Search NASA⌕ Search

SEARCH · Search NASA

Results for “Speed Control”

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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Efficient Refrigerated Display Cases - Can They Flex Their Power? Preprint

Refrigerated display cases are widely-used, critical equipment in supermarkets for maintaining product safety and quality. Energy-efficient medium temperature liquid-cooled refrigerated display cases can save 25-70% of the total supermarket energy, according to manufacturers. Traditionally, cases operate by maintaining a temperature around a user-input setpoint that is dependent on the product in the case. Although cases are major electrical energy consumers, they are hardly ever considered for implementing load-flexibility strategies. With added load-flexibility capabilities, refrigerated display cases can shed (reduce), or shift (by adding and subsequently shedding) load. Supermarkets can reduce their energy costs and enhance electric grid integrity by implementing these smart load-flexibility control strategies. Advanced controls can also enable load-shifting to coincide with optimum periods of renewable energy generation. This will further improve operational costs and reduce greenhouse gas emissions without compromising food safety and quality. In this research, we have evaluated the energy savings of liquid-cooled medium temperature display cases and developed load flexibility strategies leveraging an advanced controls system, a variable speed compressor, and heat rejection via a water-cooled condenser. This study further assessed the impact of load flexibility strategies in a controlled environment chamber for a single refrigerated display case.

ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION↗
DOE OSTI2018

Load Mitigation on Floating Offshore Wind Turbines with Advanced Controls and Tuned Mass Dampers

General Electric, the National Renewable Energy Laboratory (NREL), the University of Massachusetts Amherst (UMass), and Glosten have recently completed a US Department of Energy (DOE)-funded research program to study technologies for mitigating loads on floating offshore wind turbines through the use of advanced turbine controls and tuned mass dampers (TMDs). The analysis was based upon the Glosten PelaStar tension leg platform (TLP) with GE Haliade 150 turbine, a system developed in a previous front end engineering design (FEED) study funded by the Energy Technology Institute (ETI) in the UK. The platform was designed for the WaveHub wave energy research site, with a mean water depth of 59-m. Loads were analyzed by running time-domain simulations in four 50-year return period (50-YRP) ultimate load state (ULS) conditions and 77 fatigue load state (FLS) environmental conditions. In 50-YRP conditions advanced controls are not active. The influence of TMDs on ULS loads have been reported previously (Park et al. [2]). In FLS conditions advanced controls and TMDs afford dramatic reductions in fatigue damage, offering the potential of significant savings in tower structural requirements. Simulations in turbine idling conditions were run in OrcaFlex, and simulations in operating conditions were run in FAST. Simulations were run with a baseline turbine controller, representative of the current state of the art, and an advanced controller developed by NREL to use collective and individual blade pitch control to maintain rotor speed and reduce tower loads. UMass developed a number of TMD types, with varying system configurations, including passive nonlinear dampers and semi-actively controlled dampers with an inverse velocity groundhook control algorithm. Loads and accelerations in FLS conditions were evaluated on the basis of damage equivalent loads (DELs), and fatigue damage was computed by Miner's summations of stress cycles at the tower base. To study sensitivity to water depth, loads were analyzed at both the 59-m WaveHub depth and a more commercially realistic depth of 100 m. TMDs reduce fatigue damage at the tower-column interface flange by up to 52% in 59-m water depth and up to 28% in 100 m water depth. Advanced controls reduce fatigue damage at the tower-column flange by up to 22% in 59-m water depth and up to 40% in 100 m water depth. The most effective load-mitigation strategy is combining advanced controls with TMDs. This strategy affords a 71% reduction in fatigue damage in both 59-m and 100-m water depths.

17 WIND ENERGY↗
DOE OSTI2017

Improving the Fuel Economy of Class 8 Military Vehicles using a Smart Cruise Control Algorithm

Connected and Automated Vehicles (CAVS) have the potential for improving fuel economy by changing the way vehicles are driven. Fuel economy can be improved through a wide range of technologies, many of which do not require Level 5 automation. One of the most promising technologies is a smart cruise control for which a speed-matching algorithm can be designed to account for fuel economy. Accounting for fuel economy in the algorithm leads to different driving behavior than simply matching the driver entered set speed. This paper describes the application of such a smart cruise control to a class 8 vehicle both in simulation and in the actual vehicle on a close test track. This paper evaluates the algorithm and describes the correlation procedure used to calibrate the model using test data from the vehicle.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2018

Characterization of temporal variations and feedback timescales of exhaust gas recirculation gas properties using high-speed diode laser absorption spectroscopy for next-cycle control of cyclic variability

