Search NASA⌕ Search

SEARCH · Search NASA

Results for “Propulsion System Models”

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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Electrifying Education: Insights into Charging Electric School Buses in the United States

To combat climate change, the United States joined 193 Parties in committing to the Paris Agreement, which aims to limit global warming to 2 degrees C or less, and decarbonizing transportation will be a key requirement for achieving this goal. School buses (SBs) are a common form of student transport in the U.S. with nearly all SBs today powered by fossil fuels (primarily diesel). As a result, SBs have historically been a concerning source of both greenhouse gas (GHG) emissions and local air pollutants with negative health impacts for students and others living nearby. Electric SBs (ESBs) are a promising emerging technology for decarbonizing student transport, however, ESB adoption in the U.S. remains at an early stage (approximate 1.1%) with many outstanding uncertainties. This study aims to elucidate several of these by taking inventory of the total SB stock within U.S. states and studying real-world SB operating profiles to infer potential battery range requirements, daily charging opportunities, and charging infrastructure requirements for ESBs. In addition, we observe the geographic trends of early-stage ESB adoption, which can be used to better understand early adopter patterns and train vehicle technology adoption models.

ADVANCED PROPULSION SYSTEMS,ENERGY PLANNING, POLIC↗
DOE OSTI2024

In-cylinder spray evolution in a motored central-injection gasoline engine: Imaging and simulating the effects of flash-boiling and intake crossflow

Accurate predictions of fuel spray behavior and mixture formation in simulations of direct-injection spark-ignition (DISI) engines are fundamental to ensure proper description of all subsequent processes including ignition, combustion, and emissions. In this work, the spray evolution in a single-cylinder optical DISI engine was studied experimentally and numerically with the goal of enabling predictive computational fluid dynamics (CFD) modeling of in-cylinder sprays. The authors explored a wide range of operating conditions characterized by several fuel injection temperatures and engine speeds, using a well-characterized nine-component gasoline surrogate known as PACE-20. The effect of flash boiling and intake crossflow on the spray is discussed, with a focus on evaluating the ability of the spray models to capture highly transient spray behavior. In the experiments, the fuel temperature was varied between 20°C and 80°C, allowing for non-flash- to flash-boiling transition to emerge with enhanced flashing intensity at the highest temperatures. Spray collapse resulted in vapor-rich regions, owing to the locally lower inertia of the fluid. Varying the engine speed from 650 to 1950 rpm promoted increasingly more turbulent in-cylinder crossflow which interacted with the spray during the injection event and resulted in enhanced spray dispersion. The CFD model was able to capture the spray morphology transition at different fuel temperatures and engine speeds adequately. Further, it is shown that the spray breakup model could capture the transitional spray behavior induced by flash boiling atomization and intake flow via proper initialization of the spray cone angle and calibration of the spray models’ constants.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2020

Spray Combustion and Soot Formation

Mitigating particulate matter (PM) emissions while simultaneously controlling nitrogen oxide and hydrocarbon emissions is critical for both gasoline and diesel engines. The problem is especially critical during cold-start cycles where aftertreatment devices are less effective. Understanding how liquid sprays and films form PM and designing to change the outcome requires advanced combustion concepts developed through joint experimental and computational efforts. However, existing spray and soot computational models are oversimplified and non-physical, and are therefore unable to reliably capture quantitative or even qualitative trends over a wide range of engine operating conditions. This task involves the development and application of advanced optical diagnostics and high-pressure gas and particle sampling/analysis in unique high-temperature, high-pressure vessels to investigate spray dynamics and soot formation with the objective of providing fundamental understanding about soot processes under relevant engine conditions to aid the development of improved soot models for commercial CFD codes

02 PETROLEUM↗
DOE OSTI2023

Optimizing Hydrogen Fueling Infrastructure Plans on Freight Corridors for Heavy-Duty Fuel Cell Electric Vehicles

