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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Comparison of Vehicle-Broadcasted Fuel Consumption Rates against Precise Fuel Measurements for Medium- and Heavy-Duty Vehicles and Engines

Vehicles continuously report real-time fuel consumption estimates over their data bus, known as the controller area network (CAN). However, the accuracy of these fueling estimates is uncertain to researchers who collect these data from any given vehicle. To assess the accuracy of these estimates, CAN-reported fuel consumption data are compared against fuel measurements from precise instrumentation. The data analyzed consisted of eight medium/heavy-duty vehicles and two medium-duty engines. Varying discrepancies between CAN fueling rates and the more accurate measurements emerged but without a vehicular trend-for some vehicles the CAN under-reported fuel consumption and for others the CAN over-reported fuel consumption. Furthermore, a qualitative real-time analysis revealed that the operating conditions under which these fueling discrepancies arose varied among vehicles. A drive cycle analysis revealed that while CAN fueling estimate accuracy differs for individual vehicles, that CAN estimates capture the relative fuel consumption differences between drive cycles within 4% for all vehicles and even more accurately for some vehicles. Furthermore, in situations where only CAN-reported data are available, CAN fueling estimates can provide relative fuel consumption trends but not accurate or precise fuel consumption rates.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2018

Fuel consumption for various driving styles in conventional and hybrid electric vehicles: Integrating driving cycle predictions with fuel consumption optimization

Here, improving fuel economy and lowering emissions are key societal goals. Standard driving cycles, pre-designed by the US Environmental Protection Agency (EPA), have long been used to estimate vehicle fuel economy in laboratory-controlled conditions. They have also been used to test and tune different energy management strategies for hybrid electric vehicles (HEVs). This paper aims to estimate fuel consumption for a conventional vehicle and a HEV using personalized driving cycles extracted from real-world data to study the effects of different driving styles and vehicle types on fuel consumption when compared to the estimates based on standard driving cycles. To do this, we extracted driving cycles for conventional vehicles and HEVs from a large-scale U.S. survey that contains real-world GPS-based driving records. Next, the driving cycles were assigned to one of three categories: volatile, normal, or calm. Then, the driving cycles were used along with a driver-vehicle simulation that captures driver decisions (vehicle speed during a trip), powertrain, and vehicle dynamics to estimate fuel consumption for conventional vehicles and HEVs with power-split powertrain. To further optimize fuel consumption for HEVs, the Equivalent Consumption Minimization Strategy (ECMS) is applied. The results show that depending on the driving style and the driving scenario, conventional vehicle fuel consumption can vary widely compared with standard EPA driving cycles. Specifically, conventional vehicle fuel consumption was 13% lower in calm urban driving, but almost 34% higher for volatile highway driving compared with standard EPA driving cycles. Interestingly, when a driving cycle is predicted based on the application of case-based reasoning and used to tune the power distribution in a hybrid electric vehicle, its fuel consumption can be reduced by up to 12% in urban driving. Implications and limitations of the findings are discussed.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2015

Estimate of Fuel Consumption and GHG Emission Impact on an Automated Mobility District: Preprint

This study estimates the range of fuel and emissions impact of an automated-vehicle (AV) based transit system that services campus-based developments, termed an automated mobility district (AMD). The study develops a framework to quantify the fuel consumption and greenhouse gas (GHG) emission impacts of a transit system comprised of AVs, taking into consideration average vehicle fleet composition, fuel consumption/GHG emission of vehicles within specific speed bins, and the average occupancy of passenger vehicles and transit vehicles. The framework is exercised using a previous mobility analysis of a personal rapid transit (PRT) system, a system which shares many attributes with envisioned AV-based transit systems. Total fuel consumption and GHG emissions with and without an AMD are estimated, providing a range of potential system impacts on sustainability. The results of a previous case study based of a proposed implementation of PRT on the Kansas State University (KSU) campus in Manhattan, Kansas, serves as the basis to estimate personal miles traveled supplanted by an AMD at varying levels of service. The results show that an AMD has the potential to reduce total system fuel consumption and GHG emissions, but the amount is largely dependent on operating and ridership assumptions. The study points to the need to better understand ride-sharing scenarios and calls for future research on sustainability benefits of an AMD system at both vehicle and system levels.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2026