Dilute combustion offers efficiency gains in boosted gasoline direct injection engines both through knock-limit extension and thermodynamic advantages (i.e. the effect of γ on cycle efficiency), but is limited by cyclic variability at high dilution levels. Past studies have shown that the cycle-to-cycle dynamics are a combination of deterministic and stochastic effects. The deterministic causes of cyclic variations, which arise from feedback due to exhaust gas recirculation, imply the possibility of using active control strategies for dilution limit extension. While internal exhaust gas recirculation will largely provide a next-cycle effect (short-timescale feedback), the feedback of external exhaust gas recirculation will have an effect after a delay of several cycles (long timescale). Therefore, control strategies aiming to improve engine stability at dilution limit may have to account for both short- and long-timescale feedback pathways. This study shows the results of a study examining the extent to which variations in exhaust gas recirculation composition are preserved along the exhaust gas recirculation flow path and thus the relative importance and information content of the long-timescale feedback pathway. To characterize the filtering or retention of cycle-resolved feedback information, high-speed (1–5 kHz) CO 2 concentration measurements were performed simultaneously at three different locations along the low-pressure external exhaust gas recirculation loop of a four-cylinder General Motors gasoline direct injection engine using a multiplexed two-color diode laser absorption spectroscopy sensor system during steady-state and transient engine operation at various exhaust gas recirculation levels. It was determined that cycle-resolved feedback propagates through internal residual gases but is filtered out by the low-pressure exhaust gas recirculation flow system and do not reach the intake manifold. Intermediate variations driven by flow rate and compositional changes are also distinguished and identified.

Dilute combustion↗
DOE OSTI2023

Controlled In Situ Foaming for Mechanical Responsiveness of Architected Foams

Addition of chemical blowing agents to polysiloxane resins produces foams with closed–cell morphology. Combining this chemistry with the 3D–printing technique direct ink writing (DIW) permits the creation of architected foams with controllable, hierarchical tiers of porosity. Here, using a two–component foaming ink, the extent of foaming can be controlled by incorporating an active mixing printhead as part of the fabrication process. Changes in the mixing speed allows for in situ control of the foaming reaction where the mixing speed is directly correlated with the resulting foaming that occurs upon extrusion. These architected foams display tunable mechanical responses, porosities, and open–to–closed cell ratios. While chemically blown polysiloxane foam is a well–established material, utilizing DIW as fabrication technique presents a novel approach for creating tailored, architected foams that require minimal post–processing.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Neuroevolution Application to Collaborative and Heuristics-Based Connected and Autonomous Vehicle Cohort Simulation at Uncontrolled Intersection

Artificial intelligence is gaining tremendous attractiveness and showing great success in solving various problems, such as simplifying optimal control derivation. This work focuses on the application of Neuroevolution to the control of Connected and Autonomous Vehicle (CAV) cohorts operating at uncontrolled intersections. The proposed method implementation’s simplicity, thanks to the inclusion of heuristics and effective real-time performance are demonstrated. The resulting architecture achieves nearly ideal operating conditions in keeping the average speeds close to the speed limit. It achieves twice as high mean speed throughput as a controlled intersection, hence enabling lower travel time and mitigating energy inefficiencies from stop-and-go vehicle dynamics. Low deviation from the road speed limit is hence continuously sustained for cohorts of at most 50 m long. This limitation can be mitigated with additional lanes that the cohorts can split into. The concept also allows the testing and implementation of fast-turning lanes by simply replicating and reconnecting the control architecture at each new road crossing, enabling high scalability for complex road network analysis. The controller is also successfully validated within a high-fidelity vehicle dynamic environment, showing its potential for driverless vehicle control in addition to offering a new traffic control simulation model for future autonomous operation studies.

Jacquelin, Frederic (ORCID:0000000183154344)↗
DOE OSTI2019

Model Predictive Control of GTAW Weld Pool Penetration

Weld pool penetration is a major implication of weld integrity but it is not directly measurable. The key to solving this issue is to find or create observable phenomena that can be used to derive the penetration. An innovative method has recently been proposed/developed to derive the penetration from the reflection of projected laser from an oscillating weld pool surface. Yet, in addition to the penetration, the oscillation, thus the reflection determined by it, also depends on the pulse amplitude of the current, which needs to be adjusted as the control variable to feedback control the penetration as the output. This dependence imposes a constraint on the control algorithm such that the adjustment of the control variable must be relatively slow to minimize additional sources that affect the oscillation/sensor. This restriction on the control variable adjustment also brings challenges to the identification of the dynamic model of the weld process to be controlled, which has to apply a varying control signal to stimulate the dynamics. To solve these issues, this letter proposes using a low order model to catch the dominant dynamics such that a high speed variation in the control signal can be avoided when choosing the model predictive control algorithm. This allows use of relatively poor models to determine the adjustment on the pulsing amplitude, and still achieves relatively accurate control. Experimental results verified the effectiveness of the resultant penetration control system despite the restrictions imposed by the penetration sensor, which affect the identification of high order dynamics and free adjustments of control variables.

