Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “energy management”

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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Model Predictive Control Strategies for Turbine Electrified Energy Management

The increasing electrification of aircraft propulsion systems is leading to new control architectures being developed to address integration between electric machines and gas-based turbine engines. For hybrid-electric propulsion systems, current conceptual architectures often couple electric machines with the shafts of gas turbine engines and introduce energy storage. Leveraging the electrical power system of hybridized engines, Turbine Electrified Energy Management (TEEM) is a recent control approach that improves transient operability in an effort to enable more efficient and lighter weight turbomachinery. This study seeks to expand TEEM’s application beyond traditional proportional-integral (PI) control by presenting linear model predictive control (MPC) schemes to execute the TEEM concept. Through constraint selection and cost function design, transient operability goals for TEEM are considered with no external logic or saturation. Unique to the designs are the use of a washout filter, which simplifies transient detection and motor activation logic. The proposed architectures are implemented with both centralized MPC and distributed MPC approaches, and comparisons are drawn to a benchmark PI controller simulated on a nonlinear turbofan engine model at one ground condition and one cruise condition. Performance is evaluated using compressor maps, stall margin performance, and two novel metrics: transient stack usage and transient excursion integral. Results reveal the linear MPC scheme performs comparably to the baseline controller and can be implemented in at least two distinct configurations with potential for further modifications, thus establishing the groundwork for future investigations.

Model Predictive Control↗
NASA NTRSDate not supplied

Model Predictive Control Strategies for Turbine Electrified Energy Management

The increasing electrification of aircraft propulsion systems is leading to new control architectures being developed to address integration between electric machines and gas-based turbine engines. For hybrid-electric propulsion systems, current conceptual architectures often couple electric machines with the shafts of gas turbine engines and introduce energy storage. Leveraging the electrical power system of hybridized engines, Turbine Electrified Energy Management (TEEM) is a recent control approach that improves transient operability in an effort to enable more efficient and lighter weight turbomachinery. This study seeks to expand TEEM’s application beyond traditional proportional integral (PI) control by presenting linear model predictive control (MPC) schemes to execute the TEEM concept. Through constraint selection and cost function design, transient operability goals for TEEM are considered with no external logic or saturation. Unique to the designs are the use of a washout filter, which simplifies transient detection and motor activation logic. The proposed architectures are implemented with both centralized MPC and distributed MPC approaches, and comparisons are drawn to a benchmark PI controller simulated on a nonlinear turbofan engine model at one ground condition and one cruise condition. Performance is evaluated using compressor maps, stall margin performance, and two novel metrics: transient stack usage and transient excursion integral. Results reveal the linear MPC scheme performs comparably to the baseline controller and can be implemented in at least two distinct configurations with potential for further modifications, thus establishing the groundwork for future investigations.

Model Predictive Control↗
NASA NTRS2023

Model Predictive Control Strategies for Turbine Electrified Energy Management

The increasing electrification of aircraft propulsion systems is leading to new control architectures being developed to address integration between electric machines and gas-based turbine engines. For hybrid-electric propulsion systems, current conceptual architectures often couple electric machines with the shafts of gas turbine engines and introduce energy storage. Leveraging the electrical power system of hybridized engines, Turbine Electrified Energy Management (TEEM) is a recent control approach that improves transient operability in an effort to enable more efficient and lighter weight turbomachinery. This study seeks to expand TEEM’s application beyond traditional proportional-integral (PI) control by presenting linear model predictive control (MPC) schemes to execute the TEEM concept. Through constraint selection and cost function design, transient operability goals for TEEM are considered with no external logic or saturation. Unique to the designs are the use of a washout filter, which simplifies transient detection and motor activation logic. The proposed architectures are implemented with both centralized MPC and distributed MPC approaches, and comparisons are drawn to a benchmark PI controller simulated on a nonlinear turbofan engine model at one ground condition and one cruise condition. Performance is evaluated using compressor maps, stall margin performance, and two novel metrics: transient stack usage and transient excursion integral. Results reveal the linear MPC scheme performs comparably to the baseline controller and can be implemented in at least two distinct configurations with potential for further modifications, thus establishing the groundwork for future investigations.

