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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 19 records

All sources NASA NTRS DOE OSTI

NASA NTRS1996

Application of Hybrid Optimization-Expert System for Optimal Power Management on Board Space Power Station

The space power system has two sources of energy: photo-voltaic blankets and batteries. The optimal power management problem on-board has two broad operations: off-line power scheduling to determine the load allocation schedule of the next several hours based on the forecast of load and solar power availability. The nature of this study puts less emphasis on speed requirement for computation and more importance on the optimality of the solution. The second category problem, on-line power rescheduling, is needed in the event of occurrence of a contingency to optimally reschedule the loads to minimize the 'unused' or 'wasted' energy while keeping the priority on certain type of load and minimum disturbance of the original optimal schedule determined in the first-stage off-line study. The computational performance of the on-line 'rescheduler' is an important criterion and plays a critical role in the selection of the appropriate tool. The Howard University Center for Energy Systems and Control has developed a hybrid optimization-expert systems based power management program. The pre-scheduler has been developed using a non-linear multi-objective optimization technique called the Outer Approximation method and implemented using the General Algebraic Modeling System (GAMS). The optimization model has the capability of dealing with multiple conflicting objectives viz. maximizing energy utilization, minimizing the variation of load over a day, etc. and incorporates several complex interaction between the loads in a space system. The rescheduling is performed using an expert system developed in PROLOG which utilizes a rule-base for reallocation of the loads in an emergency condition viz. shortage of power due to solar array failure, increase of base load, addition of new activity, repetition of old activity etc. Both the modules handle decision making on battery charging and discharging and allocation of loads over a time-horizon of a day divided into intervals of 10 minutes. The models have been extensively tested using a case study for the Space Station Freedom and the results for the case study will be presented. Several future enhancements of the pre-scheduler and the 'rescheduler' have been outlined which include graphic analyzer for the on-line module, incorporating probabilistic considerations, including spatial location of the loads and the connectivity using a direct current (DC) load flow model.

Momoh, James↗

NASA NTRS1996

Advanced Intelligent System Application to Load Forecasting and Control for Hybrid Electric Bus

The primary motivation for this research emanates from providing a decision support system to the electric bus operators in the municipal and urban localities which will guide the operators to maintain an optimal compromise among the noise level, pollution level, fuel usage etc. This study is backed up by our previous studies on study of battery characteristics, permanent magnet DC motor studies and electric traction motor size studies completed in the first year. The operator of the Hybrid Electric Car must determine optimal power management schedule to meet a given load demand for different weather and road conditions. The decision support system for the bus operator comprises three sub-tasks viz. forecast of the electrical load for the route to be traversed divided into specified time periods (few minutes); deriving an optimal 'plan' or 'preschedule' based on the load forecast for the entire time-horizon (i.e., for all time periods) ahead of time; and finally employing corrective control action to monitor and modify the optimal plan in real-time. A fully connected artificial neural network (ANN) model is developed for forecasting the kW requirement for hybrid electric bus based on inputs like climatic conditions, passenger load, road inclination, etc. The ANN model is trained using back-propagation algorithm employing improved optimization techniques like projected Lagrangian technique. The pre-scheduler is based on a Goal-Programming (GP) optimization model with noise, pollution and fuel usage as the three objectives. GP has the capability of analyzing the trade-off among the conflicting objectives and arriving at the optimal activity levels, e.g., throttle settings. The corrective control action or the third sub-task is formulated as an optimal control model with inputs from the real-time data base as well as the GP model to minimize the error (or deviation) from the optimal plan. These three activities linked with the ANN forecaster proving the output to the GP model which in turn produces the pre-schedule of the optimal control model. Some preliminary results based on a hypothetical test case will be presented for the load forecasting module. The computer codes for the three modules will be made available fe adoption by bus operating agencies. Sample results will be provided using these models. The software will be a useful tool for supporting the control systems for the Electric Bus project of NASA.

