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Results for “transient driving cycle modeling”

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 OSTI2019

MaLTESE: Large-Scale Simulation-Driven Machine Learning for Transient Driving Cycles

Optimal engine operation during a transient driving cycle is the key to achieving greater fuel economy, engine efficiency, and reduced emissions. In order to achieve continuously optimal engine operation, engine calibration methods use a combination of static correlations obtained from dynamometer tests for steady-state operating points and road and/or track performance data. As the parameter space of control variables, design variable constraints, and objective functions increases, the cost and duration for optimal calibration become prohibitively large. In order to reduce the number of dynamometer tests required for calibrating modern engines, a large-scale simulation-driven machine learning approach is presented in this work. A parallel, fast, robust, physics-based reduced-order engine simulator is used to obtain performance and emission characteristics of engines over a wide range of control parameters under various transient driving conditions (drive cycles). We scale the simulation up to 3,906 nodes of the Theta supercomputer at the Argonne Leadership Computing Facility to generate data required to train a machine learning model. The trained model is then used to predict various engine parameters of interest, and the results are compared with those predicted by the engine simulator. Our results show that a deepneural-network-based surrogate model achieves high accuracy: Pearson product-moment correlation values larger than 0.99 and mean absolute percentage error within 1.07% for various engine parameters such as exhaust temperature, exhaust pressure, nitric oxide, and engine torque. Once trained, the deep-neural-network-based surrogate model is fast for inference: it requires about 16 mu s for predicting the engine performance and emissions for a single design configuration compared with about 0.5 s per configuration with the engine simulator. Moreover, we demonstrate that transfer learning and retraining can be leveraged to incrementally retrain the surrogate model to cope with new configurations that fall outside the training data space.

deep learning↗
DOE OSTI2020

Global kinetic modeling of NH 3 -SCR with two sites of NH 3 storage on Cu-SSZ-13

A comprehensive selective catalytic reduction (SCR) model is developed to detail the global kinetic reactions in the catalyst which is involved in two type of sites for high- and low-temperature NH 3 adsorption/desorption, as well as a low temperature H 2 O storage. The model accounts for the formation of ammonium nitrate in fast SCR and the decomposition formation of ammonium nitrate in the absence of NO, and addresses N 2 O relative to NO and NO 2 reactions with NH 3 . The model has been validated against commercial Cu-SSZ-13 measurements of NH 3 inventory, NH 3 oxidation, NO oxidation, standard SCR, fast SCR and NO 2 SCR at both comprehensive steady-state and transient conditions. In addition, the application of the SCR model for emissions control over a transient drive cycle at cold start was demonstrated based on diesel oxidation catalyst (DOC) and SCR aftertreatment system for a passenger car. In conclusion, the results show that the SCR model can provide the detailed emissions estimations for steady-state and transient conditions, can assist with understanding the impact of the SCR reaction mechanism, and can assist with the design and optimization of SCR catalysts to develop innovative technologies for co-optimization of engine fuel economy and emissions control technologies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2012

Systems Modeling, Simulation and Material Operating Requirements for Chemical Hydride Based Hydrogen Storage

Research on ammonia borane (AB, NH3BH3) has shown it to be a promising material for chemical hydride based hydrogen storage. AB was selected by DOE's Hydrogen Storage Engineering Center of Excellence (HSECoE) as the initial chemical hydride of study because of its high hydrogen storage capacity (up to 19.6% by weight for the release of {approx}2.5 molar equivalents of hydrogen gas) and its stability under typical ambient conditions. A new systems concept based on augers, ballast tank, hydrogen heat exchanger and H2 burner was designed and implemented in simulation. In this design, the chemical hydride material was assumed to produce H2 on the augers itself, thus minimizing the size of ballast tank and reactor. One dimensional models based on conservation of mass, species and energy were used to predict important state variables such as reactant and product concentrations, temperatures of various components, flow rates, along with pressure, in various components of the storage system. Various subsystem components in the models were coded as C language S-functions and implemented in Matlab/Simulink environment. The control variable AB (or alane) flow rate was determined through a simple expression based on the ballast tank pressure, H2 demand from the fuel cell and hydrogen production from AB (or alane) in the reactor. System simulation results for solid AB, liquid AB and alane for both steady state and transient drive cycle cases indicate the usefulness of the model for further analysis and prototype development.

