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DOE OSTI2022

Multi-modal Energy-optimal Trip Scheduling in Real-time (METS-R) for Transportation Hubs (Final Report)

This report summarizes the work performed under the award number EE0008524. The project develops the Multi-modal Energy-optimal Trip Scheduling in Real-time (METS-R) platform as the next-generation transportation solution based on autonomous electric vehicles (AEV) serving passenger trips from and to urban transportation hubs, to substantially reduce transportation energy consumption. Extensive data collection and analyses were first conducted to understand the demand patterns and energy consumption of hub-based on-road trips. Then, a data-driven framework that consists of an analytical module and a simulation module was proposed. For the analytical module, five planning + operation tools were developed to support the planning and energy-efficient operations of urban AEV services: the charging station planning that robotically allocates charging supplies based on the stationary charging demand distribution; the transit planning and demand adaptive scheduling model that efficiently generates\ candidate transit routes from hubs to other places and dynamically adjusts the transit time table to fit the current demand; the online energy-efficient routing that learns the energy-optimal paths from observations of link-level energy consumption in real-time; the hub-based ridesharing that matches trip requests together with account for the uncertainty of future trip demand and vehicle supply; and finally, the integrated demand prediction and anomaly detection pipeline that leverages the flight/train time table and support other planning/operation tools. To demonstrate the performance of these tools, a scalable high-performance agent-based simulator was built. We divided the urban space into multiple service zones where each zone was considered as an agent for passenger generation and vehicle charging. Two types of AEV agents were coded to model two types of mobility services: AEV taxi and AEV transit. For the AEV taxi, the team implemented the functions of pickup/drop-off passengers, energy-efficient routing, ridesharing, fleet rebalancing, and recharging. For the AEV bus, the team implemented the functions of demand-adaptive route scheduling, passenger boarding, and recharging. A high-performance computing framework was introduced to receive various profiling information (such as link energy updates, vehicle speed) from the simulator instances and communicate the operational commands back to the instances. The numerical experiments show that each of the proposed operational algorithms can reduce energy consumption and improve system efficiency. Furthermore, there exists the need to collectively consider multiple planning + operational strategies as multiple strategies can influence each other in terms of performance impacts. Recommendations for future work related to AEV planning and simulation are discussed.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2024

A Data Processing Pipeline To Extract A Knowledge Graph From Sec Documents For Socio-technical Analysis Of Critical Infrastructure Influence

The code is written in Python and consists of the following pipeline that is implemented in Apache Airflow. This pipeline intends to understand the companies that are directly or indirectly involved with a type of critical infrastructure system at some point in that system's lifecycle. The pipeline takes a configuration file that specifies a list of initial companies to consider, a geographic region of interest (disk) expressed as a latitude/longitude point and distance, and a set of SEC form types from which to extract entities and relations. There are three main components to this pipeline as currently implemented: Social Network Extraction, Critical Infrastructure Network Extraction, and Inference and Fusion. First, Social Network Extraction, implemented as the `organizations_sec` component of the workflow graph queries the SEC EDGAR webservice using the list of initial companies from the configuration file. Given this, it extracts metadata that documents the number of each type of form for the given set of companies and their location. This forms metadata represents a catalog of data sources for the extracted social network knowledge graph. The pipeline then downloads these forms from the website and saves them in a build directory for further processing. These documents are then parsed for entities and relations. Second, the Critical Network Extraction component extracts entities and relations for a critical infrastructure sector. Currently, we focus on Electric Vehicle charging stations and this information is available via the Department of Energy (DOE) database on fueling stations maintained by NREL. Third, the Inference and Fusion component relates the social network graph to the critical infrastructure graph in order to understand the impact of a company within a geographic region. Relations include ownership of the EV Charging Station asset as well as maintenance/ownership of the EV payment networks. The fused network can be represented in many ways and currently we emit a knowledge graph.