Diesel Fuel Consumption in Prominent U.S. Open-Pit Mines: Site-Level Estimates

This report presents a comprehensive framework for estimating diesel fuel consumption and prices at open-pit mines in the United States. The framework includes transparent methods for calculating site-level diesel energy use when direct reporting is unavailable, and a structured confidence evaluation for each method. The framework is demonstrated to estimate current diesel consumption at 21 open-pit mines in the United States. Initial findings support ongoing efforts to strengthen the competitiveness and security of the U.S. industrial base by supporting data-driven supply chain analysis and decision-making, improved transparency in mining sector energy use, and targeted deployment of energy innovation and cost-reduction strategies. Future updates to the dataset—coupled with expanded data transparency and method validation—will help ensure that the findings remain relevant as the sector continues to evolve.

02 PETROLEUM↗
DOE OSTI2013

Impact of Solar Control PVB Glass on Vehicle Interior Temperatures, Air-Conditioning Capacity, Fuel Consumption, and Vehicle Range

The objective of the study was to assess the impact of Saflex1 S-series Solar Control PVB (polyvinyl butyral) configurations on conventional vehicle fuel economy and electric vehicle (EV) range. The approach included outdoor vehicle thermal soak testing, RadTherm cool-down analysis, and vehicle simulations. Thermal soak tests were conducted at the National Renewable Energy Laboratory's Vehicle Testing and Integration Facility in Golden, Colorado. The test results quantified interior temperature reductions and were used to generate initial conditions for the RadTherm cool-down analysis. The RadTherm model determined the potential reduction in air-conditioning (A/C) capacity, which was used to calculate the A/C load for the vehicle simulations. The vehicle simulation tool identified the potential reduction in fuel consumption or improvement in EV range between a baseline and modified configurations for the city and highway drive cycles. The thermal analysis determined a potential 4.0% reduction in A/C power for the Saflex Solar PVB solar control configuration. The reduction in A/C power improved the vehicle range of EVs and fuel economy of conventional vehicles and plug-in hybrid electric vehicles.

14 SOLAR ENERGY↗
NASA NTRS1977

Full-scale altitude engine test of a turbofan exhaust-gas-forced mixer to reduce thrust specific fuel consumption

The specific fuel consumption of a low-bypass-ratio, confluent-flow, turbofan engine was measured with and without a mixer installed. Tests were conducted for flight Mach numbers from 0.3 to 1.4 and altitudes from 10,670 to 14,630 meters (35,000 to 48,000 ft) for core-stream-to-fan-stream temperature ratios of 2.0 and 2.5 and mixing-length-to-diameter ratios of 0.95 and 1.74. For these test conditions, the reduction in specific fuel consumption varied from 2.5 percent to 4.0 percent. Pressure loss measurements as well as temperature and pressure surveys at the mixer inlet, the mixer exit, and the nozzle inlet were made.

Cullom, R. R.↗
DOE OSTI2014

Effect Of Platooning on Fuel Consumption of Class 8 Vehicles Over a Range of Speeds, Following Distances, and Mass

This research project evaluates fuel consumption results of two Class 8 tractor-trailer combinations platooned together compared to their standalone fuel consumption. A series of ten modified SAE Type II J1321 fuel consumption track tests were performed to document fuel consumption of two platooned vehicles and a control vehicle at varying steady-state speeds, following distances, and gross vehicle weights (GVWs). The steady-state speeds ranged from 55 mph to 70 mph, the following distances ranged from a 20-ft following distance to a 75-ft following distance, and the GVWs were 65K lbs and 80K lbs. All tractors involved had U.S. Environmental Protection Agency (EPA) SmartWay-compliant aerodynamics packages installed, and the trailers were equipped with side skirts. Effects of vehicle speed, following distance, and GVW on fuel consumption were observed and analyzed. The platooning demonstration system used in this study consisted of radar systems, Dedicated Short-Range Communication (DSRC) vehicle-to-vehicle (V2V) communications, vehicle braking and torque control interface, cameras and driver displays. The lead tractor consistently demonstrated an improvement in average fuel consumption reduction as following distance decreased, with results showing 2.7% to 5.3% fuel savings at a GVW of 65k. The trailing vehicle achieved fuel consumption savings ranging from 2.8% to 9.7%; tests during which the engine cooling fan did not operate achieved savings of 8.4% to 9.7%. 'Team' fuel savings, considering the platooned vehicles as one, ranged from 3.7% to 6.4%, with the best combined result being for 55 mph, 30-ft following distance, and 65k GVW.

