machine learning

With the increasing integration of variable renewable energy sources into power systems, the role of flexible power generation technologies like gas turbines (GT) in rapid grid balancing remains crucial. This sustained importance underscores the need for scaled and precise modeling of GT to ensure effective integration within evolving energy frameworks. While physics-driven GT models integrate thermodynamics, fluid dynamics, and combustion principles, they often rely on approximate mathematical representations to accommodate scaling that may not capture the actual complex dynamics for GTs and inertial effects associated to GTs with different ratings. In this study, a data-driven model is proposed using machine learning (ML) techniques to conduct GT scalability analysis and performance evaluation with high accuracy. The ML model, trained on data from various operating conditions and performance parameters, aims to uncover intricate relationships and patterns, resembling GT characteristics at different scales (ratings). The model is developed to capture complex system interaction and to adapt to changing operational scenarios at different capacities, providing valuable insights of power system dynamics. In this study, the real-time digital simulator platform was employed to generate training data for the ML model and assess its dynamic characteristics. The ultimate objective was to develop a detailed modeling framework based on governing equations and data-driven ML capable of predicting key performance indicators, in thermal systems such as GTs, including power output, speed, fuel consumption, and exhaust temperature under diverse operating conditions at different scales. The developed ML framework demonstrated high accuracy, with mean relative errors for GT power prediction, reference speed, exhaust temperature, and compressor pressure ratio (CPR) parameters consistently below 0.1% across typical load fluctuation scenarios. Maximum deviations were limited to approximately 0.5 K for exhaust temperature and 0.009 for CPR, underscoring the model’s ability to replicating dynamic GT behavior with high precision. The adaptability of the ML model enables its application across diverse operational conditions and its extension to other thermal systems. By leveraging advanced ML techniques, this study presents a robust and scalable modeling framework that enhances GT simulation precision, facilitating improved integration into evolving power systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1992

Development of advanced high temperature in-cylinder components and tribological systems for low heat rejection diesel engines, phase 1

Analysis and concept design work completed in Phase 1 have identified a low heat rejection engine configuration with the potential to meet the Heavy Duty Transport Technology program specific fuel consumption goal of 152 g/kW-hr. The proposed engine configuration incorporates low heat rejection, in-cylinder components designed for operation at 24 MPa peak cylinder pressure. Water cooling is eliminated by selective oil cooling of the components. A high temperature lubricant will be required due to increased in-cylinder operating temperatures. A two-stage turbocharger air system with intercooling and aftercooling was selected to meet engine boost and BMEP requirements. A turbocompound turbine stage is incorporated for exhaust energy recovery. The concept engine cost was estimated to be 43 percent higher compared to a Caterpillar 3176 engine. The higher initial engine cost is predicted to be offset by reduced operating costs due the lower fuel consumption.

Kroeger, C. A.↗
DOE OSTI2023

Hierarchical multi-time-scale predictive thermal management and fuel optimization for heavy-duty compression ignition engines

For heavy-duty diesel engines, NO X emissions reduction is strongly constrained by fuel efficiency. This paper presents a hierarchical model predictive controller (H-MPC) for coordinated control of tailpipe NO X emissions and fuel consumption. The H-MPC uses the separation of slow and fast dynamics that exist in the engine and its aftertreatment system. The controller is synthesized with an architecture in which a high-level MPC uses a longer prediction horizon compared to the low-level predictive controller which tracks the high-level controller command and manages the thermal dynamics of the aftertreatment system. Engine load preview enables the high-level controller to estimate the desired catalyst temperature ahead of time and addresses the selective catalytic reduction (SCR) slow thermal dynamics. Calculated by the high-level controller, the intake manifold pressure, and the start of injection (SOI) crank angle is used as reference trajectories in the low-level controller that regulates fast dynamical behaviors such as engine out NO X emissions. Hardware-in-the-loop (HIL) validation of this integrated H-MPC on a rapid prototype controller shows that when the SCR catalyst temperature is above light-off temperature (warmed-up condition), the engine operation is shifted to operate with the best fuel economy since the warmed-up SCR can efficiently reduce the engine-out NO X emissions. Results indicate that up to 0.8% benefit in cycle averaged BSFC along with a 13% reduction in tailpipe NO X compared to a stock engine calibration can be achieved with the coordinated engine and aftertreatment system through H-MPC.

