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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 91 records · Page 5

Do automated vehicle (AV) enthusiasts value travel time differently from cautious travelers? an exploration of travelers’ attitudes towards AV

The anticipation of automated vehicles (AV) has resulted in diverse research topics, including understanding the adoption and usage of this emerging mode. Using attitudinal indicators, this paper identifies prevalent types of attitudes towards AV. It then explores the variation of those attitudes across different demographic groups and quantifies the influence of these attitudes on the preference for AV. The paper uses stated preference survey data collected among respondents of Chicago in 2019. The exploratory factor analysis of the attitudinal indicators identifies four factors, namely 'Cautious Travelers', 'Hedonists', 'Utilitarians', and 'Safety-First'. Next, the paper develops an integrated choice and latent variable model to test the influence of these four types of attitudes on the preference for AV. Finally, the results indicate that the cautious travelers associate higher Value of Travel Time (VOTT) to AV and enthusiasts associate lower VOTT to AV than a base model without such attitudes.

33 ADVANCED PROPULSION SYSTEMS↗

Multiphysics Modeling of Hydrokinetic Turbine Energy Conversion System

Hydrokinetic turbines (HKTs) hold great promise as a renewable energy source, but high maintenance costs and limited energy output hinder their widespread adoption. The lack of comprehensive research on HKT drivetrain designs creates a knowledge gap in enhancing generation efficiency and cost reduction. A model of the HKT system with a focus on electric drivetrains and power converters is required to address this knowledge gap. This paper first introduces a MATLAB-averaged model integrating electrical-mechanical-thermal domains and aging behaviors within multi-time frames. Then a PLECS model, which incorporates maximum power point tracking and dq reference framed control for AC-DC-AC power converters, is enriched by a dynamic thermal model to predict fast transients accurately. These models optimize the design at the component level, resulting in improved integrated system performance. Furthermore, the validation of the models is carried out through hardware experiments for the averaged model and hardware-in-the-loop testing for the dynamic model.

ADVANCED PROPULSION SYSTEMS,HYDRO ENERGY↗

Development of in-use engine speed/torque heat maps across multiple heavy-duty commercial vehicle vocations

The U.S. Department of Energy (DOE) established the SuperTruck program with the goal of achieving brake thermal efficiency (BTE) greater than or equal to 55% as demonstrated in an operational heavy-duty (HD) diesel engine at a 65-miles-per-hour (mph) cruise point. Beyond the line-haul application, HD engines operate in a wide range of speed and torque conditions that are unlikely to yield the same efficiency under real-world operation. Thereby, the in-use engine heat maps described in this paper are a valuable tool to illustrate whether the engine-efficiency “sweet spot” matches the most frequent operating conditions. In this study, NREL developed engine heat maps to quantify the important operating points for various vocations using our Fleet DNA database of commercial fleet vehicle operations data. These heat maps clearly show that high-frequency operating points vary significantly according to vehicle vocation, while only a few of them match the sweet spot. Beyond the illustration, engine in-use heat maps can also be leveraged to build up reduced-order engine-efficiency models, needed by many rapid powertrain simulations. As case studies, nine reduced-order models – including line-haul truck, transfer truck, transit bus, transit bus with compressed natural gas (CNG) engine, drayage, refuse pickup, local delivery, utility truck, and school bus with CNG engine – using a trust-region reflective algorithm to fit the on-road data extracted based on the engine in-use heat maps.

33 ADVANCED PROPULSION SYSTEMS↗

Physics model validation of propane and methane for Hydrogen Plus Other Alternative Fuels Risk Assessment Models (HyRAM+)

HyRAM+ is a toolkit that includes fast-running models for the unconstrained (i.e., no wall interactions) dispersion and flames for non-premixed fuels. The models were developed for use with hydrogen, but the toolkit was expanded to include propane and methane in a recent release. Here, in this work we validate the dispersion and flame models for these additional fuels, based on reported literature data. The validation efforts spanned a range of release conditions, from subsonic to underexpanded jets and flames for a range of mass flow rates. In general, the dispersion model works well for both propane and methane although the width of the jet/plume is predicted to be wider than observed in some cases. The flame model tends to over-predict the induced buoyancy for low-momentum flames, while the radiative heat flux agrees with the experimental data reasonably well, for both fuels. The models could be improved but give acceptable predictions for propane and methane behavior for the purposes of risk assessment.