33 ADVANCED PROPULSION SYSTEMS↗
NASA NTRS1938

Fuel Consumption of a Carburetor Engine at Various Speeds and Torques

An investigation was conducted to obtain fuel-consumption curves for a single-cylinder engine with a Wright 1820-G and Pratt & Whitney 1340-H cylinder at varying speeds, manifold pressures, and air-fuel ratios. The 1340- H cylinder was tested at speeds from 1,200 to 2,400 r.p.m. and at manifold pressures from 21 to 38 inches of mercury absolute. Less than extensive tests were made of the 1820-G cylinder. The results of the tests showed that the minimum brake fuel consumption was obtained when the engines were operating at high torques and at speeds from 60 to 70 percent of the rated speed. The fuel consumption increased at an increasing rate as the torque was reduced; and, at 45 percent of maximum torque, the fuel consumption was 20 percent higher than at maximum torque when the engines were operating at 70 percent of rated speed. Minimum specific fuel consumption was obtained at the same air-fuel ratio regardless of compression ratio. No improvement in fuel consumption was obtained when mixtures leaner than an air-fuel ratio of 15.5 were used. The leanest mixture ratio on which the engine with the 1340-H cylinder would operate smoothly was 18.5 and the spark advance for maximum power with this mixture ratio was 50 degrees B.T.C. A method is discussed for reducing the amount of testing necessary to obtain curves for minimum brake fuel consumption.

Schey, Oscar W↗
DOE OSTI2021

Hybrid electric buses fuel consumption prediction based on real-world driving data

Estimating fuel consumption by hybrid diesel buses is challenging due to its diversified operations and driving cycles. Here, long-term transit bus monitoring data were utilized to empirically compare fuel consumption of diesel and hybrid buses under various driving conditions. Artificial neural network (ANN) based high-fidelity microscopic (1 Hz) and mesoscopic (5–60 min) fuel consumption models were developed for hybrid buses. The microscopic model contained 1 Hz driving, grade, and environment variables. The mesoscopic model aggregated 1 Hz data into 5 to 60-minute traffic pattern factors and predicted average fuel consumption over its duration. The prediction results show mean absolute percentage errors of 1–2% for microscopic models and 5–8% for mesoscopic models. The data were partitioned by different driving speeds, vehicle engine demand, and road grade to investigate their impacts on prediction performance.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2017

Data-driven fuel consumption estimation: A multivariate adaptive regression spline approach

Providing guidance and information to drivers to help them make fuel-efficient route choices remains an important and effective strategy in the near term to reduce fuel consumption from the transportation sector. One key component in implementing this strategy is a fuel-consumption estimation model. In this paper, we developed a mesoscopic fuel consumption estimation model that can be implemented into an eco-routing system. Our proposed model presents a framework that utilizes large-scale, real-world driving data, clusters road links by free-flow speed and fits one statistical model for each of cluster. This model includes predicting variables that were rarely or never considered before, such as free-flow speed and number of lanes. We applied the model to a real-world driving data set based on a global positioning system travel survey in the Philadelphia-Camden-Trenton metropolitan area. Results from the statistical analyses indicate that the independent variables we chose influence the fuel consumption rates of vehicles. But the magnitude and direction of the influences are dependent on the type of road links, specifically free-flow speeds of links. Here, a statistical diagnostic is conducted to ensure the validity of the models and results. Although the real-world driving data we used to develop statistical relationships are specific to one region, the framework we developed can be easily adjusted and used to explore the fuel consumption relationship in other regions.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2024

Developing an Energy-Conscious Traffic Signal Control System for Optimized Fuel Consumption in Connected Vehicle Environments