42 ENGINEERING↗
DOE OSTI2020

Development of Real-Time System Identification to Detect Abnormal Operations in a Gas Turbine Cycle

Here, we present a novel online system identification methodology for monitoring the performance of power systems. This methodology was demonstrated in a gas turbine recuperated power plant designed for a hybrid configuration. A 120-kW Garrett microturbine modified to test dynamic control strategies for hybrid power systems designed at the National Energy Technology Laboratory (NETL) was used to implement and validate this online system identification methodology. The main component of this methodology consists of an empirical transfer function model implemented in parallel to the turbine speed operation and the fuel control valve, which can monitor the process response of the gas turbine system while it is operating. During fully closed-loop operations or automated control, the output of the controller, fuel valve position, and the turbine speed measurements were fed for a given period of time to a recursive algorithm that determined the transfer function parameters during the nominal condition. After the new parameters were calculated, they were fed into the transfer function model for online prediction. The turbine speed measurement was compared against the transfer function prediction, and a control logic was implemented to capture when the system operated at nominal or abnormal conditions. To validate the ability to detect abnormal conditions during dynamic operations, drifting in the performance of the gas turbine system was evaluated. A leak in the turbomachinery working fluid was emulated by bleeding 10% of the airflow from the compressor discharge to the atmosphere, and electrical load steps were performed before and after the leak. This tool could detect the leak 7 s after it had occurred, which accounted for a fuel flow increase of approximately 15.8% to maintain the same load and constant turbine speed operations.

algorithms↗
DOE OSTI2023

A practical approach to determine minimal quantum gate durations using amplitude-bounded quantum controls

Here, we present an iterative scheme to estimate the minimal duration in which a quantum gate can be realized while satisfying hardware constraints on the control pulse amplitudes. The scheme performs a sequence of unconstrained numerical optimal control cycles that each minimize the gate fidelity for a given gate duration alongside an additional penalty term for the control pulse amplitudes. After each cycle, the gate duration is adjusted based on the inverse of the resulting maximum control pulse amplitudes by re-scaling the dynamics to a new duration where control pulses satisfy the amplitude constraints. Those scaled controls then serve as an initial guess for the next unconstrained optimal control cycle, using the adjusted gate duration. We provide multiple numerical examples that each demonstrate fast convergence of the scheme toward a gate duration that is close to the quantum speed limit, given the control pulse amplitude bound. The proposed technique is agnostic to the underlying system and control Hamiltonian models, as well as the target unitary gate operation, making the time-scaling iteration an easy to implement and practically useful scheme for reducing the durations of quantum gate operations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Servo-aero-gravo-elastic (SAGE) scaling and its application to a 13-MW downwind turbine

Reduced scale wind turbines can be extremely cost-effective to test new rotor concepts since prototype costs are heavily dependent on the rotor diameter. Ideally, the scaled model would have the same non-dimensional deflections, dynamics, and control behavior as the full-scale model. This would provide a high-fidelity demonstration of the full-scale performance, which is ideal if the full-scale turbine has significant aeroelastic interactions. To this end, servo-aero-gravo-elastic (SAGE) scaling is developed and applied to a 13-MW turbine that is scaled to a 20% scale model. The scaling preserves the tip-speed ratio, the rotor speed normalized by the flapping frequency, and the tip deflections normalized by the blade length. In addition, the controller employs the same control structure (gain-scheduled pitch control and variable speed torque control) and is scaled dynamically (e.g., matching non-dimensional time constant of the pitch angle, etc.). Furthermore, the thrust, gravity, and centrifugal moments are scaled such that the load angles are preserved as a function of a non-dimensional wind speed. However, the environmental scaling must consider differences in Reynolds number (since this parameter cannot be held constant) and subsequent changes in the axial induction factor. While the presented results showcase these differences during operational conditions, the non-dimensional tip deflections remain comparable through all wind speed ranges, indicating the viability of the SAGE scaling method in matching full-scale aeroelastic responses.