33 ADVANCED PROPULSION SYSTEMS↗

Spatial and unobserved heterogeneity in consumer preferences for adoption of electric and hybrid vehicles: A Bayesian hierarchical modeling approach

The transition to low carbon vehicles known as alternative fuel vehicles (AFVs) is well underway. This transition has been motivated partly by consumer demand and partly by legislation such as the Zero Emission Vehicle mandate, which requires manufacturers to sell a certain percentage of their vehicles as AFVs. While the long-term adoption of AFVs (specifically, electric and hybrids) may take several years, there is a need to understand consumer preferences for AFV adoption and the pathways of AFV adoption from a national perspective. Therefore, this study sought to provide information about consumer preferences regarding AFV ownership while considering spatial and unobserved heterogeneity in consumer preferences, which can potentially impact societal transition to low carbon fueled vehicles. The 2017 National Household Travel Survey was used to calibrate Bayesian logit and hierarchical models. Here, the findings of these models reveal that higher gasoline prices contribute toward the adoption of battery electric vehicles. The results also reveal that the perceived disadvantages of AFVs for long commutes are the key barrier in wider adoption of AFVs. Interestingly, frequent use of the internet by consumers revealed a higher likelihood for purchase of hybrid vehicles. Furthermore, West Coast residents are observed to be a large portion of the early adopters and are more likely to purchase hybrids as compared to battery electric vehicles. The knowledge generated by this study has implications for making better informed decisions about AFV adoption and developing incentives to promote wider adoption of AFVs by overcoming their perceived disadvantages.

33 ADVANCED PROPULSION SYSTEMS↗

Colorado Alternatively Powered Aircraft Airport Infrastructure Study

Advanced Air Mobility encompasses emerging technologies in propulsion of general aviation and commuter aircraft for the purpose of moving passengers and goods. The State of Colorado has a strong aerospace and aviation legacy, and this research explores the potential energy implications of a transition from traditional aircraft propulsion systems to more-electric, full electric and hydrogen powered aircraft in flight schools, and small community air service utilizing NASA's Regional Air Mobility Model. Effort includes identifying potential energy needs and cost-effective solutions to support those emerging needs analyzing potential benefits on on-site generation and storage to optimize energy systems.Advanced Air Mobility encompasses emerging technologies in propulsion of general aviation and commuter aircraft for the purpose of moving passengers and goods. The State of Colorado has a strong aerospace and aviation legacy, and this research explores the potential energy implications of a transition from traditional aircraft propulsion systems to more-electric, full electric and hydrogen powered aircraft in flight schools, and small community air service utilizing NASA's Regional Air Mobility Model. Effort includes identifying potential energy needs and cost-effective solutions to support those emerging needs analyzing potential benefits on on-site generation and storage to optimize energy systems.

33 ADVANCED PROPULSION SYSTEMS↗

Automated Control for Nuclear Thermal Propulsion Start-Up using MOOSE-based Applications

This report presents a Griffin/Bison/RELAP-7 numerical model of a prototypical NTP system that features fuel assemblies arranged in rings, and which was designed to simulate rapid startup transients. The physics modeled include full-core neutronics, assembly-wise heat conduction, and conjugate heat transfer, with the balance of plant mainly imposed through boundary conditions. In addition, various forms of automated reactivity control were deployed by using the MOOSE to autonomously drive the model and simulate the reactor transitioning from assumed initial conditions to nominal power in a fraction of a minute. To generate the cross-sections of the neutronics model, and in an effort to simultaneously account for the tremendous axial temperature gradients in the reactor and to limit the number of state points required for cross-section generation, the average component temperatures and hydrogen densities in the cooling channels were correlated to the average fuel and moderator temperatures, and fixed axial profiles were derived for nominal conditions and then used during the transient. With this approximation, a tractable cross-section library tabulated with fuel/moderator temperatures and CD angles was generated using Serpent. The full-core SPH correction procedure and the CD decusping technology in Griffin, respectively, ensure preservation of the multiplication factor and reaction rates at state points, along with a reasonably accurate reactivity worth between tabulated CD angles, despite using a coarse mesh. Feedback from other physics was calculated by modeling one representative fuel assembly per ring, along with the corresponding fuel and moderator cooling channels. To limit power overshoots during startup, another layer of multiphysics coupling was added to the model in order to automatically control the drums. Two different technologies presented herein showed outstanding performance in this regard: (1) a novel hybrid PID controller based on both power and reactivity signals, and (2) a PGC that relies on kinetics parameters and reactivity coefficients to predict future behavior and adjust the desired signal accordingly. A challenging benchmark was devised, featuring a power demand curve that exponentially increases by a factor of 500 within 30 seconds, then levels out after that. Both control approaches create a simulated power curve that closely follows the power demand curve and limits power overshoots to 1% or less. While the former approach requires more tuning of the internal parameters, the latter requires additional knowledge of the reactivity feedback coefficients and rates of change of the corresponding variables, including fuel and moderator temperature, which could be difficult to dynamically measure for a real NTP system. Fortunately, some inaccuracy in these quantities will not drastically degrade the PGC performance. Subsequently, a more realistic startup sequence was considered, in which the mass flow rate and outlet pressures are ramped up to model bootstrap and thrust build-up phases prior to reaching steady-state conditions, demonstrating the ability of the hybrid PID and PGCs to handle such transients, with both types of controllers exhibiting very similar behavior. Nevertheless, a significant chamber temperature overshoot was observed, caused by the demanded power signal and assumed mass flow rate. This issue could be mitigated by deploying a reactor controller that follows the chamber temperature signal and actuates both the control valves and drums (rather than using a power signal based solely on the drums to control reactivity). Enhancement of the hydrogen fluid properties available in MOOSE, as well as a better understanding of prototypical initial conditions, are also needed to further enhance this startup model. Finally, a study was performed to model decay heat post-shutdown, and to prepare for extending this model to predict shutdown behavior and post-shutdown pulsed cooling requirements.

