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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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Finite Element method (FEM) Array Control Software (FACS) is a user-friendly, interactive software package designed to provide a user interface to the FEM. The use of the FACS commands are described.
A deterministic state-of-charge (SOC) balancing approach software control code is introduced as an integral secondary management to primary control layer of an islanded small microgrid or nanogrid system made up of multiple grid-forming inverter/battery/solar combination systems, where each set of batteries with each inverter are on independent DC buses (i.e. non-paralleled on the DC sides). A DERMS-level control approach, algorithm and automation controller program was developed to improve coordination and enable microgrid asset compliance and SOC balancing, enabling provision of a system-level power stability support architecture, load support, and asset scalability. The architecture is configured to treat each unit or micro/nano-grid as a node in a microgrid network, allowing for autonomous DERMS control regarding load and SOC balancing and power stability. As the network grows with the addition of units, greater coordination efforts may be required. The ideal small network microgrid ranges from 2-10 inverter/battery units before additional control parameters must be considered in the existing architecture. The control approach focuses on a deterministic state-of-charge analysis as the primary level control process followed by a secondary control loop using a forced frequency-watt droop strategy to conform off-the-shelf components into behaving under a leader-follower configuration. Adopting this control scheme has been shown to allow for a balanced, unit-coordinated microgrid network, enabling stable power flow. The deterministic state-of-charge approach is introduced as an integral primary control layer of an islanded small network microgrid. A standard strategy for SOC balancing is implementing a battery management system (BMS) to control SOC on the DC side. An alternative approach is to determine how to coordinate sending and receiving power on the AC side with multiple units. The latter approach assesses all the integrated units in the microgrid network. Once the individual units are identified, further system data is required to calculate each unit's total kWh, provided information about its capability to supply or consume kWh and availability. The secondary control layer in the multi-layered small network microgrid methodology uses the primary layer’s decision to initiate frequency setpoint changes, initializing the SOC balancing. The secondary control layer considers numerous system-dependent variables to enable a charging and discharging profile based on adjustable frequency setpoints. The combined architecture will result in stable, coordinated power flow enhancing an AC microgrid's functionalities.
On December 4th, 1998 at 3:36 AM STS-88 (the space shuttle Endeavor) was launched with the "Node 1 Unity Module" in its payload bay. After working on the Space Station program for a very long time, that launch was one of the most beautiful sights I had ever seen! As the Shuttle proceeded to rendezvous with the Russian American module know as Zarya, I returned to Houston quickly to start monitoring the activation of the software I had spent the last 3 years working on. The FGB module (also known as "Zarya"), was grappled by the shuttle robotic arm, and connected to the Unity module. Crewmembers then hooked up the power and data connections between Zarya and Unity. On December 7th, 1998 at 9:49 PM CST the Node Control Software was activated. On December 15th, 1998, the Node-l/Zarya "cornerstone" of the International Space Station was left on-orbit. The Node Control Software (NCS) is the first software flown by NASA for the International Space Station (ISS). The ISS Program is considered the most complex international engineering effort ever undertaken. At last count some 18 countries are active partners in this global venture. NCS has performed all of its intended functions on orbit, over 200 miles above us. I'll be describing how we built the NCS software.
INL has performed simplified model testing using a variable in the software control program to compare with the testing performed at ORNL, which uses hardware to modify the control signal. The INL tests compared well with the ORNL tests, showing similar stress and strain values, as well as similarly shaped hysteresis loops. This demonstrates that possibility of performing simplified model testing without any hardware modifications.
The Ada language software developed to control the NASA Lewis Research Center's Power Management and Distribution testbed is described. The testbed is a reduced-scale prototype of the electric power system to be used on space station Freedom. It is designed to develop and test hardware and software for a 20-kHz power distribution system. The distributed, multiprocessor, testbed control system has an easy-to-use operator interface with an understandable English-text format. A simple interface for algorithm writers that uses the same commands as the operator interface is provided, encouraging interactive exploration of the system.