The development of a future hydrogen energy economy will require the development of several hydrogen market and industry segments including a hydrogen-based commercial freight transportation ecosystem. For a sustainable freight transportation ecosystem, the supporting fueling infrastructure and the associated vehicle powertrains making use of hydrogen fuel will need to be co-established. This article introduces the OR-AGENT (Optimal Regional Architecture Generation for Electrified National Transportation) tool developed at the Oak Ridge National Laboratory, which has been used to optimize the hydrogen refueling infrastructure requirements on the I-75 corridor for heavy-duty (HD) fuel cell electric commercial vehicles (FCEV). This constraint-based optimization model considers existing fueling locations, regional-specific vehicle fuel economy and weight, vehicle origin and destination (O-D), and vehicle volume by class and infrastructure costs to characterize in-mission refueling requirements for a given freight corridor. The authors applied this framework to determine the ideal public access locations for hydrogen refueling (constrained by existing fueling stations), the minimal viable cost to deploy sufficient hydrogen fuel dispensers, and associated equipment, to accommodate a growing population of hydrogen fuel cell trucks. The framework discussed in this article can be expanded and applied to a larger interstate system, expanded regional corridor, or other transportation network. This article is the third in a series of papers that defined the model development to optimize a national hydrogen refueling infrastructure ecosystem for HD commercial vehicles.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

LLNL FESP Theory Highlights: November 2024

This talk presented a refined understanding of plasma-facing thermionic emitter cathodes by examining the limitations of the conventional space charge-limited model, which overlooks ion trapping dynamics within the virtual cathode. While conventional theory distinguishes between temperature-limited and space charge-limited regimes based on electron current constraints, recent findings reveal that trapped ions can form a quasi-neutral "second plasma," expanding upstream and interacting with the primary plasma. These effects are amplified in non-planar geometries, such as cylindrical or spherical sheaths, where trapped ions create a positive feedback loop with the upstream plasma. To address these phenomena, a new "Aid-and-Compete" model was developed, offering insights into current enhancement and sheath mode transitions relevant for plasma devices, including emissive cathodes in electric propulsion, fusion applications, thin film deposition systems, and plasma diagnostics.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Development of an Optimized Gasoline Surrogate Formulation for PACE Experiments and Simulations

New powertrain solutions are needed to address societal challenges stemming in part from a transportation sector which relies heavily on combustion of conventional hydrocarbon fuels like gasoline. One way to advance new solutions is through predictive simulations. Predictive simulations can potentially limit the extent of experimental validations, reduce time spent in engineering design cycles, unlock new strategies for high efficiency combustion with power density, and minimize tailpipe emissions. However, the simulation tools currently available are either too computationally expensive, inadequate in their accuracy, or a combination of the two. A DOE-funded consortium of national laboratories called the Partnership to Advance Combustion Engines (PACE) seeks to address this gap by rapidly delivering new knowledge and tools which enable market-competitive powertrain solutions for light-duty vehicles. Approaches to modeling combustion in powertrain systems typically incorporate computational fluid dynamics (CFD) simulations with chemical kinetic models. These CFD simulations generally use surrogate fuels featuring a limited number of existing components in a reduced kinetic model to limit computational costs. Such surrogate fuels often sacrifice matching several or more combustion and physical properties of the target gasoline fuel. Validation of surrogate fuels is also often only pursued for a small subset of standard metrics such as research or motor octane number (RON, MON). The purpose of this project is to develop an optimal E10 gasoline surrogate fuel suitable for tasks across PACE to facilitate rapid common analysis and progression toward consortium goals. This project received contributions from tasks led by eight PACE principal investigators. The project funding here reflects all tasks under Pitz, whose tasks also contributed to additional PACE projects. Based on the optimal gasoline surrogate fuel composition, a reduced chemical kinetic model will be shared with PACE researchers, industry, and the broader combustion community.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

Economic analysis of the benefits to petroleum refiners for low carbon boosted spark ignition biofuels