33 ADVANCED PROPULSION SYSTEMS↗

A drift kinetic model for the expander region of a magnetic mirror

Here, we present a drift kinetic model for the free expansion of a thermal plasma out of a magnetic nozzle. This problem relates to plasma space propulsion systems, natural environments such as the solar wind, and end losses from the expander region of mirror magnetically confined fusion concepts such as the gas dynamic trap. The model incorporates trapped and passing orbit types encountered in the mirror expander geometry and maps to an upstream thermal distribution. This boundary condition and quasineutrality require the generation of an ambipolar potential drop of ~5T e /e, forming a thermal barrier for the electrons. The model for the electron and ion velocity distributions and fluid moments is confirmed with data from a fully kinetic simulation. Finally, the model is extended to account for a population of fast sloshing ions arising from neutral beam heating within a magnetic mirror, again resulting in good agreement with a corresponding kinetic simulation.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Modeling Nuclear Thermal Propulsion Startup Transients

A poster for the 2021 intern poster session. This poster details the RELAP-7/Griffin model developed for transient simulations to compare the effects of startup sequencing on the propellant efficiency, startup time, and maximum core temperature of a nuclear thermal propulsion (NTP) system. The sequencing parameters under consideration in this study are the ramping rates of both reactivity insertion and hydrogen propellant mass flow rate. Recommendations are made regarding startup sequencing based on the results produced by this model.

33 ADVANCED PROPULSION SYSTEMS↗

Modeling strategy for progressive failure prediction in lithium-ion batteries under mechanical abuse

The prediction for the internal failure of lithium-ion batteries (LIBs) under external mechanical abuse loading remains a challenge for safe design. This paper systematically studies the modeling approach for progressive failure simulation and short-circuit prediction. Hemispherical indentation experiments are conducted on a battery specimen containing 5 representative sandwich (RS) layers to examine the deformation and progressive failure behavior of battery components. Three different models, viz, a high-fidelity detailed model, an intermediate homogenized model and a fully homogenized model, are developed and employed to simulate the progressive failure in a multi-layer battery specimen. The simulation results obtained using the three models all correlate well with experimental phenomena, capturing the overall stress-strain response and ultimate failure of the battery structure. The numerical results can help us understand the failure behavior and the mechanism for mechanical abuse-induced short circuit in LIBs. The feasibility of the three models for use in progressive failure prediction is compared by analyzing the capability of the models in predicting the critical failure events, the computational efficiency of the models, and the feasibility to implement coupled mechanical-electrochemical-thermal simulations. The results of this work provide useful insights on practical choices for the modeling strategy and safety design of LIBs under mechanical abuse conditions.

25 ENERGY STORAGE↗

Predictive model using artificial neural network to design phase change material-based ocean thermal energy harvesting systems for powering uncrewed underwater vehicles