Software interface for controlling and collecting data from the Open PV Electrical Tool (OPET) device. This repository contains everything relating to the control of the OPET device including source code. If you are looking for the hardware or firmware software repositories, links are below: https://github.com/NREL/opet-hardware https://github.com/NREL/opet-firmware
This research discusses development of a software-controlled laboratory instrument based spread spectrum time domain reflectometry system (SSTDR). This constitutes one task within PNNL’s Light Water Sustainability Program (LWRS) whose mission includes advancing nondestructive examination (NDE) techniques for off-line and on-line in-situ cable condition monitoring. In 2022, PNNL evaluated SSTDR for detection and characterization of a number of cable anomalies (Glass et al. 2022). The review included comparison of SSTDR to Frequency Domain Reflectometry (FDR) techniques which have enjoyed encouraging feedback and are starting to be used in nuclear power plants for periodic cable condition monitoring of cable systems as part of the plant’s overall cable aging management program. The FDR test introduces a broad-band chirp onto the cable at the cable end then listens for any reflection from a change of impedance along the cable caused by a damaged conductor or insulation, splices, contact with moisture, or other cable anomalies. The signal is captured in the frequency domain then transformed back to the time domain using an inverse Fourier transform (IFT). Based on the velocity of propagation, the impedance response signal is plotted against distance along the cable. Peak locations along the X-axis indicate the distance along the cable where a portion of the signal has been reflected back to the instrument as a result of a cable anomaly. The FDR test is considered the gold standard of reflectometry however it does require the cable to be de-energized to perform the test. The LIVEWIRE commercial SSTDR produces a similar plot to the FDR however all processing is in the time domain. A pseudo-random noise code (PN code) is input onto the cable conductor and the instrument listens for any reflected response from cable anomalies. The SSTDR processes the signal as an autocorrelation comparing the input PN code to any reflected signal detected. The autocorrelation analysis for thermal aging, water and water ingress detection, ground fault and phase-to-phase fault detection at various locations along the cable and with the cable attached and detached from a motor load, and on both energized and un-energized conditions were performed. These results were contrasted to Frequency Domain Reflectometry (FDR) measurements of the un-energized cable. Results were encouraging but indicated more work was warranted – particularly with the SSTDR, it seemed that the insulation damage would likely be better evaluated with multiple bandwidth cable tests particularly including larger bandwidths than were possible with the current commercial instrument. The commercial instrument’s bandwidth was set at 6, 12, 24, and 48MHz but note that SSTDR and FDR definitions of bandwidth trend similarly but are not the same. The FDR response could be more broadly adjusted, and the bandwidth of 100 to 500 MHz produced the best responses. FDR responses to anomalies were clearer than SSTDR responses and indications were that a broader bandwidth SSTDR may lead to improved SSTDR detection capability. This project used a laboratory instrument based SSTDR (primarily using an Arbitrary Waveform Generator (AWG) and a digital oscilloscope plus Python in-house software) that allowed software adjustment of the SSTDR bandwidth, window functions applied to the exciting Pseudo-random Noise (PN) code plus and other aspects of the SSTDR signal processing. Hereafter, this will be referred to as the PNNL SSTDR. Evaluating specific performance of the PNNL SSTDR is left to a separate report. This report documents hardware and software development to produce the SSTDR cable test system.
Idaho National Laboratory, in collaboration with Invensys, performed a laboratory assessment on Invensys Foxboro Control Software. During this assessment, vulnerabilities were discovered, evaluated, and mitigation strategies developed.
While most software development for control systems is directed at what the system is supposed to do (i.e., function), high-consequence controls must account for what the system is not supposed to do (i.e., safety, security and reliability requirements). A Domain Specific Language (DSL) for high-consequence digital controls is proposed. As with similar tools for the design of controls, the DSL will have plug-in modules for common controller functions. However, the DSL will also augment these modules with attendant "templates" that aid in the proof of safety, security and reliability requirements, not available in current tools. The object is to create a development methodology that makes construction of high-assurance control systems as easy as controls that are designed for function alone.