Weaver, GabrielA.↗

DOE OSTI2021

Applications of Digital Twin System in a Smart City System with Multi-Energy

With the increasing number of electric vehicles (EV), the smart transportation system is becoming more closely related to the smart energy system in a smart city. However, because of the high complexity, dynamics, and large-scale of these two systems, it is challenging to study their operation problems systematically, especially in severe conditions, e.g., the 2021 winter Texas power traffic crisis. With artificial intelligence, federated learning, edge computing, and automatic control, a digital twin based smart city is proposed in this paper and it focuses on two applications: smart transportation and smart energy grid. Both systems are presented in a structured design manner with several components in the digital twin system, which also contains many real-implementations of different scenarios. The proposed digital twin of a smart city provides a potential clue for the problems mentioned above.

artificial intelligence↗

DOE OSTI2022

Macro Analysis to Estimate Electric Vehicles Fast-Charging Infrastructure Requirements in Small Urban Areas

Electric vehicles (EVs) are known to reduce emissions and fossil fuel dependency. However, the limited range, long charging time, and inadequate charging infrastructure have hampered the adoption of EVs. The current EV charging infrastructure planning studies and tools require detailed information, extensive resources, and skills that can be a significant barrier to urban areas for finding the required charging infrastructure to support a targeted EV market share. This study generates regression models to estimate the number of direct current fast charging stations and the chargers to support the EV charging demand for urban areas. These models provide macro-level estimates of the required infrastructure investment in urban areas, which can be easily implemented by policy-makers and city planners. This study incorporates data obtained from applying a disaggregate optimization-based charger placement model, developed recently by the same authors, for multiple case studies to generate the required data to calibrate the macro-level models, in the state of Michigan. This simulated data set includes the number of charging stations and chargers for each market share, technology advancement scenario, and the transportation network topology. The results show that the number of charging stations reduces with battery size and charging power and increases with EV market share and the road network lane length. The number of chargers reduces with charging power, whereas it increases with battery size, EV market share, and vehicle miles traveled in the system. The model developed here can be applied to any state having urban characteristics and weather conditions similar to Michigan.

Engineering↗

NASA NTRS2001

Baseline Testing of The EV Global E-Bike

The NASA John H. Glenn Research Center initiated baseline testing of the EV Global E-Bike as a way to reduce pollution in urban areas, reduce fossil fuel consumption and reduce Operating costs for transportation systems. The work was done Linder the Hybrid Power Management (HPM) Program, which includes the Hybrid Electric Transit Bus (HETB). The E-Bike is a state of the art, ground up, hybrid electric bicycle. Unique features of the vehicle's power system include the use of an efficient, 400 W. electric hub motor and a 7-speed derailleur system that permits operation as fully electric, fully pedal, or a combination of the two. Other innovative features, such as regenerative braking through ultracapacitor energy storage are planned. Regenerative braking recovers much of the kinetic energy of the vehicle during deceleration. The E-Bike is an inexpensive approach to advance the state of the art in hybrid technology in a practical application. The project transfers space technology to terrestrial use via nontraditional partners, and provides power system data valuable for future space applications. A description of the E-bike, the results of performance testing, and future vehicle development plans is the subject of this report. The report concludes that the E-Bike provides excellent performance, and that the implementation of ultracapacitors in the power system can provide significant performance improvements.

Eichenberg, Dennis J.↗

DOE OSTI2025

Automation for Electric Vehicle Battery Pack Disassembly

Battery‐electric vehicles (EVs) are growing exponentially. The demand for these batteries is expected to increase sevenfold by 2035. The EV batteries reach their end of life when the capacity fades to 70%–80% of new, with some being removed from the primary applications with even lower levels of degradation. These batteries can be used in less demanding applications. The disassembly process is currently manual, slow, unsafe, and expensive. Automation is needed to increase the throughput. EV battery packs feature various continually changing designs and form factors, which limit the usefulness of deterministically programmed robotic solutions. The conceptual robotic disassembly of EV batteries has attracted the attention of researchers. However, while many approaches have been proposed, practical implementations are lacking. Here, we review proposed concepts for EV battery disassembly and describe the selected approach, with elements of partial solutions validated in a laboratory setting, including the selection of commercial solutions, the development of custom end effectors, and methodologies for detection, localization, and classification of fasteners. The computer vision tasks employed an overhead 2D camera to detect the type of battery pack and approximate localization of fasteners, and a 3D camera mounted on the robotic arm for precise localization (position and tilt) and classification.

