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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Enabling Fast Charging: A Technology Gap Assessment

The transportation sector accounts for the largest percentage of energy use in the United States. Decreasing energy consumption across this sector, especially in commercial light duty transportation, is essential for the U.S. to gain energy independence. Recently, powertrain electrification with plug-in electric vehicles (PEVs) have gained traction as an alternative due to their inherent efficiency advantages compared to the traditional internal combustion engine vehicle (ICEV). Accounting for 500,000 vehicle on the road today, these PEVs will reduce oil imported into the U.S. by five billion gallons and save two billion dollars in fuel costs to consumers over their useful life. Though there are many different classes of PEV, the intent of this study is to focus on non-hybrid powertrains, or battery electric vehicles (BEVs). Despite rapid drops in cost within the BEV powertrain of over 4x in the last 10 years, the PEV market still only accounts for approximately 1% of new light duty vehicle sales annually. Though BEV powertrain costs are not quite at parity with the ICEV, another gap to wider adoption of BEVs that have been identified is the ability to refuel quickly, or to fast charge. Though the majority of recharging BEVs is done at home, having access to fast charge stations has a big impact on BEV utility from a consumer perspective. To address the fast charge barrier, charging at 350 kW, or extreme fast charging (XFC), has been proposed and will serve as the basis for discussion in this report. Studies have shown that in areas where drivers have access to 50 kW or 120 kW fast charge stations, annual electric vehicle miles traveled (eVMT) increased by over 25%, even in cases where fast charging was used for 1-5% of total charging events [1, 2]. Having access to these fast charge stations can help alleviate the “range anxiety” that is cited as a common reason for consumers to hesitate to buy a BEV. Though, to be truly competitive to the ICEV refueling experience, even higher power stations are necessary. These extreme fast charge stations (XFC) should be able to recharge a BEV in less than 10 minutes and provide approximately 175 additional miles of driving. However, this introduces a host of new challenges that need to be addressed. As a result, it is expected that packs designed to meet XFC will be significantly more expensive initially than BEVs optimized for range that can reach 140kW with current technology. From the battery cell to the power grid to which these 350 kW chargers are connected, this study will discuss the issues that need to be addressed at each level in order to implement a 350 kW charging network. Although this report is U.S.-focused, the findings should be applicable to other countries with mature automotive infrastructures.

25 ENERGY STORAGE↗
NASA NTRS1981

The AGT101 technology - An automotive alternative

The Advanced Gas Turbine Powertrain System Development Project is oriented at providing the United States automotive industry the technology base necessary to produce gas turbine powertrains for automotive applications that will have: (1) reduced fuel consumption, (2) the ability to use a variety of fuels, (3) low emissions, and (4) competitive cost/performance. The AGT101 powertrain being developed consists of a regenerated single-shaft gas turbine engine flat rated at 74.6 kW (100 hp) coupled to a split-differential gearbox and a Ford automatic overdrive production transmission. Performance predictions for the AGT101 powertrain represent a 59-percent improvement in mileage estimates over a 1985 conventionally-powered automobile for the combined federal driving cycle.

Rackley, R. A.↗
NASA NTRS1981

Ceramics for the AGT101 automotive gas turbine

An advanced gas turbine powertrain for automotive application is being developed. Objectives of the program include a fuel consumption of 42.8 mpg on No. 2 diesel fuel in a 3000 pound car, same overall vehicle performance as obtained with a conventional spark ignition internal combustion engine, low emission, multiple fuel capacity, reliability, and competitive cost. The AGT101 powertrain consists of a power section, gearbox and transmission, and the design and analysis conducted thus far support the initial engine concept, as no significant design changes have been required. The ceramic rotor design approach and component materials are discussed, and it is projected that the AGT powertrain will be competitive with any other alternative powertrain in meeting the design objectives.