The project titled “Developing an Energy-Conscious Traffic Signal Control System for Optimized Fuel Consumption in Connected Vehicle Environments” addresses energy-related challenges associated with adaptive traffic control systems by integrating connected vehicles (CV) and connected infrastructure (CI). The system developed in this project, a CV-based adaptive traffic control system, aims to improve fuel consumption in mixed traffic environments by capitalizing on emerging CV and CI communication technologies, as well as leveraging recent advances in Artificial Intelligence (AI), optimization, and edge computing. The system was tested at the MLK Smart Corridor, an urban testbed managed by the University of Tennessee at Chattanooga (UTC) and the City of Chattanooga. The system was validated through extensive simulations, both Software-in-the-Loop (SILS) and Hardware-in-the-Loop (HILS), and was further implemented and tested in real-world conditions at several intersections along the corridor. The Fuel Consumption Performance Index (FC-PI) and the Ecological Performance Index (Eco-PI) were developed as the key components for evaluating the system’s impact on fuel consumption and emissions. These metrics provided a comprehensive means of understanding the impact of traffic signal control optimization in mixed traffic environments. The report presents an in-depth analysis of the Eco-PI, FC-PI, adaptive traffic control system integration, and the testing and field implementation of the system. The results demonstrate significant reductions in fuel consumption and emissions, showcasing the system’s capability to contribute to more sustainable urban traffic management. The report also documents the challenges encountered and recommendations for scaling and further improving the system.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2019

A Simple Hybrid Electric Vehicle Fuel Consumption Model for Transportation Applications(DOI: 10.5772/intechopen.89055)

This study presents a simple power-based microscopic hybrid electric vehicle (HEV) fuel consumption model for use in microscopic traffic software and various connected and automated vehicle (CAV) applications, including eco-routing and eco-drive systems. While numerous HEV energy consumption models have been developed, these models are complex and require vehicle engine data deeming them difficult to implement and making them nontransferable. The proposed model was developed using empirical data for a 2010 Toyota Prius—the most popular HEV. The model was then extended to other HEVs thus extending the domain of application of the model. The proposed fuel consumption model estimates the instantaneous fuel consumption rates of an HEV using instantaneous vehicle operational input variables, including the vehicle’s speed, acceleration, and roadway grade, which can be acquired from global positioning system (GPS) equipment or other sensors. The model estimates vehicle fuel consumption rates consistent with empirical data producing an average error of 2.1% for the Toyota Prius and up to 4% for other HEVs demonstrating the applicability and transferability of the model to various HEVs.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2016

Fuel consumption impacts of auto roof racks

The after-market roof rack is one of the most common components attached to a vehicle for carrying over-sized items, such as bicycles and skis. It is important to understand these racks' fuel consumption impacts on both individual vehicles and the national fleet because they are widely used. We estimate the national fuel consumption impacts of roof racks using a bottom-up approach. Our model incorporates real-world data and vehicle stock information to enable assessing fuel consumption impacts for several categories of vehicles, rack configurations, and usage conditions. In addition, the model draws on two new data-gathering techniques, on-line forums and crowd-sourcing. The results show that nationwide, roof racks are responsible for 0.8‰ of light duty vehicle fuel consumption in 2015, corresponding to 100 million gallons of gasoline per year. Sensitivity analyses show that results are most sensitive to the fraction of vehicles with installed roof racks but carrying no equipment. Here, the aerodynamic efficiency of typical roof racks can be greatly improved and reduce individual vehicle fuel consumption; however, government policies to minimize extensive driving with empty racks--if successful--could save more fuel nationally.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2017

The Accuracy and Correction of Fuel Consumption from Controller Area Network Broadcast

Fuel consumption (FC) has always been an important factor in vehicle cost. With the advent of electronically controlled engines, the controller area network (CAN) broadcasts information about engine and vehicle performance, including fuel use. However, the accuracy of the FC estimates is uncertain. In this study, the researchers first compared CAN-broadcasted FC against physically measured fuel use for three different types of trucks, which revealed the inaccuracies of CAN-broadcast fueling estimates. To match precise gravimetric fuel-scale measurements, polynomial models were developed to correct the CAN-broadcasted FC. Lastly, the robustness testing of the correction models was performed. The training cycles in this section included a variety of drive characteristics, such as high speed, acceleration, idling, and deceleration. The mean relative differences were reduced noticeably.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2019