Momoh, James↗

NASA NTRS1983

Automated distribution system management for multichannel space power systems

A NASA sponsored study of space power distribution system technology is in progress to develop an autonomously managed power system (AMPS) for large space power platforms. The multichannel, multikilowatt, utility-type power subsystem proposed presents new survivability requirements and increased subsystem complexity. The computer controls under development for the power management system must optimize the power subsystem performance and minimize the life cycle cost of the platform. A distribution system management philosophy has been formulated which incorporates these constraints. Its implementation using a TI9900 microprocessor and FORTH as the programming language is presented. The approach offers a novel solution to the perplexing problem of determining the optimal combination of loads which should be connected to each power channel for a versatile electrical distribution concept.

Fleck, G. W.↗

NASA NTRS1982

Development of management technology for large power systems

Autonomous power management has been proposed as a method to perform optimization of power subsystem performance in connection with the management of multikilowatt space platforms. A concept for a 250-kW utility-type power subsystem was developed. A Cassegrain concentrator solar array primary source is conditioned by a solar array switching unit which supplies seventeen 220 +20 Vdc power channels. A power management subsystem provides the monitoring and control of the overall electrical power subsystem. The discussed system concept for autonomous management of high power space platforms utilizes on-board microprocessors in a decentralized data management architecture. A data bus protocol and a data bus contention resolution scheme were selected in conjunction with the dencentralized management architecture.

Decker, D. K.↗

NASA NTRS2023

Modeling and Simulation of a Parallel Hybrid Electric Regional Aircraft for the Electrified Powertrain Flight Demonstration (EPFD) Program

This paper presents a parametric modeling and integrated aircraft sizing and synthesis approach for a charge depleting parallel hybrid electric architecture. The developed models are integrated within the baseline thin-haul and regional aircraft. In addition to the physical architecture, different modes of operation enabled by propulsion system electrification are also modeled parametrically. The modes of operation presented in this paper are the peak power shaving, climb power electric boost, in-flight battery recharging, and electric taxi. The sizing of the powertrain and the aircraft are performed within the multidisciplinary analysis and optimization environment, E-PASS. The consideration of the physical system and its operation together provides a holistic approach where the propulsion system and the airframe are designed under an optimized power and energy management strategy. The parametric nature of the work enables the design space exploration for electrification and lays the groundwork for future technology projection and uncertainty quantification studies. The developed capability is generic and can be applied on other aircraft classes. The work is done as part of the Electrified Powertrain Flight Demonstration program.

electrified powertrain flight demonstration↗

NASA NTRS1995

Artificial neural network application for space station power system fault diagnosis

This study presents a methodology for fault diagnosis using a Two-Stage Artificial Neural Network Clustering Algorithm. Previously, SPICE models of a 5-bus DC power distribution system with assumed constant output power during contingencies from the DDCU were used to evaluate the ANN's fault diagnosis capabilities. This on-going study uses EMTP models of the components (distribution lines, SPDU, TPDU, loads) and power sources (DDCU) of Space Station Alpha's electrical Power Distribution System as a basis for the ANN fault diagnostic tool. The results from the two studies are contrasted. In the event of a major fault, ground controllers need the ability to identify the type of fault, isolate the fault to the orbital replaceable unit level and provide the necessary information for the power management expert system to optimally determine a degraded-mode load schedule. To accomplish these goals, the electrical power distribution system's architecture can be subdivided into three major classes: DC-DC converter to loads, DC Switching Unit (DCSU) to Main bus Switching Unit (MBSU), and Power Sources to DCSU. Each class which has its own electrical characteristics and operations, requires a unique fault analysis philosophy. This study identifies these philosophies as Riddles 1, 2 and 3 respectively. The results of the on-going study addresses Riddle-1. It is concluded in this study that the combination of the EMTP models of the DDCU, distribution cables and electrical loads yields a more accurate model of the behavior and in addition yielded more accurate fault diagnosis using ANN versus the results obtained with the SPICE models.