08 HYDROGEN↗
DOE OSTI2012

Chemical Hydrides for Hydrogen Storage in Fuel Cell Applications

Due to its high hydrogen storage capacity (up to 19.6% by weight for the release of 2.5 molar equivalents of hydrogen gas) and its stability under typical ambient conditions, ammonia borane (AB) is a promising material for chemical hydrogen storage for fuel cell applications in transportation sector. Several systems models for chemical hydride materials such as solid AB, liquid AB and alane were developed and evaluated at PNNL to determine an optimal configuration that would meet the 2010 and future DOE targets for hydrogen storage. This paper presents an overview of those systems models and discusses the simulation results for various transient drive cycle scenarios.

08 HYDROGEN↗
DOE OSTI2017

Performance Modeling of Materials-Based Hydrogen Storage Systems for Automotive Applications

One of the challenges of fuel cell vehicles is storage of the hydrogen fuel. In an effort to reduce the temperature and pressure limitations of storing neat hydrogen either as a high pressure gas or cryogenic liquid, material-based hydrogen storage is being developed. Hydrogen stored either as an adsorbent or as a chemical compound not only provides more reasonable pressures and temperatures but also improves the storage density of the hydrogen. Modeling tools have been developed as part of the U.S. Department of Energy's Hydrogen Storage Engineering Center of Excellence to assess the performance of these materials in light duty vehicle applications. The purpose of these modeling tools is to evaluate newly developed hydrogen storage materials and ensure that they meet customer expectations for driving range and performance before further investment. Recent advances in these modeling tools have been made to allow direct material property inputs. Such material properties as hydrogen capacity, isotherms and other thermodynamic and kinetic properties can reasonably be measured by materials researchers. Using these properties as inputs, the models can then provide estimates of the mass and volume of the storage system and the driving range and fuel efficiency of the vehicle during transient operation with four different drive cycles. The system sizing estimator and the framework model used to perform this analysis will be described and results presented for adsorbents and chemical based storage materials.

25 ENERGY STORAGE↗
DOE OSTI2017

The Development of Vocational Vehicle Drive Cycles and Segmentation

Under a collaborative interagency agreement between the U.S. Environmental Protection Agency and the U.S Department of Energy (DOE), the National Renewable Energy Laboratory (NREL) performed a series of in-depth analyses to characterize the on-road driving behavior including distributions of vehicle speed, idle time, accelerations and decelerations, and other driving metrics of medium- and heavy-duty vocational vehicles operating within the United States. As part of this effort, NREL researchers segmented U.S. medium- and heavy-duty vocational vehicle driving characteristics into three distinct operating groups or clusters using real world drive cycle data collected at 1 Hz and stored in NREL's Fleet DNA database. The Fleet DNA database contains millions of miles of historical real-world drive cycle data captured from medium- and heavy vehicles operating across the United States. The data encompass data from existing DOE activities as well as contributions from valued industry stakeholder participants. For this project, data captured from 913 unique vehicles comprising 16,250 days of operation were drawn from the Fleet DNA database and examined. The Fleet DNA data used as a source for this analysis has been collected from a total of 30 unique fleets/data providers operating across 22 unique geographic locations spread across the United States. This includes locations with topology ranging from the foothills of Denver, Colorado, to the flats of Miami, Florida. The range of fleets, geographic locations, and total number of vehicles analyzed ensures results that include the influence of these factors. While no analysis will be perfect without unlimited resources and data, it is the researchers understanding that the Fleet DNA database is the largest and most thorough publicly accessible vocational vehicle usage database currently in operation. This report includes an introduction to the Fleet DNA database and the data contained within, a presentation of the results of the statistical analysis performed by NREL, review of the logistic model developed to predict cluster membership, and a discussion and detailed summary of the development of the vocational drive cycle weights and representative transient drive cycles for testing and simulation. Additional discussion of known limitations and potential future work are also included in the report content.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

Comparison of the Accuracy and Speed of Transient Mobile A/C System Simulation Models: Preprint

The operation of air conditioning (A/C) systems is a significant contributor to the total amount of fuel used by light- and heavy-duty vehicles. Therefore, continued improvement of the efficiency of these mobile A/C systems is important. Numerical simulation has been used to reduce the system development time and to improve the electronic controls, but numerical models that include highly detailed physics run slower than desired for carrying out vehicle-focused drive cycle-based system optimization. Therefore, faster models are needed even if some accuracy is sacrificed. In this study, a validated model with highly detailed physics, the 'Fully-Detailed' model, and two models with different levels of simplification, the 'Quasi-Transient' and the 'Mapped- Component' models, are compared. The Quasi-Transient model applies some simplifications compared to the Fully-Detailed model to allow faster model execution speeds. The Mapped-Component model is similar to the Quasi-Transient model except instead of detailed flow and heat transfer calculations in the heat exchangers, it uses lookup tables created with the Quasi-Transient model. All three models are set up to represent the same physical A/C system and the same electronic controls. Speed and results of the three model versions are compared for steady state and transient operation. Steady state simulated data are also compared to measured data. The results show that the Quasi-Transient and Mapped-Component models ran much faster than the Fully-Detailed model, on the order of 10- and 100-fold, respectively. They also adequately approach the results of the Fully-Detailed model for steady-state operation, and for drive cycle-based efficiency predictions