Kreiner, D. M.↗
NASA NTRS2020

Hybrid Electric MC-12 Ground Testing Plan Chapter

In the commercial aviation world, hybrid/electric propulsion is a promising technology for fuel, emissions, and noise reduction in support of the challenging goals established by 2050 EU Flightpath/SRIA, NASA ARMD Strategic Implementation Plan, and the US Air Force ATTAM programs. Ongoing results indicate operational benefits are possible in those three technical areas. Considering military applications, hybrid/electric propulsion may yield further significant improvements by enabling new, unorthodox mission capabilities. Potential benefits are expected in the areas of vehicle signature reduction (lower noise, lower exhaust signature), usage in enhanced flight environments, minimized human-in-the-loop workload by offering a platform compatible with future goals of autonomous operations facilitation, maintenance cost reductions, and performance burst/dash energy. Additional synergies are likely when used in conjunction with energy weapons. Some potential areas of mutual interest could include, dusty operations capability, remote supply capability, extended surveillance, dispatch able power, fuel-flexible vehicles, and autonomous rescue equipment. Many of the key technologies that have been demonstrated in ground operation must now be qualified for altitude conditions. We expect to have many flight qualified powertrain systems over the next decade for military planners to choose from for new future battlefield capability. This requires new flight-weight and flight-efficient powertrain components, fault tolerant power management, and electromagnetic interference mitigation technologies. Moreover, initial studies indicate some combination of ambient and cryogenic thermal management and relatively high bus voltages when compared to state of practice will be required to achieve a net system benefit. Developing all these powertrain technologies within a realistic aircraft architectural geometry and under realistic operational conditions requires a unique electric aircraft test bed. The MC-12 surveillance aircraft is an ideal military aircraft for demonstrating some of the benefits of incorporating hybrid electric propulsion. This report details an approach for full-scale ground-based altitude testing the hybrid electric MC-12 powertrain through a full flight profile.

military electric aircraft propulsion↗
NASA NTRSDate not supplied

Piloted Evaluation of a Fault Recovery System for an Aircraft with Distributed Electric Propulsion

Electrified aircraft powertrains contain multiple tightly coupled subsystems, making them much more complex than traditional aircraft propulsion systems, both in terms of integration and control. Electrification enables aircraft to have multiple distributed thrust-producing fans that the flight control system can utilize for enhanced maneuverability, further increasing the control complexity. The SUbsonic Single Aft eNgine (SUSAN) Electrofan is a NASA concept aircraft that leverages this technology. SUSAN is a series/parallel partial hybrid electric single-aisle transport aircraft that takes advantage of its electrified powertrain to provide fuel burn and emissions benefits when compared to the state-of-the-art. Achieving these benefits requires an appropriately designed control architecture that coordinates the various powertrain and flight control subsystems. As such, the SUSAN aircraft is designed with a high level of automation, allowing it to properly manage coupled subsystems and react rapidly to failures and anomalies. To do this effectively, algorithms that perform component health management, fault detection, isolation, and accommodation, and continuous optimization, must be developed, tested, validated, and implemented. This paper describes a piloted evaluation of such an algorithm in scenarios with multiple fan failures, performed in a flight simulator, demonstrating failure recovery and continued safe operation up to the limits of the powertrain. These scenarios are subsequently related to certification requirements.

Electrified Aircraft Propulsion↗
NASA NTRS2025

Piloted Evaluation of a Fault Recovery System for an Aircraft with Distributed Electric Propulsion

Electrified aircraft powertrains contain multiple tightly coupled subsystems, making them much more complex than traditional aircraft propulsion systems, both in terms of integration and control. Electrification enables aircraft to have multiple distributed thrust-producing fans that the flight control system can utilize for enhanced maneuverability, further increasing the control complexity. The SUbsonic Single Aft eNgine (SUSAN) Electrofan is a NASA concept aircraft that leverages this technology. SUSAN is a series/parallel partial hybrid electric single-aisle transport aircraft that takes advantage of its electrified powertrain to provide fuel burn and emissions benefits when compared to the state-of-the-art. Achieving these benefits requires an appropriately designed control architecture that coordinates the various powertrain and flight control subsystems. As such, the SUSAN aircraft is designed with a high level of automation, allowing it to properly manage coupled subsystems and react rapidly to failures and anomalies. To do this effectively, algorithms that perform component health management, fault detection, isolation, and accommodation, and continuous optimization, must be developed, tested, validated, and implemented. This paper describes a piloted evaluation of such an algorithm in scenarios with multiple fan failures, performed in a flight simulator, demonstrating failure recovery and continued safe operation up to the limits of the powertrain. These scenarios are subsequently related to certification requirements.

Electrified Aircraft Propulsion↗
NASA NTRSDate not supplied

Piloted Evaluation of a Fault Recovery System for an Aircraft with Distributed Electric Propulsion

Electrified aircraft powertrains contain multiple tightly coupled subsystems, making them much more complex than traditional aircraft propulsion systems, both in terms of integration and control. Electrification enables aircraft to have multiple distributed thrust-producing fans that the flight control system can utilize for enhanced maneuverability, further increasing the control complexity. The SUbsonic Single Aft eNgine (SUSAN) Electrofan is a NASA concept aircraft that leverages this technology. SUSAN is a series/parallel partial hybrid electric single-aisle transport aircraft that takes advantage of its electrified powertrain to provide fuel burn and emissions benefits when compared to the state-of-the-art. Achieving these benefits requires an appropriately designed control architecture that coordinates the various powertrain and flight control subsystems. As such, the SUSAN aircraft is designed with a high level of automation, allowing it to properly manage coupled subsystems and react rapidly to failures and anomalies. To do this effectively, algorithms that perform component health management, fault detection, isolation, and accommodation, and continuous optimization, must be developed, tested, validated, and implemented. This paper describes a piloted evaluation of such an algorithm in scenarios with multiple fan failures, performed in a flight simulator, demonstrating failure recovery and continued safe operation up to the limits of the powertrain. These scenarios are subsequently related to certification requirements.