Momoh, James A.↗

NASA NTRS2026

A Modular Conjugate Heat Transfer Optimization Framework for Thermal Management of Electric Aircraft

Conjugate heat transfer (CHT) analysis and optimization is a powerful method for improving thermal management, as it simultaneously resolves the temperature distribution in both fluid and solid domains. This paper presents a modular, discrete adjoint-based CHT optimization capability integrated within the OpenMDAO/MPhys framework. A unique feature of the proposed framework is its flexibility to extend to multidisciplinary optimization, including aero-structural-thermal applications. The fluid domain is modeled using a finite-volume Computational Fluid Dynamics (CFD) solver, and the solid domain with a conduction heat transfer solver. A mixed Neumann-Dirichlet boundary condition is developed to enable full submersion of the solid geometry within the fluid domain, while ensuring consistent temperature and heat flux coupling at the CHT interface. Gradient-based optimization is performed; the gradients are efficiently computed using the discrete adjoint solvers implemented in DAFoam. To demonstrate the method, this paper considers two cases related to electric aircraft thermal management: a U-bend heat exchanger and an actively cooled battery pack. The U-bend case aims to minimize pressure loss while maximizing heat flux by changing the pipe geometry. The optimized design reduces pressure loss by 52.7% and increases total heat flux by 2.3%. In the battery pack case, a 3-by-3 cell configuration is cooled by ambient airflow, with constant heat generation prescribed in the cells. The battery casing shape serves as the design variable, and the objective function is a weighted sum of pressure loss and pack weight, subject to a maximum temperature constraint. The optimized design achieves a 44.6% reduction in pressure loss and a 1.5% reduction in weight, while satisfying the thermal constraint. To ensure the reliability of the optimized designs, this study validates coarse-mesh, steady-state predictions against fine-mesh unsteady simulations, demonstrating consistency within acceptable errors. This work demonstrates the potential of the developed framework to enable rapid, high-fidelity design of thermal management systems for electric aircraft.

heat transfer↗

NASA NTRSDate not supplied

On the Moon to Stay: Challenges Presented to Power Electronics Technology by Sustained Operations on the Lunar Surface

NASA’s Artemis Program seeks not only to return humans to the Moon for the first time since the 1970’s but also to provide the technological basis for infrastructure that will enable permanent and expanding scientific and industrial exploitation of the Lunar surface. The primary purpose of this infrastructure is to generate and distribute power to a diverse and growing range of scientific and industrial assets, and the keys to success for this function are power management and control circuits that are highly reliable and maintainable for a decade of operation in the extreme thermal, radiation, and dust environment of the Lunar surface. While various combinations of wide band gap semiconductors, electronic devices, circuit topologies, and shielding schemes have been successfully developed for mission environments ranging from low Earth orbit to the Jovian system, power management technology has not been optimized to meet the full combination of mission requirements for the Lunar surface. To accomplish this, NASA requests the dedicated focus of the power electronics industry.

semiconductors↗

NASA NTRS2012

Retrofits Convert Gas Vehicles into Hybrids

Successful space missions can rarely be attributed to a single thing. Rather, they are the result of a system of systems: integrated elements functioning effectively in their individual roles and together with related components, then those systems interacting with and supporting other systems to form a collaborative whole - from the spacecraft itself to the engineering and research teams that design and build it. An example is found in spacecraft power systems. Unlike a gas-powered car or a battery-powered laptop, most spacecraft are powered by multiple energy sources - such as photovoltaic panels, fuel cells, and batteries - working in tandem to ensure the spacecraft functions throughout the course of a mission. As with any system, the appropriate combination of elements and the method of their management are key to high performance and efficiency. One initiative at Glenn Research Center, the Hybrid Power Management (HPM) program, focused on joining new and mature technologies for optimal power systems applications in space and on Earth, with the goal not only to develop ultra-efficient space power systems, but to advance HPM to address global energy issues. The HPM program emerged from Glenn s long history of electric vehicle research dating back to the 1970s, including the NASA Hybrid Electric Transit Bus (HETB) project in the 1990s, which was the largest vehicle to use supercapacitor energy storage.