A refinery modeling framework is developed to estimate the benefits of blending high-quality biofuels directly with refinery gasoline components for attaining a premium grade fuel (also termed as Co-Optima Boosted SI gasoline here). Our results change the paradigm of bio-blendstocks (BBs) being competitors to fossil components, by identifying opportunities for refineries to add value to their product slate, from some favorable BB properties. This potential value can be characterized by calculating the breakeven value (BEV), as defined down below. The proposed modeling framework incorporates extensive data from (1) projected product over the next few decades, (2) crude oil and refinery products pricing, and (3) fuel specifications. The complete refinery models serve as a basis for assessing the value of biofuels, assuming profitability remains the same for representative petroleum refinery configurations. Our assessment showed wide range of variation of biofuels BEV from $\$$20-$\$$120/bbl, within the considered blending level and crude prices. Further, the BEV was correlated with the fuel octane ratings such as octane numbers (research, RON and motor octane numbers, MON) and both antiknock index (AKI, average of RON and MON) and sensitivity (S, difference between RON and MON), with a slightly higher correlation with the sensitivity. However, the expected decrease in gasoline demand for the upcoming years could negatively impact biofuels demand and value, in a business-as-usual scenario. Our analysis also showed a more valuable bio-blendstocks incorporation in smaller refineries since they can enhance the capabilities for producing specialty, high-value fuels/products, and introduce high octane-barrels into otherwise constrained blending operations. Additional implications towards refiners include opportunities to rebalance operations, access to high-value fuel markets, and synchronization with broader transportation industry trends. Furthermore, results indicate the value of Co-Optima boosted spark ignition (BSI) efficiency gains can extend to refiners to incentivize decarbonization and diversified feedstock production.

09 BIOMASS FUELS↗
DOE OSTI2026

BEAM CORE: A Flexible Ecosystem for Freight, Demographics, and Vehicle Analysis

The Behavior, Energy, Autonomy, and Mobility Comprehensive Regional Evaluator (BEAM CORE) is an open-source, modular ecosystem of highly refined, agent-based modeling tools developed by Lawrence Berkeley National Laboratory and the National Laboratory of the Rockies. Organizations such as metropolitan planning organizations, agencies, and companies can use BEAM CORE to analyze freight movement and optimize logistics solutions, assess the impacts of emerging freight technologies or e-commerce trends, model dynamic population growth and evolution, and understand the drivers and impacts of electric vehicle adoption across households in a given region. Users can choose from a flexible suite of modeling modules according to their needs and priorities. The modules integrate with travel demand models to support enhanced analysis of diverse scenarios involving freight movement, vehicle technologies, and other key factors relevant to regional planning.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

Electric Vehicles Charging Time Constrained Deliverable Provision of Secondary Frequency Regulation

Aggregation of electric vehicles (EVs) is a promising technique for providing secondary frequency regulation (SFR) in highly renewable energy-penetrated power systems. Equipped with energy storage devices, EV aggregation can provide reliable SFR. However, the main challenge is to guarantee reliable intra-interval SFR capacities and inter-interval delivery following the automatic generation control (AGC) signal. Furthermore, aggregated EV SFR provision will be further complicated by the EV charging time anxiety because SFR provision might extend EV's charging time. This paper proposes a deliverable EV SFR provision with a charging-time-constrained control strategy. First, a charging-time-constrained EV aggregation is proposed to address the uncertainty of EV capacity based on the state-space model considering the charging-time restriction of EV owners. Second, a real-time economic dispatch and time domain simulation (RTED-TDS) cosimulation framework is proposed to verify financial results and the dynamic performance of the EV SFR provision. Last, the proposed charging time-constrained EV aggregation is validated on the IEEE 39-bus system. In conclusion, the results demonstrate that with charging time-constrained EV aggregation, the dynamic performance of the system can be improved with a marginal increase in total cost. More importantly, the charging time constraint can be respected in the proposed SFR provision of the EV aggregation.