Electrified Aircraft Propulsion↗
DOE OSTI2014

Optimization to reduce fuel consumption in charge depleting mode

A powertrain includes an internal combustion engine, a motor utilizing electrical energy from an energy storage device, and a plug-in connection. A Method for controlling the powertrain includes monitoring a fuel cut mode, ceasing a fuel flow to the engine based upon the fuel cut mode, and through a period of operation including acceleration of the powertrain, providing an entirety of propelling torque to the powertrain with the electrical energy from the energy storage device based upon the fuel cut mode.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2021

Effects of Hybridization on Selective Catalytic Reduction (SCR) Thermal Management of a Medium Heavy-Duty Hybrid Work Truck

The increased market penetration of hybrid electric powertrains in medium heavy-duty (MHD) applications has provided a novel platform for vehicle research. One example of such a platform is the MHD parallel hybrid truck developed by Odyne Systems, LLC. In collaboration with Odyne Systems, LLC and the Department of Energy (DOE), Oak Ridge National Laboratory (ORNL) developed a validated vehicle plant model for this truck and tested the Odyne powertrain in a hardware-in-the-loop (HIL) environment. While testing in the HIL environment, the effects of reduced engine load, and thus catalyst heating, on the selective catalytic reduction (SCR) catalyst produced diminished hybrid improvement as the level of energy storage usage increased. This article will discuss these results and the potentially unforeseen interactions with modern aftertreatment systems when hybridizing conventional powertrains.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2026

Heavy-Duty Nonroad Material Handler Electrification Part 2: Energy Efficiency and Performance Evaluation

Decarbonization efforts achieved through electrification in nonroad mobile machinery can realize a reduction in fuel consumption of more than 20%, thanks to concepts familiar to light-duty passenger vehicles. This case study compares the results of a hybrid-electric material handler to its conventional counterpart, utilizing machine-specific drive cycles presented in part one of this paper series. The hybrid prototype features an extended-range electric vehicle (EREV) powertrain that demonstrated substantial energy efficiency improvements. Specifically, there was a reduction in equivalent fuel consumption of 75% when operating in electric-only mode, and 33% when maintaining the battery by charging with an on-board generator. Together, the efficiency improvements can be extrapolated over a low-intensity, 8-h shift characterized by significant idle time and highly dynamic engine load for a 47% reduction in net energy consumption. Key technologies that led to this improvement included engine downsizing and decoupling, regenerative braking, and an electrohydraulic pump unit with advanced controls. Finally, his study explains details of the powertrain architecture and subsystems that were implemented on a demonstration vehicle, control strategies used to meet project goals, and an analysis of energy consumption from testing on a closed course. Also included in this study is a discourse on comparison metrics that can be used for quantifying the energy consumption differences between hybrid-electric and conventional diesel powertrains in nonroad mobile machinery.

25 ENERGY STORAGE↗
NASA NTRS2024

X-57 Maxwell High Lift Motor Controller Electromagnetic Interference Test Results

During research and development for NASA’s X-57 Maxwell all-electric aircraft project, the efficiency and power density requirements of its electric propulsion subsystem components were met, but aspects of integrating its powertrain subsystems proved problematic. Electromagnetic interference (EMI) from the cruise motor controller (CMC) was a significant challenge for the project. This problem was exacerbated by the lack of EMI requirements imposed on subsystem powertrain components. This report presents the results of EMI testing of the X-57 high lift motor controller (HLMC) at the NASA Glenn Research Center’s EMI Laboratory. For reference, the conducted emissions are compared to DO–160G and MIL–STD–61G conducted emissions limits. After the EMI test, mitigation of the conducted emissions using lightweight EMI chokes produced at NASA Glenn was evaluated using the Fast Fourier Transform (FFT) capability of an oscilloscope in the hardware development laboratory. This process can contribute to the rapid prototyping of electric powertrain components and EMI filters and improve the likelihood of successful EMI qualification at the component and system levels.