Source record↗

NASA NTRSDate not supplied

Parallel Hybrid Turboprop Performance Modeling and Optimization

NASA’s Electrified Powertrain Flight Demonstration (EPFD) project conducts ground and flight tests of integrated Megawatt (MW) class hybrid-electric powertrain systems on regional turboprop aircraft demonstrators. To meet the increased demand for assessment of potential capabilities and benefits from these novel vehicle configurations, NASA is developing tooling and models to estimate the performance of hybridized regional turboprops. This paper covers the development of a parametrically driven performance model for a De Havilland Canada Dash 8-400 (Q400) regional turboprop integrated with a novel parallel hybrid architecture using the Gascon framework. Gascon is a modern reimplementation of the General Aviation Synthesis Program (GASP) built using the Condor mathematical modeling framework in Python. Within Gascon, a parametric representation of the parallel hybrid architecture was synthesized, which features the electric motor coupled to the power turbine. This capability allows for in-the-loop optimization of the parametric parallel hybrid architecture to characterize the mission capabilities and fuel savings of the design and determine optimal power scheduling strategies for efficient electric power management for a given mission. The study shows that a fuel savings of up to 20% can be achieved, but that increased fuel savings comes at the expense of payload capacity.

Gascon↗

NASA NTRSDate not supplied

Parallel Hybrid Turboprop Performance Modeling and Optimization

Gascon↗

NASA NTRS1989

Space Station Freedom photovoltaic power module design status

Electric power generation for the Space Station Freedom will be provided by four photovoltaic (PV) power modules using silicon solar cells during phase I operation. Each PV power module requires two solar arrays with 32,800 solar cells generating 18.75 kW of dc power for a total of 75 kW. A portion of this power will be stored in nickel-hydrogen batteries for use during eclipse, and the balance will be processed and converted to 20 kHz ac power for distribution to end users through the power management and distribution system. The design incorporates an optimized thermal control system, pointing and tracking provision with the application of gimbals, and the use of orbital replacement units to achieve modularization. The design status of the PV power module, as derived from major trade studies, is discussed at hardware levels ranging from component to system. Details of the design are presented where appropriate.

Jimenez, Amador P.↗

NASA NTRS1989

Space Station Freedom photovoltaic power module design status

Electric power generation for Space Station Freedom will be provided by four photovoltaic (PV) power modules using silicon solar cells during Phase 1 operation. Each PV power module requires two solar arrays with 32,800 solar cells generating 18.75 kW of dc power for a total of 75 kW. A portion of this power will be stored in nickel-hydrogen batteries for use during eclipse, and the balance will be processed and converted to 20 kHz ac power for distribution to end users through the power management and distribution system. The design incorporates an optimized thermal control system, pointing and tracking provision with the application of gimbals, and the use of orbital replacement units (ORU's) to achieve modularization. Design status of the PV power module, as derived from major trade studies, is discussed at hardware levels ranging from component to system. Details of the design are presented where appropriate.

Jimenez, Amador P.↗

NASA NTRS2004

Weight Optimization of Active Thermal Management Using a Novel Heat Pump

Efficient lightweight power generation and thermal management are two important aspects for space applications. Weight is added to the space platforms due to the inherent weight of the onboard power generation equipment and the additional weight of the required thermal management systems. Thermal management of spacecraft relies on rejection of heat via radiation, a process that can result in large radiator mass, depending upon the heat rejection temperature. For some missions, it is advantageous to incorporate an active thermal management system, allowing the heat rejection temperature to be greater than the load temperature. This allows a reduction of radiator mass at the expense of additional system complexity. A particular type of active thermal management system is based on a thermodynamic cycle, developed by the authors, called the Solar Integrated Thermal Management and Power (SITMAP) cycle. This system has been a focus of the authors research program in the recent past (see Fig. 1). One implementation of the system requires no moving parts, which decreases the vibration level and enhances reliability. Compression of the refrigerant working fluid is accomplished in this scheme via an ejector.