Kaminski, Meghan (ORCID:0000000322334784)↗
DOE OSTI2021

Constrained power reference control for wind turbines

The cost of wind energy can be reduced by controlling the power reference of a turbine to increase energy capture, while maintaining load and generator speed constraints. We apply standard torque and pitch controllers to the direct inputs of the turbine and use their set points to change the power output and reduce generator speed and blade load transients. A power reference controller increases the power output when conditions are safe and decreases it when problematic transient events are expected. Transient generator speeds and blade loads are estimated using a gust measure derived from a wind speed estimate. A hybrid controller decreases the power rating from a maximum allowable power. Compared to a baseline controller, with a constant power reference, the proposed controller results in generator speeds and blade loads that do not exceed the original limits, increases tower fore-aft damage equivalent loads by 1%, and increases the annual energy production by 5%.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Intracycle RPM control for vertical axis wind turbines

The wind energy market is currently dominated by horizontal axis wind turbines (HAWTs); however, vertical axis wind turbines (VAWTs) are emerging as a design alternative, especially for deep-water offshore siting due to their low center of gravity, ease of access to drivetrain components, and overall simplicity. Due to the absence of a pitch mechanism in large-scale Darrieus VAWTs, stall control has often been used to manage power and loads. Introducing a pitching mechanism in H-type VAWTs has been studied, but this diminishes the mechanical simplicity advantage, and the use of a pitching mechanism in a large-scale Darrieus-type VAWT is not practical. This work examines an innovative, alternative method to control the rotor dynamics of a large-scale 5 MW VAWT to maximize power while constraining loads without introducing any new or complex mechanical elements. This control strategy is termed intracycle revolution per minute (RPM) control, where the rotational speed of the turbine is allowed to vary in an optimal fashion with the azimuthal location of blades as opposed to typical constant RPM operation. An optimization framework is formulated for an open-loop optimal control problem and solved to maximize power subject to constraints on aerodynamic design loads. Results are presented to demonstrate the benefits and the performance limits of intracycle RPM control for large-scale 5 MW Darrieus VAWTs, namely, (1) power production (quantified in terms of AEP) that can be increased subject to baseline load limits and (2) opportunities to significantly increase AEP or decrease loads via intracycle RPM control that are examined for both two-bladed and three-bladed VAWTs.

17 WIND ENERGY↗
DOE OSTI2022

Impact of battery cell imbalance on electric vehicle range

Due to manufacturing variation, battery cells often possess heterogeneous characteristics, leading to battery state-of-charge variation in real-time. Since the lowest cell state-of-charge determines the useful life of battery pack, such variation can negatively impact the battery performance and electric vehicles range. Existing research has been focused on control design to mitigate cell imbalance. However, it is yet unclear how much impacts the cell imbalance can have on electric vehicle range. This paper closes this knowledge gap by using a simulation environment consisting of real-world driving speed data, vehicle longitudinal control, propulsion and vehicle dynamics, and cell level battery modeling. In particular, each battery cell is modeled as an equivalent circuit model, and variations among cell parameters are introduced to assess their impact on electric vehicles range and to identify the most influential parameter variations. Simulation results and analysis can be used to assist balancing control design and to benchmark control performance.

25 ENERGY STORAGE↗
DOE OSTI2021

Nonlinear dynamics of proton beams with hollow electron lens in the CERN high-luminosity LHC

The design stored beam energy in the CERN high-luminosity large hadron collider (HL-LHC) upgrade is about 700 MJ, with about 36 MJ in the beam tails, according to estimates based on scaling considerations from measurements at the LHC. Such a large amount of stored energy in the beam tails poses serious challenges on its control and safe disposal. In particular, orbit jitters can cause significant losses on primary collimators, which can lead to accidental beam dumps, magnet quenches, or even permanent damage to collimators and other accelerator elements. Thus, active control of the diffusion speed of halo particles is necessary and the use of hollow electron lenses (HELs) represents the most promising approach to handle overpopulated tails at the HL-LHC. HEL is a very powerful and advanced tool that can be used for controlled depletion of beam tails, thus enhancing the performance of beam halo collimation. For these reasons, HELs have been recently included in the HL-LHC baseline. In this paper, we present detailed beam dynamics calculations performed with the goal of defining HEL specifications and operational scenarios for HL-LHC. The prospects for effective halo control in HL-LHC are presented.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

A Cyber-Physical System for Freeway Ramp Meter Signal Control Using Deep Reinforcement Learning in a Connected Environment