Uncrewed Underwater Vehicles (UUVs) are a major beneficiary of the phase change material (PCM)-based ocean thermal energy harvesting technology for their mission needs. However, this technology relies on different parameters and energy conversion steps that could be critical to the general energy generation efficiency. Sea trials showed that the design performed lower than their laboratory design specifications. This underperformance results from different factors, mainly the UUV’s trajectory, travel time, underwater ocean currents, temperature fluctuations, and biofouling on the heat exchanger due to long term underwater operations. Therefore, there exists a need to continuously monitor the ambient energy harvesting system and predict system performance, for mission planning purposes. Two major parameters influencing the energy harvesting system include the final pressure inside the hydraulic energy storage vessel or accumulator, and the electrical load value. Here, this work focuses on the hydraulic to electric energy conversion system. Therefore, a combination of numerical model and experimental testing is used to develop a predictive model using artificial neural network using MATLAB. After validation with experimental testing, 1000 data samples obtained from the numerical model are used to train the ANN. Compared to the experimental results, the developed ANN model can predict in less than a second the designed benchtop system’s total efficiency with less than 15 percent maximum error range. This predictive model development represents a cost-effective way for optimization and a computational energy efficient mode aboard UUVs for mission planning for deployed UUVs using PCM-based ocean thermal energy harvesting technology.

30 DIRECT ENERGY CONVERSION↗

Scalable probabilistic estimates of electric vehicle charging given observed driver behavior

To prepare for rapid growth in global electric vehicle adoption, grid and policy planners depend on detailed forecasts of future charging demand. In this paper we propose a novel holistic, scalable, probabilistic framework to produce large-scale estimates of electric vehicle charging load for long-term planning that capture real drivers’ charging patterns. Our framework captures the uncertainty and stochasticity in charging demand by taking a graphical modeling approach. It has three core elements: driver groups, charging segment choices, and charging session time and energy requirements. The framework uses hierarchical clustering to group drivers by their charging histories, capturing their heterogeneous behaviors and preferences across different segments or types of charging. The framework uses probabilistic mixture models for each driver group’s sessions to identify the unique charging behaviors observed within each segment. We illustrate its application with a large data set from California, profiling the charging patterns and unique driver clusters it identifies. Using the model knobs representing drivers’ battery capacities, behavior, and segment access we present scenarios for California’s charging demand in 2030 with 8 million passenger electric vehicles. Peak charging demand ranged from 3.3 to 8.7 GW across scenarios. Furthermore, each was calculated in under 45 s on a laptop computer.

33 ADVANCED PROPULSION SYSTEMS↗

Advanced Power Electronics and Electric Machines

The advanced power electronics and electric machines (APEEM) research group at the National Renewable Energy Laboratory (NREL) has developed world-class experimental and modeling capabilities for designing and evaluating efficient and reliable power electronics and electric machines thermal management systems. They also design, fabricate and characterize advanced power electronics packaging, and are developing state-of-health monitoring techniques. These researchers deliver safe, reliable, high performing, power-dense components that allow seamless integration between renewable energy sources, electric transportation, and the grid, helping to make widespread electric vehicle (EV) adoption and greenhouse gas emissions reduction more feasible. This document outlines the group's major capabilities in the areas of power electronics; module development and characterization; thermal modeling and management; thermomechanical reliability analysis of devices, modules, inverters/converters, and electric machines; physics-of-failure-based reliability analysis; and microelectronics. It also overviews the group's state-of-the-art equipment for fluid-based thermal management; thermal measurement & characterization; thermomechanical reliability analysis; micro- and power electronics measurement & characterization; and prototype fabrication, as well as the group's world-class modeling and simulation capabilities.

advanced gate drivers↗

Predictive Battery Lifetime Modeling at the National Renewable Energy Laboratory

Overview of the development of algebraic battery lifetime modeling efforts within NREL's Electrochemical Energy Storage group within the Energy Conversion and Storage Systems Center. Traditional approaches to developing battery lifetime models are compared with a new methodology incorporating machine learning to autonomously identify parsimonious model equations.

ADVANCED PROPULSION SYSTEMS↗

Low Temperature Oxidation of Methylpropyl Ether

Ethers are potential high-performance fuels that can be produced from renewable carbon sources such as biomass, but their combustion properties are not clearly understood. The cetane numbers (CN) for ethers, a measure of autoignition tendency, can range from less than 10 to greater than 100, and predictive tools based upon the molecular structures are desirable in order to focus fuel development research. In this study, we used molecular modeling, chemical kinetic modeling, and experimental measurements to understand the important reactions that lead to the autoignition of methylpropyl ether (MPE), a model for ethers containing alkyl chains long enough for intramolecular hydrogen transfer. These reactions are known to be important in the autoignition of alkanes and ethers and we propose to investigate the relationship between alkyl and ether reaction pathways. A reaction mechanism for MPE was created using MIT's Reaction Mechanism Generator (RMG) and G4 quantum calculation results and models were tested using the ChemKin Pro suite of software. Results from atmospheric pressure, flow tube reactor experiments and rapid compression machine (RCM) experiments were used to test the kinetic model and suggest refinements.

33 ADVANCED PROPULSION SYSTEMS↗