Islam, Abu [Rochester Inst. of Technology, Rochest↗

DOE OSTI2026

Comparison of CNN-Based Image Classification Approaches for Implementation of Low-Cost Multispectral Arcing Detection

Camera-based sensing has benefited in recent years from developments in machine learning data processing methods, as well as improved data collection options such as Unmanned Aerial Vehicles (UAV) mounted sensors. However, cost considerations, both for the initial purchase of sensors as well as updates, maintenance, or potential replacement if damaged, can limit adoption of more expensive sensing options for some applications. To evaluate more affordable options with less expensive, more available, and more easily replaceable hardware, we examine the use of machine learning-based image classification with custom datasets, utilizing deep learning based-image classification and the use of ensemble models for sensor fusion. Utilizing the same models for each camera to reduce technical overhead, we showed that for a very representative training dataset, camera-based detection can be successful for detection of electrical arcing. We also use multiple validation datasets, based on conditions expected to be of varying difficulty, to evaluate custom data. These results show that ensemble models of different data sources can mitigate risks from gaps in training data, though the system will be less redundant for those cases unless other precautions are taken. We found that with good quality custom datasets, data fusion models can be utilized without specialization in design to the specific cameras utilized, allowing for less specialized, more accessible equipment to be utilized as multispectral camera components. This approach can provide an alternative to expensive sensing equipment for applications in which lower-cost or more easily replaceable sensing equipment is desirable.

convolutional neural networks↗

NASA NTRS2011

Modeling Ionosphere Environments: Creating an ISS Electron Density Tool

The International Space Station (ISS) maintains an altitude typically between 300 km and 400 km in low Earth orbit (LEO) which itself is situated in the Earth's ionosphere. The ionosphere is a region of partially ionized gas (plasma) formed by the photoionization of neutral atoms and molecules in the upper atmosphere of Earth. It is important to understand what electron density the spacecraft is/will be operating in because the ionized gas along the ISS orbit interacts with the electrical power system resulting in charging of the vehicle. One instrument that is already operational onboard the ISS with a goal of monitoring electron density, electron temperature, and ISS floating potential is the Floating Potential Measurement Unit (FPMU). Although this tool is a valuable addition to the ISS, there are limitations concerning the data collection periods. The FPMU uses the Ku band communication frequency to transmit data from orbit. Use of this band for FPMU data runs is often terminated due to necessary observation of higher priority Extravehicular Activities (EVAs) and other operations on ISS. Thus, large gaps are present in FPMU data. The purpose of this study is to solve the issue of missing environmental data by implementing a secondary electron density data source, derived from the COSMIC satellite constellation, to create a model of ISS orbital environments. Extrapolating data specific to ISS orbital altitudes, we model the ionospheric electron density along the ISS orbit track to supply a set of data when the FPMU is unavailable. This computer model also provides an additional new source of electron density data that is used to confirm FPMU is operating correctly and supplements the original environmental data taken by FPMU.