Lear, William E.↗

NASA NTRSDate not supplied

NASA POWER: Providing Analysis-Ready, Cloud-Optimized Data for AI /ML Training and Applications in Earth Science

As global demand for sustainable development grows, the integration of Earth Observation (EO) data into decision making frameworks has become a primary objective for the scientific community. The NASA Prediction of Worldwide Energy Resources (POWER) project serves as a bridge between NASA EO data and the specialized needs of the renewable energy, sustainable infrastructure and agroclimatology communities. In this poster presentation we will present an overview of POWER data products and services along with its use in diverse research to decision-making workflows. By providing over 40 years of high-resolution historical, hourly and daily solar and meteorological data, POWER transforms satellite observations and global model reanalysis into actionable, Analysis-Ready Dataset (ARD). Currently, the project delivers over 250 industry-friendly parameters to the users from different NASA datasets like CERES SYN1Deg, MERRA-2, and IMERG alongside downscaled CMIP6 climate model data, fulfilling over 16 million requests from 50,000 unique users monthly. To ensure data quality and traceability, these parameters are rigorously validated against the ground-based observations from the Baseline Surface Radiation Network (BSRN) and the Global Surface Summary of the Day (GSOD) – these results will be discussed in the presentation. A newly introduced web-based PaRameter Uncertainty ViEwer (PRUVE) tool will be presented that provides an online validation platform to the users that benchmarks satellite-based and assimilation data products against these surface measurements. To reduce technical barriers to data adoption, POWER data is accessible through RESTful APIs, ESRI ArcGIS Image Services, a web-based Data Access Viewer tool, allowing users to visualize, validate and apply the dataset. For efficient data delivery POWER data is cloud-optimized into Zarr datastore accessible through NASA managed Amazon S3 ensures high-performance allowing users to integrate EO directly into operational pipelines. These customized services will be presented. Use cases from application will be presented from the energy sector - such as for design of generation systems, performance monitoring of solar power plants, in infrastructure sector- optimizing building energy efficiency and thermal comfort, in agriculture – such as driving crop simulation and yield forecasting models to enable climate resilient farming. Furthermore, the shift toward machine learning (ML) in EO research that has positioned POWER as a key provider for training datasets which will be discussed. Use-cases will be presented to showcase how NASA data is enabling the development of predictive tools for climate variability and resource management. The poster will present POWER’s future plans including technology development to enhance data traceability and reproducibility and improving I/O performance to support the rapid integration of new EO products, ensuring that POWER remains a robust scalable backend for the evolving landscape of AI-driven Earth Science. Additionally, POWER is developing an AI Agent and an MCP-Server to enable industry AI-Agentic workflows.

Neha Khadka↗

NASA NTRS2006

Development of Efficient Mid-IR Interband Cascade Lasers for Chemical Sensing

Significant progress has been made: Above room temperature (up to 350K) pulsed operation has been demonstrated. CW operation temperature has been raised up to 237 K. DFB IC lasers have been applied for the detection of trace gases such as CH4, HCl, and H2CO. Devices have been operated continuously over several hundred hours without degradation. Main challenge remains for many potential applications of ICLs. CW operation at room temperature and above with significant output powers. There is still significant room for improvement: Laser design and material quality - many parameters have not been optimized. Device fabrication and thermal management (passivation, better mounting, etc.). Significantly higher output power can be achieved with laser arrays.

diode lasers↗

NASA NTRS1993

NEP systems model

A new nuclear electric propulsion (NEP) systems analysis code is discussed. The new code is modular and consists of a driver code and various subsystem models. The code models five different subsystems: (1) reactor/shield; (2) power conversion; (3) heat rejection; (4) power management and distribution (PMAD); and (5) thrusters. The code optimizes for the following design criteria: minimum mass; minimum radiator area; and low mass/low area. The code also optimizes the following parameters: separation distance; temperature ratio; pressure ratio; and transmission frequency. The discussion is presented in vugraph form.

George, Jeffrey A.↗

NASA NTRS1994

Predictability in space launch vehicle anomaly detection using intelligent neuro-fuzzy systems

Included in this viewgraph presentation on intelligent neuroprocessors for launch vehicle health management systems (HMS) are the following: where the flight failures have been in launch vehicles; cumulative delay time; breakdown of operations hours; failure of Mars Probe; vehicle health management (VHM) cost optimizing curve; target HMS-STS auxiliary power unit location; APU monitoring and diagnosis; and integration of neural networks and fuzzy logic.

Gulati, Sandeep↗