02 PETROLEUM↗
DOE OSTI2026

High Voltage High Power Traction Inverter Thermal Management

This project develops thermal management solutions for various 530-kW inverter topologies being developed by Oak Ridge National Laboratory (ORNL). The thermal management solutions will provide high thermal performance and be designed to keep inverter components (e.g., power modules, capacitors) within allowable operating temperatures to help meet the project objectives. Steady-state and transient thermal models of the inverter and cooling system will be created and used to predict component temperatures under various drive cycle conditions.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2015

Suitability of Synthetic Driving Profiles from Traffic Micro-Simulation for Real-World Energy Analysis: Preprint

A shift towards increased levels of driving automation is generally expected to result in improved safety and traffic congestion outcomes. However, little empirical data exists to estimate the impact that automated driving could have on energy consumption and greenhouse gas emissions. In the absence of empirical data on differences between drive cycles from present day vehicles (primarily operated by humans) and future vehicles (partially or fully operated by computers) one approach is to model both situations over identical traffic conditions. Such an exercise requires traffic micro-simulation to not only accurately model vehicle operation under high levels of automation, but also (and potentially more challenging) vehicle operation under present day human drivers. This work seeks to quantify the ability of a commercial traffic micro-simulation program to accurately model real-world drive cycles in vehicles operated primarily by humans in terms of driving speed, acceleration, and simulated fuel economy. Synthetic profiles from models of freeway and arterial facilities near Atlanta, Georgia, are compared to empirical data collected from real-world drivers on the same facilities. Empirical and synthetic drive cycles are then simulated in a powertrain efficiency model to enable comparison on the basis of fuel economy. Synthetic profiles from traffic micro-simulation were found to exhibit low levels of transient behavior relative to the empirical data. Even with these differences, the synthetic and empirical data in this study agree well in terms of driving speed and simulated fuel economy. The differences in transient behavior between simulated and empirical data suggest that larger stochastic contributions in traffic micro-simulation (relative to those present in the traffic micro-simulation tool used in this study) are required to fully capture the arbitrary elements of human driving. Interestingly, the lack of stochastic contributions from models of human drivers in this study did not result in a significant discrepancy between fuel economy simulations based on synthetic and empirical data; a finding with implications on the potential energy efficiency gains of automated vehicle technology.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2020

Design tool for estimating metal hydride storage system characteristics for light-duty hydrogen fuel cell vehicles

The U.S. Department of Energy (DOE) has developed the Framework model to simulate fuel cell-based light-duty vehicle operation for various hydrogen storage systems. This transient model simulates the performance of the storage system, fuel cell, and vehicle for comparison to DOE's Technical Targets using four drive cycles. Metal hydride hydrogen storage models have been developed for the Framework model. Despite the utility of this model, it requires that material researchers input system design specifications that cannot be easily estimated. To confront this challenge, a design tool has been developed that allows researchers to directly enter physical and thermodynamic metal hydride properties into a simple sizing module that then estimates the systems parameters required to run the storage system model. This design tool can also be used as a standalone MS Excel model to estimate the storage system mass and volume outside of Framework and compare it to the DOE Technical Targets. This model will be explained and exercised with existing hydrogen storage materials.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2013

High Performance Computing Facility Operational Assessment, 2012 Oak Ridge Leadership Computing Facility