Silicon carbide↗
DOE OSTI2015

The heavy-duty vehicle future in the United States: A parametric analysis of technology and policy tradeoffs

Here, we present a parametric analysis of factors that can influence advanced fuel and technology deployments in U.S. Class 7–8 trucks through 2050. The analysis focuses on the competition between traditional diesel trucks, natural gas vehicles (NGVs), and ultra-efficient powertrains. Underlying the study is a vehicle choice and stock model of the U.S. heavy-duty vehicle market. Moreover, the model is segmented by vehicle class, body type, powertrain, fleet size, and operational type. We find that conventional diesel trucks will dominate the market through 2050, but NGVs could have significant market penetration depending on key technological and economic uncertainties. Compressed natural gas trucks conducting urban trips in fleets that can support private infrastructure are economically viable now and will continue to gain market share. Ultra-efficient diesel trucks, exemplified by the U.S. Department of Energy's SuperTruck program, are the preferred alternative in the long haul segment, but could compete with liquefied natural gas (LNG) trucks if the fuel price differential between LNG and diesel increases. However, the greatest impact in reducing petroleum consumption and pollutant emissions is had by investing in efficiency technologies that benefit all powertrains, especially the conventional diesels that comprise the majority of the stock, instead of incentivizing specific alternatives.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2018

Residual value analysis of plug-in vehicles in the United States

Knowledge about the value of used plug-in electric vehicles (PEVs), known as residual value, is critical for potential PEV purchasers, corporations, and governments who wish to consider the lifetime cost effectiveness of PEVs. In this study, we investigate the residual values of PEVs and compare them with those of other vehicle powertrain technologies using the “true market value” data from Edmunds.com, and considering U.S. federal incentives. We define the adjusted retention rate as the ratio between resale value and the manufacturer’s suggested retail price, subtracting incentives. We develop statistical models to quantify the effects of powertrain technologies on residual value while controlling key factors, including vehicle size, brand, and market segments. We find that the long-range high-performance Tesla Model S holds value significantly better than any other vehicle type evaluated, including internal combustion engine vehicles. Hybrid electric vehicles and plugin hybrid electric vehicles are comparable to one another. They hold slightly less value than internal combustion engine vehicles, but significantly more than short-range (<125 miles) battery electric vehicles. However, short-range battery electric vehicles have a faster improvement in 3-year adjusted retention rate than any other powertrain technology from model year 2013–2014. Finally, the other factor that significantly influences adjusted retention rate is the home country of the vehicle manufacturer (e.g., United States, Japan, or Germany).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Microsimulation of Energy and Flow Effects from Optimal Automated Driving in Mixed Traffic

In this paper we study the energy and traffic impact of a proposed Anticipative Cruise Controller in a PTV VISSIM microsimulation environment. We dissect our controller into two parts: 1. the unconnected mode, active when following a human-driven vehicle, and 2. the connected mode, active when following another automated vehicle equipped with connectivity. Probabilistic constraints balance safety considerations with inter-vehicle compactness, and vehicle constraints for acceleration capabilities are expressed through the use of powertrain maps. Emergent highway traffic scenarios are then modeled using time headway distributions from empirical traffic data. To study the impact of automation over a range of demands of free-flow to stop-and-go, we vary vehicle flux from low to high and vary automated vehicle penetration from low to high. When examining all-human driving scenarios, network capacity failed to meet demand in high-volume scenarios, such as rush-hour traffic. We further find that with connected automated vehicles introduced, network capacity was improved to support the high-volume scenarios. Finally, we examine energy efficiencies of the fleet for conventional, electric, and hybrid vehicles. We find that automated vehicles perform at a 10%-20% higher energy efficiency over human drivers when considering conventional powertrains, and find that automated vehicles perform at a 3%-9% higher energy efficiency over human drivers when considering electric and hybrid powertrains. Due to secondary effects of smoothing traffic flow and reducing unnecessary braking, energy benefits also apply to human-driven vehicles that interact with automated ones. Such simulated humans were found to drive up to 10% more energy-efficiently than they did in the baseline all-human scenario.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

AutonomieAI: An efficient and deployable vehicle energy consumption estimation toolkit

Here, this paper presents AutonomieAI, a novel toolkit designed for efficient energy estimation of vehicles across diverse trip scenarios, routes, and drive cycles, applicable to a broad range of vehicle powertrain technologies. It leverages state-of-the-art Machine Learning techniques to deliver real-time energy prediction of vehicles, enabling co-simulation with transportation level system tools and opening doors for large-scale optimization at city, network or national level. Benchmark results show that AutonomieAI achieves high accuracy, with an average percentage error below 2% for most powertrain types, and computational efficiency capable of processing over 10,000 trips per second. Applications of AutonomieAI have potential to offer the flexibility to assist in solving eco-routing problems, optimize for vehicle and powertrain selection, study charging decision behavior, and optimize for charging station placement. AutonomieAI is the result of large neural network based model architectures, trained on very large and unique high fidelity vehicle simulation data. It is lightweight, deployable, efficient and has accuracy comparable to specialized and complex physics based simulation softwares.