24 POWER TRANSMISSION AND DISTRIBUTION↗
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↗
DOE OSTI2023

Electric Vehicle Lithium-Ion Battery Life Cycle Management

There is no question that electric vehicles (EVs), which are key for addressing climate change impacts from the transportation sector, are quickly gaining popularity and availability. With limits and other challenges related to the supply of critical battery minerals, maximizing the use of EV batteries and ensuring recovery of battery minerals is imperative. Therefore, proper end-of-life-cycle management (reuse and recycling) of these batteries must be part of the EV ecosystem from the perspective of both the supply chain and environmental footprint. Second use of batteries for energy storage systems extends the initial life of these resources and provides a buffer until economical material recovery facilities are in place. Although there are multiple pathways to recycling and recovery of materials, new recovery technologies are moving toward commercially available hydrometallurgy and promising direct recycling, which analysis has shown has the lowest overall carbon footprint. Strategically locating these plants close to battery collection further reduces transportation and thus recycling and recovering costs. Proper life cycle management could alleviate future lithium-ion battery materials supply chains for EVs. Governments and other stakeholders around the world have started initiatives and proposed regulations to address the challenges associated with life cycle management of EV lithium batteries. Finally, as manufacturers are increasingly faced with the likelihood of such extensive regulatory requirements, attention should be given to new designs, sales, and service models that can reduce life cycle management costs.

25 ENERGY STORAGE↗
DOE OSTI2024

TCO Analysis Approach and Regional Analysis of dWPT for Class 8 Tractors

Dynamic Wireless Power Transfer (dWPT) is a method by which battery electric vehicles (BEVs) can charge their battery while traveling on the road without the need for a physical conductive connection to the power source. dWPT has been proposed as a strategy to enable a reduction in vehicle battery capacity and associated mass and cost. In this slide deck presented at the EVs@Scale Consortium - Wireless Power Transfer Pillar Deep-Dive Meeting on November 11th, 2023, NREL provides results from an evaluation of dWPT using data from Class 8 tractors driving in the Atlanta Metro Area. NREL selected data for archetypal days representing local, regional, and long-haul trips, defined according to trip length, that included travel on primary roadways. EVI-InMotion (Electric Vehicle Infrastructure - InMotion), a systems planning and optimization tool developed at NREL, was used to evaluate dWPT performance assuming dWPT charging on 120 road segments for a total roadway lane distance of 2,365 miles. The EVI-InMotion results and representative day drive cycles were analyzed with NREL's T3CO (Transportation Technology Total Cost of Ownership) tool to estimate the total cost of ownership (TCO) for scenarios comprising two model years - 2030 and 2040 - and two technology progress cases. TCO was calculated for diesel, fuel cell electric, BEVs with batteries sized assuming no dWPT capabilities, and 200kWh BEVs with dWPT installed. This analysis finds that en-route stationary charging frequency and downtime when not on electrified roadways are the main contributors to TCO for the dWPT vehicles and that these vehicles can achieve cost parity with FCEVs at low electricity costs. Based on the scenario assumptions used here, low electricity costs would further help the cost parity with diesel vehicles in regional and long-haul cases due to stationary fueling downtime. This presentation also concludes that key factors affecting the parity potential of dWPT-capable vehicles include more extensive dWPT road coverage, higher en-route charging power, less expensive power batteries, and higher hydrogen or diesel fuel costs.

ADVANCED PROPULSION SYSTEMS,ENERGY PLANNING, POLIC↗
DOE OSTI2026

Development of Machine-Learned Interatomic Potentials to Predict Structure, Transport, and Reactivity in Platinum-Based Fuel Cells

Machine-learned interatomic potentials (MLIPs) have rapidly progressed in accuracy, speed, and data efficiency in recent years. However, training robust MLIPs in multicomponent systems remains a challenge. In this work, we train an MLIP to describe hydrated Nafion ionomers and platinum catalysts, which are important components of fuel cells, by constructing a diverse training set to describe the bulk polymer and interfacial catalyst–polymer interactions well. We use our trained MLIP to study the properties of the platinum–Nafion system, including polymer structure, proton mobility in a bulk Nafion polymer and near a platinum-Nafion interface, and reactions near and far from the interface, finding excellent results for structure and reactions contained within our training set. Transport seems to be well described, with both vehicular transport and Grotthuss hopping captured, although converged calculations of diffusivities were not computed because they require calculations of tens of nanoseconds that are challenging with current state-of-the-art MLIPs. The combined insights that this model provides can be leveraged to optimize fuel cell performance, and the approach can be applied to other chemical processes and devices where structure, transport, and reactivity all contribute to the overall observed performance.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2025