Freeway bottlenecks such as on-ramp merging areas account for about 40% of recurring freeway congestion. It is generally agreed that building more roads and adding more lanes to existing infrastructure does not solve the congestion problem, and so dynamic traffic control measures offer a more cost-effective alternative. Ramp meters, traffic signal devices that regulate traffic flow entering freeways, are among the most effective measures to mitigate congestion at on-ramp merging areas on freeways. The confluence of deep reinforcement learning (RL) and connectivity provides a possible solution to advance ramp meter signal control. Deep RL is a group of machine-learning methods that enables an agent learning from the environment to improve its performance. In this study, three deep RL methods-proximal policy optimization (PPO), Ape-X deep Q-network (DQN), and asynchronous advantage actor-critic agents (A3C)-are explored for ramp meter signal control to maximize vehicle speed and traffic throughput, as well as to minimize energy consumption and emissions at freeway on-ramp merging areas in a connected environment. The low computational requirement and scalability of deep RL for deployment make it a powerful optimization tool for time-sensitive applications such as ramp meter signal control. The results of this study show that deep RL methods yield superior performance to both a fixed-time controller and ALINE A, a state-of-the-art feedback controller.

ADVANCED PROPULSION SYSTEMS,MATHEMATICS AND COMPUT↗
DOE OSTI2017

Intelligent Weld Manufacturing: Role of Integrated Computational Welding Engineering

A master welder uses his sensory perceptions to evaluate the process and connect them with his/her knowledge base to take the necessary corrective measures with his/her acquired skills to make a good weld. All these actions must take place in real time. Success depends on intuition and skills, and the procedure is labor-intensive and frequently unreliable. The solution is intelligent weld manufacturing. The ultimate goal of intelligent weld manufacturing would involve sensing and control of heat source position, weld temperature, weld penetration, defect formation and ultimately control of microstructure and properties. This involves a solution to a problem (welding) with many highly coupled and nonlinear variables. The trend is to use an emerging tool known as intelligent control. This approach enables the user to choose a desirable end factor such as properties, defect control, or productivity to derive the selection of process parameters such as current, voltage, or speed to provide for appropriate control of the process. Important elements of intelligent manufacturing are sensing and control theory and design, process modeling, and artificial intelligence. Significant progress has been made in all these areas. Integrated computational welding engineering (ICWE) is an emerging field that will aid in the realization of intelligent weld manufacturing. The paper will discuss the progress in process modeling, microstructure, properties, and process control and automation and the importance of ICWE. Also, control and automation strategies for friction stir welding will be discussed.

42 ENGINEERING↗
DOE OSTI2020

Modifying Network Guided Vehicle for Repeatable EcoCAR ACC Energy Testing

The newest iteration of the Department of Energy (DOE) Advanced Vehicle Technology Competitions is the EcoCAR Mobility Challenge. In this paper, ANL and HORIBA MIRA collaborate to propose and pilot a test method that enables controlled, repeatable track-based energy consumption testing of semi-autonomous features. The testing was performed at MIRA’s proving ground facility in Nuneaton, UK, using their Network Guided Vehicle (NGV) connectivity and automation test platform. The NGV served as a repeatable lead vehicle following prescribed drive traces around two different track circuits while the host vehicle under test, a Honda Civic with full speed range Adaptive Cruise Control, followed behind. Over the course of a two day test, multiple iterations of certification and custom EPA drive traces were performed on track, demonstrating the viability of a two vehicle energy test. Results were analyzed to assess NGV lead vehicle performance in following the prescribed cycle using SAE J2951 standard calculations in an effort to quantify how repeatably and accurately the lead vehicle followed the trace. Host vehicle energy consumption was assessed using both vehicle CAN bus monitoring and an on-board fuel flow meter.

ACC↗
DOE OSTI2026

A Graphical User Interface for the Deep Underground Neutrino Experiment Robotic Test Stand

In preparation for DUNE, Fermilab along with six other institutions are testing cold electronics for quality control before components placed in the far detector. We test them by using a robotic arm that places these chips into sockets on a computer board that will test their functionality. Up until now, the chips have been tested using a command line script that drives a state machine to conduct tests step-by-step. In order to lower the skill barrier to conduct tests and to speed up the quality control process, I was tasked to create a graphical user interface that would allow users to use buttons, text boxes, and drop-down menus to input information and tell the testing state machine how to operate. I had to learn about the Python package Tkinter to start the process of widget placement. I further developed a pause feature unused in the previous command line script that would allow the user to shut down testing gracefully, bring the robotic arm to go back to ground state, and go forward or backward a step in the testing process. After completing the basic functionality of the GUI, I started testing production chips with the GUI to debug. Some issues were found, which required me to further develop parts of the inherited state machine code. The code for the GUI has now been pushed into the copy the DUNE/FD_CE git repository and will soon be merged with the official DUNE/FD_CE repository so that the other institutions testing DUNE cold electronics can use and expand upon it.

Gutierrez Villanueva, Jaziel [Fermilab]↗