Model Predictive Control↗
DOE OSTI2025

An Introduction to the Federated Architecture for Secure and Transactive Distributed Energy Management Solutions (FAST-DERMS)

Deployment and capability of distributed energy resources (DER) in power systems is growing rapidly. These resources present an opportunity for low-cost provision of energy and grid services. The Federal Energy Regulatory Commission recently provided rulings to enable market participation of these distribution-connected resources, but the prevailing strategies for their management may not scale well to meet future needs. This paper introduces the Federated Architecture for Secure and Transactive Distributed Energy Management Solutions (FAST-DERMS) which was designed to address this need. In it we describe the architectural features of the approach, and a reference controls implementation employing a hierarchical coordination that includes stochastic optimization, model predictive control, and a simple real-time management scheme. Sample results from simulation show firm transmission-level service provision measured at the distribution substation.

grid architecture↗
NASA NTRS1976

Terminal area energy management regime investigations utilizing an 0.030-scale model (47-0) of the space shuttle vehicle orbiter configuration 140A/B/C/R in the Ames Research Center 11 x 11 foot transonic wind tunnel (OH/48)

Data obtained in a wind tunnel test were examined to: (1) obtain pressure distributions, forces and moments over the vehicle 5 Orbiter in the terminal area energy management (TAEM) and approach phases of flight; (2) obtain elevon and rudder hinge moments in the TAEM and approach phases of flight; (3) obtain body flap and elevon loads for verification of loads balancing with integrated pressure distributions; and (4) obtain pressure distributions near the short OMS pods in the high subsonic, transonic and low supersonic Mach number regimes. Testing was conducted over a Mach number range from 0.6 to 1.4 with Reynolds number variations from 7.57 x 1 million to 2.74 x 1 million per foot. Model angle of attack was varied from -4 to 16 degrees and angles of sideslip ranged from -8 to 8 degrees.

Hawthorne, P. J.↗
NASA NTRS1976

Terminal area energy management regime investigations utilizing an 0.030-scale model (47-0) of the space shuttle vehicle orbiter configuration 140A/B/C/R in the Ames Research Center 11 x 11 foot transonic wind tunnel (0A148), volume 1

Data obtained in wind tunnel tests are presented. The objectives of the tests were to: (1) obtain pressure distributions, forces and moments over the vehicle 5 Orbiter in the terminal area energy management (TAEM) and approach phases of flight; (2) obtain elevon and rudder hinge moments in the TAEM and approach phases of flight; (3) obtain body flap and elevon loads for verification of loads balancing with integrated pressure distributions; and (4) obtain pressure distributions near the short OMS pods in the high subsonic, transonic and low supersonic Mach number regimes. Testing was conducted over a Mach number range from 0.6 to 1.4 with Reynolds number variations from 4.57 million to 2.74 million per foot. Model angle-of-attack was varied from -4 to 16 degrees and angles of side slip ranged from -8 to 8 degrees.

Hawthorne, P. J.↗
NASA NTRS1962

Fixed-Base Simulator Studies of the Ability of the Human Pilot to Provide Energy Management Along Abort and Deep-Space Entry Trajectories

A simulation study has been made to determine a pilot's ability to control a low L/D vehicle to a desired point on the earth with initial conditions ranging from parabolic orbits to abort conditions along the boost phase of a deep-space mission. The program was conducted to develop procedures which would allow the pilot to perform the energy management functions required while avoiding the high deceleration or skipout region and to determine the information display required to aid the pilot in flying these procedures. The abort conditions studied extend from a region of relatively high flight-path angles at suborbital velocities while leaving the atmosphere to a region between orbital and near-escape velocity outside the atmosphere. The conditions studied included guidance from suborbital and superorbital aborts as well as guidance following return from a deepspace mission. In this paper, the role of the human pilot?s ability to combine safe return abort procedures with guidance procedures has been investigated. The range capability from various abort and entry conditions is also presented.

PILOT↗
NASA NTRS1976

Terminal area energy management regime investigations utilizing an 0.030-scale model (47-0) of the space shuttle vehicle orbiter configuration 140A/B/C/R in the Ames Research Center 11 x 11 foot transonic wind tunnel (OA148), volume 5

Data obtained in wind tunnel test OA148 are presented. The objectives of the test series were to: (1) obtain pressure distributions, forces and moments over the vehicle 5 orbiter in the thermal area energy management (TAEM) and approach phases of flight; (2) obtain elevon and rudder hinge moments in the TAEM and approach phases of flight; (3) obtain body flap and elevon loads for verification of loads balancing with integrated pressure distributions; and (4) obtain pressure distributions near the short OMS pods in the high subsonic, transonic and low supersonic Mach number regimes.