Real-Time Innovations, Inc. (RTI) collaborated with Ames Research Center, the Jet Propulsion Laboratory and Stanford University to leverage NASA research to produce ControlShell software. RTI is the first "graduate" of Ames Research Center's Technology Commercialization Center. The ControlShell system was used extensively on a cooperative project to enhance the capabilities of a Russian-built Marsokhod rover being evaluated for eventual flight to Mars. RTI's ControlShell is complex, real-time command and control software, capable of processing information and controlling mechanical devices. One ControlShell tool is StethoScope. As a real-time data collection and display tool, StethoScope allows a user to see how a program is running without changing its execution. RTI has successfully applied its software savvy in other arenas, such as telecommunications, networking, video editing, semiconductor manufacturing, automobile systems, and medical imaging.
C3PU sets up a model predictive control formulation for the optimal charging control of battery packs and can be deployed for real-time operation on an embedded microprocessor. C3PU uses electrochemical and thermal models of battery packs to predict the charging trajectories of the battery pack over a time horizon under different operating conditions. It then selects the optimal charging trajectory such that a pre-defined objective is minimized, which in the present state of the code is to minimize the charging duration of the battery pack. The optimal charging trajectory is obtained by solving an underlying mathematical problem. However, C3PU is flexible to incorporate other charging objectives. The underlying battery models can be swapped as well, as long as they follow certain mathematical properties. Mathematically, optimal control problems (in this case, optimally controlling the charging current of the battery pack) are computationally expensive. C3PU implements advanced numerical techniques, namely pseudo-spectral optimization, to reduce the computational burden of the underlying problem to solve. This allows for the problem to be solved in real-time in an embedded system. Once the optimal charging trajectory is computed over a time horizon, C3PU can package such data and send it out via appropriate communication protocols.
For long-duration automated operation of regenerative life support systems in space environments, there is a need for advanced integration and control systems that are significantly more reliable and safe, and that support error recovery and minimization of operational failures. This presentation outlines some challenges of hazardous space environments and complex system interactions that can lead to system accidents. It discusses approaches to hazard analysis and error recovery for control software and challenges of supporting effective intervention by safety software and the crew.
Flight path control in software system for Lunar Orbiter, discussing optimization program for midcourse aim point and lunar injection point
Flight path control in software system for Lunar Orbiter, discussing optimization program for midcourse aim point and lunar injection point
Recent research has highlighted the potential for solar to act as a zero-marginal-cost and zero-emission flexibility resource on the bulk power system when operated with advanced control systems. To increase the performance of these systems, leading technologies, including machine learning (ML) and hierarchical inverter set point allocation, have been developed by Latimer Controls, Inc. to estimate the headroom of large PV plants for grid operation and control; however, these technologies lack comprehensive validation under real-world application scenarios. Latimer Controls, Inc. received two voucher awards for research at a national laboratory from the Department of Energy American Made Solar Prize Round 6. The National Renewable Energy Laboratory (NREL) was selected to collaborate with Latimer staff to conduct a performance evaluation of Latimer PV control software. The NREL team will develop a hardware-in-the-loop (HIL) testbed to perform testing and validation of the Latimer PV control technology in a de-risked yet realistic testbed environment. Latimer and NREL worked together to analyze the test data, draw conclusions from the results, and disseminate the resulting scientific findings. In this CRADA work, we propose to test and validate the real-world application of the Latimer Control solution in an HIL environment. We evaluate the performance of different flexible solar technologies in responding to automatic generation control signals in a closed-loop fashion. In particular, a data-driven potential high limit (PHL) estimation is developed for large solar plants to accurately estimate their headroom so that they have fast and short-time