Oak Ridge National Laboratory’s Leadership Computing Facility (OLCF) continues to deliver the most powerful resources in the United States for open science. At 2.33 petaflops peak performance, the Cray XT Jaguar delivered more than 1.4 billion core hours in calendar year (CY) 2012 to researchers around the world for performing computational simulations relevant to national and energy security; advancing the frontiers of knowledge in physical sciences and areas of biological, medical, environmental, and computer sciences; and providing world-class research facilities for the nation’s science enterprise. OLCF users achieved numerous wide-ranging research accomplishments and technological innovations in 2012. It is not possible to fully summarize the breadth and impact of their productivity within this brief report—OLCF researchers published more than 300 research articles in 2012 alone. Here we identify selected accomplishments that advance the state of the art in science and engineering research and development. The work was recognized through peer-review publications in notable journals such as Science, Nature, and The Proceedings of the National Academy of Sciences (PNAS), among the many noted in this report. Exploration of the nuclear landscape carried out by Innovative and Novel Computational Impact on Theory and Experiment (INCITE) researchers and their theoretical prediction of isotopes were featured in Nature in 2012 (see Section 3.2.2). On the other end of the physical-scale spectrum, researchers executed a 22,000-year transient Earth System Model simulation that explained the misleading lag of carbon dioxide behind Antarctic temperature records and pointed to carbon dioxide’s role in driving global climate change over glacial cycles. This deglaciation study and related work by OLCF users were featured in Nature and PNAS in 2012 (see Section 3.2.3). Other representative achievements by OLCF users include generation of spectroscopic and photometric data for more accurate distance measurements, necessary for planning future National Science Foundation and Department of Energy (DOE) missions such as the Large Synoptic Survey Telescope and the Palomar Transient Factory; calculations to enable the experimental verification of Bose glass; and screening of 2 million compounds against a targeted receptor in a matter of days, as opposed to the months that would be required for computing clusters, creating a vast library of molecular compounds that can be used for future screenings of potential drug candidates. These and other accomplishments are described in Section 3.

OA↗
DOE OSTI2012

Cold-Start Emissions Control in Hybrid Vehicles Equipped with a Passive Hydrocarbon and NOx Adsorber

We presents a study of the potential for using low-cost sorbent materials (i.e. Ag-Beta-zeolite and Fe-Mn-Zr transition metal oxides) to temporally trap hydrocarbons (HCs) and nitrogen oxides (NOx) emissions during cold-start periods in HEVs and PHEVs over transient driving cycles. The adsorption behavior of the candidate sorbent materials was characterized in our laboratory flow reactor experiments. The parameters were then used to develop a one-dimensional, transient device model which has been implemented in the Powertrain Systems Analysis Toolkit (PSAT) to simulate a passive HC and NOx absorber device. The results show that such an absorber can substantially reduce HC and NOx emissions by storing them when the 3-way catalyst is too cool to function and re-releasing them when the exhaust temperature rises. These improved emission controls do not involve any penalty in fuel consumption or require any change in engine operation. The cost of these sorbent materials is also much less than conventional 3-way catalysts.

42 ENGINEERING↗
DOE OSTI2023

Comparative feedstock analysis in Setaria viridis L. as a model for C 4 bioenergy grasses and panicoid crop species

Second generation feedstocks for bioethanol will likely include a sizable proportion of perennial C4 grasses, principally in the Panicoideae clade. The Panicoideae contain agronomically important annual grasses including Zea mays L. (maize), Sorghum bicolor (L.) Moench (sorghum), and Saccharum officinarum L. (sugar cane) as well as promising second generation perennial feedstocks including Miscanthus × giganteus and Panicum virgatum L. (switchgrass). The underlying complexity of these polyploid grass genomes is a major limitation for their direct manipulation and thus driving a need for rapidly cycling comparative model. Setaria viridis (green millet) is a rapid cycling C4 panicoid grass with a relatively small and sequenced diploid genome and abundant seed production. Stable, transient, and protoplast transformation technologies have also been developed for Setaria viridis making it a potentially excellent model for other C4 bioenergy grasses. Here, the lignocellulosic feedstock composition, cellulose biosynthesis inhibitor response and saccharification dynamics of Setaria viridis are compared with the annual sorghum and maize and the perennial switchgrass bioenergy crops as a baseline study into the applicability for translational research. A genome-wide systematic investigation of the cellulose synthase-A genes was performed identifying eight candidate sequences. Two developmental stages; (a) metabolically active young tissue and (b) metabolically plateaued (mature) material are examined to compare biomass performance metrics.

09 BIOMASS FUELS↗
NASA NTRS1989

Modelling and measurement of crack closure and crack growth following overloads and underloads

Ignoring crack growth retardation following overloads can result in overly conservative life predictions in structures subjected to variable amplitude fatigue loading. Crack closure is believed to contribute to the crack growth retardation, although the specific closure mechanism is dabatable. The delay period and corresponding crack growth rate transients following overload and overload/underload cycles were systematically measured as a function of load ratio and overload magnitude. These responses are correlated in terms of the local 'driving force' for crack growth, i.e. the effective stress intensity factor range. Experimental results are compared with the predictions of a Dugdale-type (1960) crack closure model, and improvements in the model are suggested.