Hawthorne, P. J.↗
NASA NTRS2003

Fuzzy Logic Trajectory Design and Guidance for Terminal Area Energy Management

The second generation reusable launch vehicle will leverage many new technologies to make flight to low earth orbit safer and more cost effective. One important capability will be completely autonomous flight during reentry and landing, thus making it unnecessary to man the vehicle for cargo missions with stringent weight constraints. Implementation of sophisticated new guidance and control methods will enable the vehicle to return to earth under less than favorable conditions. The return to earth consists of three phases--Entry, Terminal Area Energy Management (TAEM), and Approach and Landing. The Space Shuttle is programmed to fly all three phases of flight automatically, and under normal circumstances the astronaut-pilot takes manual control only during the Approach and Landing phase. The automatic control algorithms used in the Shuttle for TAEM and Approach and Landing have been developed over the past 30 years. They are computationally efficient, and based on careful study of the spacecraft's flight dynamics, and heuristic reasoning. The gliding return trajectory is planned prior to the mission, and only minor adjustments are made during flight for perturbations in the vehicle energy state. With the advent of the X-33 and X-34 technology demonstration vehicles, several authors investigated implementing advanced control methods to provide autonomous real-time design of gliding return trajectories thus enhancing the ability of the vehicle to adjust to unusual energy states. The bulk of work published to date deals primarily with the approach and landing phase of flight where changes in heading angle are small, and range to the runway is monotonically decreasing. These benign flight conditions allow for model simplification and fairly straightforward optimization. This project focuses on the TAEM phase of flight where mathematically precise methods have produced limited results. Fuzzy Logic methods are used to make onboard autonomous gliding return trajectory design robust to a wider energy envelope, and the possibility of control surface failures, thus increasing the flexibility of unmanned gliding recovery and landing.

Burchett, Bradley↗
NASA NTRSDate not supplied

Turbine Electrified Energy Management with Model Predictive Control

Affordability, sustainability, and efficiency are primary motivators driving the future of NASA aeronautics research. These factors are realized, in part, through the development and implementation of new technologies and strategies enabling efficient, affordable, and safe hybrid-electric aircraft. Research supporting electrified aircraft propulsion control systems exemplifies such new methodologies, offering varied opportunities to integrate electric machines with gas-based turbine engines. For hybrid-electric propulsion systems, current conceptual architectures seek to introduce energy storage and exploit electrical power system components to assist gas-based system components. Capitalizing on the electric machines in hybridized engines, Turbine Electrified Energy Management (TEEM) is a control approach that enhances transient operability to improve overall propulsion and vehicle efficiency by injecting or extracting power from engine shafts. Traditionally implemented with proportional-integral (PI) control, this study expands the application of TEEM by presenting model predictive control (MPC) schemes to execute the TEEM concept. Via cost function design and constraint selection, the transient operability goals for TEEM are considered in the controller designs. The proposed MPCs are simulated on a nonlinear turbofan engine model at two environmental conditions, with comparisons drawn to a baseline PI. Performance is evaluated using compressor maps and two TEEM-specific metrics: transient stack usage and transient excursion integral. Simulation results reveal the developed schemes perform comparably to the benchmark controller and can be implemented in two distinct configurations. Potential modifications for future investigations include cost function measures that optimize energy use, additional performance effectiveness measures, and battery storage capabilities.

Elyse D. Hill↗
NASA NTRS1981

Concepts for design of an energy management system incorporating dispersed storage and generation

New forms of generation based on renewable resources must be managed as part of existing power systems in order to be utilized with maximum effectiveness. Many of these generators are by their very nature dispersed or small, so that they will be connected to the distribution part of the power system. This situation poses new questions of control and protection, and the intermittent nature of some of the energy sources poses problems of scheduling and dispatch. Under the assumption that the general objectives of energy management will remain unchanged, the impact of dispersed storage and generation on some of the specific functions of power system control and its hardware are discussed.

Kirkham, H.↗
NASA NTRS1981

Integration of energy management concepts into the flight deck

The rapid rise of fuel costs has become a major concern of the commercial aviation industry, and it has become mandatory to seek means by which to conserve fuel. A research program was initiated in 1979 to investigate the integration of fuel-conservative energy/flight management computations and information into today's and tomorrow's flight deck. One completed effort within this program has been the development and flight testing of a fuel-efficient, time-based metering descent algorithm in a research cockpit environment. Research flights have demonstrated that time guidance and control in the cockpit was acceptable to both pilots and ATC controllers. Proper descent planning and energy management can save fuel for the individual aircraft as well as the fleet by helping to maintain a regularized flow into the terminal area.

Morello, S. A.↗
DOE OSTI2024

An Introduction to the Federated Architecture for Secure and Transactive Distributed Energy Management Solutions (FAST-DERMS): Preprint

Deployment and capability of distributed energy resources (DER) in power systems is growing rapidly. These resources present an opportunity for low-cost provision of energy and grid services. The Federal Energy Regulatory Commission recently provided rulings to enable market participation of these distribution-connected resources, but the prevailing strategies for their management may not scale well to meet future needs. This paper introduces the Federated Architecture for Secure and Transactive Distributed Energy Management Solutions (FASTDERMS) which was designed to address this need. In it we describe the architectural features of the approach, and a reference controls implementation employing a hierarchical coordination that includes stochastic optimization, model predictive control, and a simple real-time management scheme. Sample results from simulation show firm transmission-level service provision measured at the distribution substation.