regulation and control capability to participate in grid services and respond to grid signals in real time (e.g., AGC). This PHL estimation algorithm is embedded in a hardware power plant controller (PPC) and tested with an IEEE-39 bus system model developed in RTDS. To account for the varying cloud conditions and diverse inverter dispatches, we developed a 135-MW PV plant with detailed modeling of 27 individual PV modules and inverters using RTDS. The real-world communications used in such big plants, such as ModBus TCP/IP for inverter level and DNP3 for plant level, were developed to emulate the real-world applications in big PV plants. The ML-based PHL estimation method is tested under nine separate weather scenarios against the ‘reference-control’ solution, hereafter referred to as the baseline solution. The baseline method reserves a subset of inverters (reference group) to operate at their PHL at all times and dispatches only the remaining inverters (control group) at curtailed levels to fulfill the flexibility need. Despite being successfully piloted by NREL in California in 2017 and Chile in 2020, there exist two gaps in the state of the art to fully unlock the flexibility of PV plants: a. There is a trade-off between the PHL estimation accuracy and the flexibility range. b. There lacks granularity in the PHL estimation to capture the variation across inverters. The Latimer solution seeks to address these gaps by applying machine learning methods to improve PHL estimation accuracy while accounting for variability at every inverter. Performance metrics were taken from the 2023 Georgia Power CARES utility-scale RFP. The results demonstrate that the ML-based approach outperforms the traditional baseline method in PHL estimation accuracy for 7 of 9 scenarios. The average PHL error across the nine scenarios was 7.40% for the ML-based method, 2.06% less than the 9.46% PHL error average across scenarios that was exhibited by the baseline method. Additionally, the PHL error was below 5% for at least 95% of the testing interval for 3 of 9 tested intervals with the ML approach, whereas it did not achieve this metric for any of the baseline tests. Overall, simulation results indicate the superior performance of an ML-based approach compared to the conventional baseline reference-control approach, showcasing its potential to support grid stability and operational efficiency. This laboratory HIL testing using real PPC, representative power system simulation models in real-time with detailed PV plant and inverter models, and real-world communication protocols gives us confidence that this machine learning based PHL estimation algorithm works well in the hardware PPC and therefore de-risks future field commissioning. The end goal of this project is to advance grid technology to address the grid operation challenges brought by solar plant’s variability and uncertainties in power generation.
The Cassini Attitude and Articulation Control Subsystem (AACS) is responsible for determining and controlling the spacecraft attitude including instrument pointing, antenna pointing, and thrust vector pointing during velocity change maneuvers. The 12 year mission life, long round-trip light time, and extended periods of coast without continuous ground control drive the AACS flight software design in the directions of autonomy, fault tolerance, and modularity to accommodate planned upgrades in flight. The Cassini AACS Flight Software is depicted in increasing levels of detail using a Context Diagram, Architecture Diagrams (i.e., Dependency Diagrams), an Object Diagram for each object, and a Statechart (i.e., State Transition Diagram) for each object. The detail contained in the diagrams is enhanced and refined during the Requirements and Design Phases of both Subsystem and Software Development. Examples of all the diagrams as well as the criteria for object selection, the advantages of statecharts, and the ease of modifying the design to accommodate changes in scope are described.
The Exploration Systems Development (ESD) Standing Review Board (SRB) requested the NASA Engineering and Safety Center (NESC) conduct an independent review of the plan developed by Ground Systems Development and Operations (GSDO) for identifying models and emulators to create a tool(s) to verify their command and control software. The NESC was requested to identify any issues or weaknesses in the GSDO plan. This document contains the outcome of the NESC review.
The need to increase engineering productivity and decrease software life cycle costs in real-time system development establishes a motivation for a method of rapid prototyping. The design by iterative rapid prototyping technique is described. A tool which facilitates such a design methodology for the generation of embedded control software is described.