Heat Pipe Enhanced Thermal Management System for GaN Switches in an Integrated Modular Motor Drive for Aircraft Propulsion

This paper presents the process of sizing a heat pipe enhanced thermal management system (TMS) for GaN switches in an integrated modular motor drive (IMMD) powering a 250 kW aircraft propulsion electric motor. A test setup mimicking the TMS and GaN switches assembly is constructed. The condenser chamber of the TMS is modeled in ANSYS Fluent while the GaN switches assembly is modeled in ANSYS Thermal allowing us to verify heat spreader temperature under test conditions and estimate GaN temperatures under test and actual application operating conditions.

DIRECT ENERGY CONVERSION↗
DOE OSTI2022

Control Design for a Marine Hydrokinetic Cycloturbine Vehicle

Abstract Marine Hydrokinetic (MHK) cycloturbines generate sustainable power by exploiting tidal currents. By powering the turbines and using pitching foils for control, a vehicle comprised of MHK cycloturbines also has the ability to station keep and maneuver. The vehicle consists of four counter-rotating cycloturbines, with hydrofoils oriented perpendicular to the flow in a paddlewheel configuration. Lift and drag generated from these foils sum together to produce thrust. An experimentally tuned simulation model that solves the six-degrees-of-freedom rigid body equations of motion for the MHK vehicle subject to hydrodynamic, hydrostatic, and propulsive forces is used to aid the design of vehicle controllers. Global feedback controllers are initially designed by applying classical control methods to an approximate linear model of the system dynamics. A higher performing nonlinear controller is designed using the nonlinear dynamic inversion (NDI) method. NDI accounts for the nonlinearities of the MHK system and therefore is suitable for a wide range of operating conditions. The response of the classical and NDI controllers to speed, depth, roll, pitch, and yaw commands are evaluated and compared in simulation. The classical controller outperforms the NDI controller for small amplitude maneuvers, although the degradation with NDI is minor. However, in the nonlinear operating regime the NDI controller outperforms the classical controller and the classical controller exhibits instability.

Automation & Control Systems↗
DOE OSTI2024

Tutorial - Electric Motor and Integrated Traction Drive Thermal Management

The share of vehicles with fully electric propulsion systems is constantly increasing, and so is their traction drive power. The continuous push to increase power of electric vehicle (EV) traction drives necessitates their efficient cooling to prevent damage to temperature sensitive components of the drive system and achieving higher power outputs in a smaller footprint. With increasing power and power density of electric traction drives, their thermal management is becoming increasingly challenging. This tutorial will provide an overview of thermal management approaches for electric motors and power electronics in EV applications. It will review examples of current industry solutions for power-dense electric motor cooling, power electronics (inverter) cooling, their integration concepts and thermal management system solutions. We'll look at the advantages and challenges of power electronics integration into a single traction drive unit and respective thermal management system concepts. We'll talk about barriers to implementation of a unified thermal management system. The tutorial will also review key aspects of thermal management system design: modeling and simulation using FEA and CFD tools, experimental characterization, and general workflow for thermal management system evaluation.

ADVANCED PROPULSION SYSTEMS,DIRECT ENERGY CONVERSI↗
DOE OSTI2023

Deep generative models for vehicle speed trajectories

Generating realistic vehicle speed trajectories is a crucial component in evaluating vehicle fuel economy and in predictive control of self-driving cars. Traditional generative models rely on Markov chain methods and can produce accurate synthetic trajectories but are subject to the curse of dimensionality. They do not allow to include conditional input variables into the generation process. In this paper, we show how extensions to deep generative models allow accurate and scalable generation. Proposed architectures involve recurrent and feed-forward layers and are trained using adversarial techniques. Our models are shown to perform well on generating vehicle trajectories using a model trained on GPS data from Chicago metropolitan area.

33 ADVANCED PROPULSION SYSTEMS↗