DERMS↗
NASA NTRS2018

Turbine Electrified Energy Management (TEEM) For Enabling More Efficient Engine Designs

NASA is investing in Electrified Aircraft Propulsion (EAP) research as part of an effort to assist industry in meeting the future needs of a global aviation market. The integration of electric machines into traditional turbine-based propulsion provides opportunities to change system architectures effecting radical improvements in propulsive efficiency. However, less consideration has been afforded to the utilization of these electrical machines to improve the thermal efficiency and performance of the gas turbine engine. Noting this deficit, a novel operability concept is proposed and is referred to as Turbine Electrified Energy Management (TEEM). The concept is a transient control technology that supplements the main fuel control for the suppression of the natural off-design dynamics associated with changes in engine operating state. Here the electric machines, used as engine actuators during the transient, add or extract torque from the engine shafts to maintain the speed-flow characteristics of steady-state design operation. This greatly reduces the need to maintain transient stall margin stack in the compressors, among other potential benefits. This paper demonstrates the feasibility of the concept in dynamic simulation using a Numerical Propulsion System Simulation (NPSS) engine model of a NASA hybrid electric propulsion concept known as the Parallel Hybrid Electric Turbofan (hFan).

Culley, Dennis E.↗
DOE OSTI2023

Inverse reinforcement learning control for building energy management

Reinforcement learning (RL) based control is widely considered a promising approach in building automation and control as it has demonstrated the potential to deal with complex objectives in adjacent domains like robotics, autonomous vehicles, gaming applications, and advertisement recommendations. When applied to any environment, model-free RL learns to improve its control performance over time without requiring a control model, by receiving and then analyzing feedback from the building environment after each control action. Operational objectives are becoming increasingly complex through the simultaneous consideration of thermal comfort, carbon emissions, grid services, and indoor air quality. In this context, conventional rule-based control approaches are proving sub-optimal, mostly heuristic, and inadequate. The model-free and self learning nature of RL appears promising and attractive as it may address the scalability issues associated with advanced control approaches. However, it suffers from long training times and unstable control behavior during the early stages of its learning process, which makes it unsuitable to be applied directly to buildings. This paper addresses these issues using an inverse reinforcement learning approach (IRL), a technique utilized to learn the objective of a controller agent which is considered an expert in its respective domain. Here, we consider a rule-based control as the expert demonstrator. IRL is different from a direct imitation (i.e., direct mapping of states to actions) of control actions as it tries to find the underlying intent of an expert's policy, providing the controller with a better-generalized policy for unseen states or environments with slightly different dynamics. This approach propels the RL controller's policy to levels similar to or better than that of a rule-based policy before it starts learning by interacting with the building. This makes RL for building energy management applications more practical as it prevents the erratic and exploratory behavior in the initial training period, simultaneously speeding up the learning process when compared to applying an untrained RL agent directly to a building environment.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS2009

CEOS Contributions to Informing Energy Management and Policy Decision Making Using Space-Based Earth Observations

Earth observations are playing an increasingly significant role in informing decision making in the energy sector. In renewable energy applications, space-based observations now routinely augment sparse ground-based observations used as input for renewable energy resource assessment applications. As one of the nine Group on Earth Observations (GEO) societal benefit areas, the enhancement of management and policy decision making in the energy sector is receiving attention in activities conducted by the Committee on Earth Observation Satellites (CEOS). CEOS has become the "space arm" for the implementation of the Global Earth Observation System of Systems (GEOSS) vision. It is directly supporting the space-based, near-term tasks articulated in the GEO three-year work plan. This paper describes a coordinated program of demonstration projects conducted by CEOS member agencies and partners to utilize Earth observations to enhance energy management end-user decision support systems. I discuss the importance of engagement with stakeholders and understanding their decision support needs in successfully increasing the uptake of Earth observation products for societal benefit. Several case studies are presented, demonstrating the importance of providing data sets in formats and units familiar and immediately usable by decision makers. These projects show the utility of Earth observations to enhance renewable energy resource assessment in the developing world, forecast space-weather impacts on the power grid, and improve energy efficiency in the built environment.

Eckman, Richard S.↗
NASA NTRS1994

Principles of light energy management

Six methods used to minimize excess energy effects associated with lighting systems for plant growth chambers are reviewed in this report. The energy associated with wall transmission and chamber operating equipment and the experimental requirements, such as fresh air and internal equipment, are not considered here. Only the energy associated with providing and removing the energy for lighting is considered.

Davis, N.↗