Dexter, R. J.↗
DOE OSTI2017

Transient dynamics of terrestrial carbon storage: Mathematical foundation and its applications

Terrestrial ecosystems have absorbed roughly 30% of anthropogenic CO 2 emissions over the past decades, but it is unclear whether this carbon (C) sink will endure into the future. Despite extensive modeling and experimental and observational studies, what fundamentally determines transient dynamics of terrestrial C storage under global change is still not very clear. Here we develop a new framework for understanding transient dynamics of terrestrial C storage through mathematical analysis and numerical experiments. Our analysis indicates that the ultimate force driving ecosystem C storage change is the C storage capacity, which is jointly determined by ecosystem C input (e.g., net primary production, NPP) and residence time. Since both C input and residence time vary with time, the C storage capacity is time-dependent and acts as a moving attractor that actual C storage chases. The rate of change in C storage is proportional to the C storage potential, which is the difference between the current storage and the storage capacity. The C storage capacity represents instantaneous responses of the land C cycle to external forcing, whereas the C storage potential represents the internal capability of the land C cycle to influence the C change trajectory in the next time step. The influence happens through redistribution of net C pool changes in a network of pools with different residence times. Moreover, this and our other studies have demonstrated that one matrix equation can replicate simulations of most land C cycle models (i.e., physical emulators). As a result, simulation outputs of those models can be placed into a three-dimensional (3-D) parameter space to measure their differences. The latter can be decomposed into traceable components to track the origins of model uncertainty. In addition, the physical emulators make data assimilation computationally feasible so that both C flux- and pool-related datasets can be used to better constrain model predictions of land C sequestration. Altogether, this new mathematical framework offers new approaches to understanding, evaluating, diagnosing, and improving land C cycle models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Design, Modeling, and Control of a Hardware-in-the-Loop Testbed for Off-Road Vehicles

This paper presents the design, modeling, and control of a hardware-in-the-loop (HIL) testbed for off-road vehicles. The proposed HIL testbed employs a transient hydrostatic dynamometer to load a diesel engine to emulate any loading cycles of a wheel loader, which is a representative off-road vehicle. A fully validated wheel loader model is used to calculate the engine load, including both the drive and work functions. Besides, iterative learning control (ILC) has been designed for the loading torque tracking of the hydrostatic dynamometer to ensure accurate emulation of real-world operation scenarios. The developed HIL testbed is used to demonstrate more than 26% energy benefits of automated wheel loaders through systematic optimization compared with human-operated wheel loaders. As a result, this HIL testbed serves as a robust platform for advancing research and development across various off-road vehicles, including excavators, tractors, and harvesters.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

A novel open-source cultivation system helps establish the first full cycle chemosynthetic symbiosis model system involving the giant ciliate Zoothamnium niveum

Symbiotic interactions drive species evolution, with nutritional symbioses playing vital roles across ecosystems. Chemosynthetic symbioses are globally distributed and ecologically significant, yet the lack of model systems has hindered research progress. The giant ciliate Zoothamnium niveum and its sulfur-oxidizing symbionts represent the only known chemosynthetic symbiosis with a short life span that has been transiently cultivated in the laboratory. While it is experimentally tractable and presents a promising model system, it currently lacks an open-source, simple, and standardized cultivation setup. Following the FABricated Ecosystems (EcoFABs) model, we leveraged 3D printing and polydimethylsiloxane (PDMS) casting to develop simple flow-through cultivation chambers that can be produced and adopted by any laboratory. The streamlined manufacturing process reduces production time by 86% and cuts cost by tenfold compared to the previous system. Benchmarking using previously established optimal growth conditions, the new open-source cultivation system proves stable, efficient, more autonomous, and promotes a more prolific growth of the symbiosis. For the first time, starting from single cells, we successfully cultivated the symbiosis in flow-through chambers for 20 days, spanning multiple generations of colonies that remained symbiotic. They were transferred from chamber to chamber enabling long-term cultivation and eliminating the need for continuous field sampling. The chambers, optimized for live imaging, allowed detailed observation of the synchronized growth between the host and symbiont. Highlighting the benefit of this new system, we here describe a new step in the first hours of development where the host pauses growth, expels a coat, before resuming growth, hinting at a putative symbiont selection mechanism early in the colony life cycle. With this simple, open-source, cultivation setup, Z. niveum holds promises for comparative studies, standardization of research and wide adoption by the symbiosis research community.

59 BASIC BIOLOGICAL SCIENCES↗