Autonomie↗
DOE OSTI2024

Well‐to‐wheels analysis of greenhouse gas emissions for passenger vehicles in Middle East and North Africa

Battery electric vehicles (BEVs) are widely considered a pathway to achieve low carbon mobility. BEVs emit zero emissions from the tailpipe, but their life cycle carbon reduction compared to gasoline vehicles varies based on primary energy sources, electricity generation, and use efficiency. The Middle East and North Africa (MENA) region is an area rich in fossil fuels, meriting a detailed comparison between the emissions from BEV and other powertrains. We developed a MENA‐specific life cycle model that estimates well‐to‐wheel (WTW) greenhouse gas (GHG) emissions from passenger transport with internal combustion engine vehicles (ICEVs), hybrid electric vehicles (HEVs), plug‐in hybrid electric vehicles, and BEVs. MENA's average WTW GHG emissions for all supply chain steps including combustion emissions from vehicle operation are 767 g/kWh and 84 g CO 2 eq/MJ for electricity and gasoline, respectively, but are highly variable due to heterogeneity in upstream supply chains. The use of hybrid gasoline ICEVs provides the largest emission reduction opportunity for existing vehicle fleets in 9 of the 16 MENA countries. For these nine countries, replacing gasoline ICEVs with HEVs could, on average, reduce country‐level life cycle GHG emissions by 47%. There is a similar emission reduction opportunity for 14 of the 16 MENA countries when normalizing vehicle efficiencies irrespective of the powertrain shares and other trends in existing vehicle fleets. Future scenario analysis shows that BEVs would have the lowest WTW GHG emissions among all powertrains in most MENA countries only if significantly reduced electricity transmission losses and cleaner grid mix are realized, although a high cost of infrastructure developments is expected.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

FASTSim™ (Future Automotive Systems Technology Simulator) [SWR-20-101 and SWR-12-07]

The Future Automotive Systems Technology Simulator (FASTSim™) provides a simple way to compare powertrains and estimate the impact of technology improvements on light-, medium-, and heavy-duty vehicle efficiency, performance, cost, and battery life. This extremely fast simulation tool features a streamlined user interface and can rapidly perform a variety of tasks using basic computing resources: • less than 0.1 second to simulate second-by-second standard duty cycles • less than 10 seconds to estimate vehicle efficiency, fuel economy, acceleration, battery life, and cost • less than 5 minutes to perform powertrain comparisons of efficiency and cost. FASTSim models a variety of vehicle powertrains and fuel converter types: • Conventional vehicles - spark ignition, Atkinson, diesel, and hybrid diesel • Electric-drive vehicles - hybrid, plug-in hybrid, and all-electric • Hydrogen fuel cell vehicles. The default model includes a variety of vehicles and duty cycles and an option for adding additional vehicles and custom cycles: • Packaged with more than 20 vehicles • User interface enables addition of more vehicles • Includes standard U.S. drive cycles as well as European and Japanese cycles. FASTSim is available for download in Microsoft Excel and Python formats here: https://www.nrel.gov/transportation/fastsim.html

Baker, Chad↗
DOE OSTI2024

T3CO (Transportation Technology Total Cost of Ownership) Open Source [SWR-21-54]

T3CO (Transportation Technology Total Cost of Ownership), is open source software for modeling total cost of ownership for commercial vehicles with advanced powertrains. T3CO is a modeling framework for determining geospatially and temporally optimized total cost of ownership (TCO) for vehicle powertrain technologies. T3CO runs NREL's FASTSim™ software for a representative set of operating conditions to minimize TCO based on vehicle parameters that affect purchase and operating costs (e.g., fuel/electricity consumption, asset depreciation, opportunity costs associated with charging time) while simultaneously ensuring that firm performance constraints (e.g. zero-to-sixty time, gradeability) are satisfied. T3CO will enable the user to control which powertrain parameters are used in optimizing TCO, and these parameters will be modified by a multi-objective optimization (MOO) algorithm to identify a Pareto-optimal solution set. The optimization algorithm will be modular so that users can choose from many different MOO options or insert their own user-defined optimization tool. NREL T3CO Homepage: https://www.nrel.gov/transportation/t3co.html PyPI package: https://pypi.org/project/t3co/

Lustbader, Jason↗