Economic Optimal Control for Minimizing Fuel Consumption of Heavy-Duty Trucks in a Highway Environment

This paper provides a comparative assessment of three economic optimal control strategies, aimed at minimizing the fuel consumption of heavy-duty trucks in a highway environment, under a representative lead vehicle model informed by traffic data. These strategies fuse a global, offline dynamic programming (DP) optimization with online model predictive control (MPC). We then show how two of the three strategies can be adapted to accommodate the presence of traffic and optimally navigate signalized intersections using infrastructure-to-vehicular (I2V) communication. The MPC optimization, which is local in nature, makes refinements to a coarsely (but globally, subject to grid resolution) optimized target velocity profile from the DP optimization. The three candidate economic MPC formulations that are evaluated include: a nonlinear time-based formulation that directly penalizes predicted fuel consumption, a nonlinear time-based formulation that penalizes braking effort as a surrogate for fuel consumption, and a linear distance-based convex formulation that maintains a tradeoff between energy expenditure and tracking of the coarsely optimized velocity profile obtained from DP. Using a medium-fidelity Simulink model, based on a Volvo truck's longitudinal and engine dynamics, we analyze the optimization's performance on four highway routes under various traffic scenarios. Results demonstrate 3.7-8.3% fuel economy improvement on highway routes without traffic and 6.5-10% on the same routes with traffic included. Furthermore, we present a detailed analysis of energy usage by "type" (aerodynamic losses, braking losses, and comparison of brake-specific fuel consumption), under each candidate control strategy.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2023

Reducing Fuel Consumption on a Heavy-Duty Nonroad Vehicle: Conventional Powertrain Modifications

This investigation focuses on conventional powertrain technologies that provide operational synergy based on customer utilization to reduce fuel consumption for a heavy-duty, nonroad (off-road) material handler. The vehicle of interest is a Pettibone Cary-Lift 204i, with a base weight of 50,000 lbs. and a lift capacity of 20,000 lbs. The conventional powertrain consists of a US Tier 4 Final diesel engine, a non-lockup torque converter, a four-speed powershift automatic transmission, and all-wheel drive. The paper will present a base vehicle energy/fuel consumption breakdown of propulsion, hydraulic and idle distribution based on a representative end-user drive cycle. The baseline vehicle test data was then used to develop a correlated lumped parameter model of the vehicle-powertrain-hydraulic system that can be used to explore technology integration that can reduce fuel consumption. Two conventional powertrain modifications are explored that provide potential pathways that significantly alter the base powertrain and include 1.) a torque converter disconnect clutch and 2.) a low voltage stop-start system that have the potential to reduce fuel consumption on the end user representative drive cycle by 10.3% and 9.8%, respectively. Details of how the powertrain modifications would be executed, physical hardware, and application to other heavy-duty nonroad vehicle applications are included in the discussion.

33 ADVANCED PROPULSION SYSTEMS↗
NASA NTRS2016

Comparison of Fuel Consumption of Descent Trajectories Under Arrival Metering

This paper compares fuel consumption of descent trajectories from cruise altitude to meter fix when the required time of arrival is later than the nominal time of arrival at the meter fix. The required delay, which is the difference between the nominal and the required times of arrival, is achieved by either slowing down the aircraft in the cruise and descent phases or flying a longer route at a constant altitude. Performance models of ten different Boeing and Airbus aircraft, obtained from the Base of Aircraft Data, are employed for generating the results. It is demonstrated that the most fuel-efficient speed control strategy for absorbing delay is first reducing descent speed as much as possible and then reducing cruise speed. This is a common finding for all ten aircraft considered. For some aircraft, flying at a fixed flight path angle and constant Mach-calibrated-airspeed results in lower fuel consumption compared to standard descent at idle-thrust and constant Mach-calibrated- airspeed. Finally, for the cases examined, it is shown that executing a path stretch maneuver at cruise altitude and descent at a reduced speed is more fuel efficient than inserting an intermediate-altitude cruise segment.

Nikoleris, Tasos↗