Engineering↗
NASA NTRS2011

Reducing US Oil Dependence Using Simulation

People across the world are addicted to oil; as a result, the instability of oil prices and the shortage of oil reserves have influenced human behaviors and global businesses. Today, the United States makes up only 5% of the global population but consumes 25% of the. world total energy. Most of this energy is generated from fossil fuels in the form of electricity. The contribution of this paper is to examine the possibilities of replacing fossil fuel with renewable energies to generate electricity as well as to examine other methods to reduce oil and gas consumption. We propose a system dynamics model in an attempt to predict the future US dependence on fossil fuels by using renewable energy resources such as, nuclear, wind, solar, and hydro powers. Based on the findings of our model, the study expects to provide insights towards promising solutions of the oil dependency problem.

Ayoub, Fadi↗
NASA NTRS1979

Causes of high pressure compressor deterioration in service

The high mechanical reliability and low deterioration rate of the JT9D high-pressure compressor results in long utilization without exceeding engine operational limits. The increasing cost and decreasing supply of fuel have focused attention on the fuel burned implications of such high time use without refurbishment. The paper presents the results of JT9D high pressure compressor studies. The mechanical deterioration of the JT9D high-pressure compressor gaspath parts versus increasing service usage, documented from inspection of service parts, is presented and discussed including changes in airfoil roughness, blade length, airfoil contour and outer air seal trench characteristics. An estimate of the performance loss versus usage is related to each type of damage. The combined estimated high-pressure compressor performance loss for all mechanisms determined from part inspection is compared to historical engine test data to establish the validity of the predicted loss levels. The effect of cold section refurbishment on engine fuel consumption recovery and the results of an optimization study to determine the appropriate interval for high pressure compressor refurbishment are also reported.

Richardson, J. H.↗
NASA NTRS2015

A Metric to Quantify Shared Visual Attention in Two-Person Teams

Introduction: Critical tasks in high-risk environments are often performed by teams, the members of which must work together efficiently. In some situations, the team members may have to work together to solve a particular problem, while in others it may be better for them to divide the work into separate tasks that can be completed in parallel. We hypothesize that these two team strategies can be differentiated on the basis of shared visual attention, measured by gaze tracking. 2) Methods: Gaze recordings were obtained for two-person flight crews flying a high-fidelity simulator (Gontar, Hoermann, 2014). Gaze was categorized with respect to 12 areas of interest (AOIs). We used these data to construct time series of 12 dimensional vectors, with each vector component representing one of the AOIs. At each time step, each vector component was set to 0, except for the one corresponding to the currently fixated AOI, which was set to 1. This time series could then be averaged in time, with the averaging window time (t) as a variable parameter. For example, when we average with a t of one minute, each vector component represents the proportion of time that the corresponding AOI was fixated within the corresponding one minute interval. We then computed the Pearson product-moment correlation coefficient between the gaze proportion vectors for each of the two crew members, at each point in time, resulting in a signal representing the time-varying correlation between gaze behaviors. We determined criteria for concluding correlated gaze behavior using two methods: first, a permutation test was applied to the subjects' data. When one crew member's gaze proportion vector is correlated with a random time sample from the other crewmember's data, a distribution of correlation values is obtained that differs markedly from the distribution obtained from temporally aligned samples. In addition to validating that the gaze tracker was functioning reasonably well, this also allows us to compute probabilities of coordinated behavior for each value of the correlation. As an alternative, we also tabulated distributions of correlation coefficients for synthetic data sets, in which the behavior was modeled as a first-order Markov process, and compared correlation distributions for identical processes with those for disparate processes, allowing us to choose criteria and estimate error rates. 3) Discussion: Our method of gaze correlation is able to measure shared visual attention, and can distinguish between activities involving different instruments. We plan to analyze whether pilots strategies of sharing visual attention can predict performance. Possible measurements of performance include expert ratings from instructors, fuel consumption, total task time, and failure rate. While developed for two-person crews, our approach can be applied to larger groups, using intra-class correlation coefficients instead of the Pearson product-moment correlation.

Gontar, Patrick↗