Gurgew, Danielle N.↗

NASA NTRS2013

Design of the Core Stage Inter-Tank Umbilical {CSITU) Compliance Mechanism

Project Goals: a) Design the compliance mechanism for the CSITU system to a 30% level -3D models completed in Pro/Engineer -Relevant design analysis b) Must meet all system requirements and establish basis for proceeding with detailed design. Tasks to be completed: A design that meets requirements for the 30% design review, 01/16/2013. Umbilical arms provide commodities to the launch vehicle prior to T-0. Commodities can range anywhere from hydraulics, pneumatics, cryogenic, electrical, ECS, etc ... Umbilicals commonly employ truss structures to deliver commodities to vehicle. Common configurations include: -Tilt-up -Swing Arm -Hose Drape -Drop Arm Umbilical arms will be mounted to Mobile Launch Platform. SLS currently has 9 T-0 umbilical arms. The compliance refers to the ability of the umbilical to adjust to minor changes in vehicle location. The compliance mechanism refers to the mechanism on the ground support equipment {GSE) that compensates for these changes. For the CSITU, these minor changes, or vehicle excursions, can be up to +4 in. Excursions refer to movements of the vehicle caused by wind loads and thermal expansion. It is ideal to have significant vertical compliance so a passive secondary release mechanism may be implemented.

Smith, Kurt R.↗

DOE OSTI2024

Tutorial - Electric Motor and Integrated Traction Drive Thermal Management

The share of vehicles with fully electric propulsion systems is constantly increasing, and so is their traction drive power. The continuous push to increase power of electric vehicle (EV) traction drives necessitates their efficient cooling to prevent damage to temperature sensitive components of the drive system and achieving higher power outputs in a smaller footprint. With increasing power and power density of electric traction drives, their thermal management is becoming increasingly challenging. This tutorial will provide an overview of thermal management approaches for electric motors and power electronics in EV applications. It will review examples of current industry solutions for power-dense electric motor cooling, power electronics (inverter) cooling, their integration concepts and thermal management system solutions. We'll look at the advantages and challenges of power electronics integration into a single traction drive unit and respective thermal management system concepts. We'll talk about barriers to implementation of a unified thermal management system. The tutorial will also review key aspects of thermal management system design: modeling and simulation using FEA and CFD tools, experimental characterization, and general workflow for thermal management system evaluation.

ADVANCED PROPULSION SYSTEMS,DIRECT ENERGY CONVERSI↗

DOE OSTI2024

Motivation and Design of the OCPP Security Service

Pacific Northwest National Laboratory is conducting in-depth research aimed at exploring how zero trust security principles can be effectively applied to electric vehicle charging infrastructure. This investigation seeks to enhance the resilience and reliability of these systems against cyber threats, ensuring secure and uninterrupted access to charging services for electric vehicle users and electric supply. Zero trust is a security concept centered on the belief that system operators should not automatically trust users or systems based on their location, whether inside or outside the organization, but instead must verify everything trying to connect to their systems before granting access. A key aspect of the project is to demonstrate and validate zero trust approaches targeted to electric vehicle (EV) charging infrastructure. It has been observed that both open-source and commercial solutions often overlook the specific protocols employed in managing EV charging stations and proceeded with a general, protocol-agnostic approach. While these strategies effectively block non-authorized routes to the charging infrastructure, they do not tackle the situations where attackers may exploit legitimate access channels, such as the inattentive operator model posited by the Idaho National Laboratory. To address this gap, this paper proposes and discusses a new security service targeted to the Open Charge Point Protocol (OCPP), which is the de facto protocol for the management of charging stations and serves a critical role in the broader adoption of electric vehicles. The design and architecture of the proposed OCPP security service are discussed in detail, outlining how it aims to safeguard charging station management system (CSMS) functions. The service is particularly important in scenarios where the charging station operator (CSO), responsible for the maintenance and operation of charging stations, and the charging network provider (CNP), which manages the charging network's accessibility and billing, are separate entities. This distinction is crucial because CSOs and CNPs often have different priorities, objectives, and operational responsibilities, which may not always align perfectly. For instance, a CSO might prioritize uptime and customer satisfaction, while a CNP might focus on maximizing revenue and network utilization. Such misalignment can create security vulnerabilities, as each entity might implement different policies and standards, potentially leaving gaps in the overall security posture.

33 ADVANCED PROPULSION SYSTEMS↗

NASA NTRSDate not supplied

Hall Magnetohydrodynamic Power Generation and Drag Augmentation Using A Coaxial-Electrode Configuration During Hypersonic Entry

For interplanetary missions, a spacecraft must reduce its relative velocity from orbital speeds of multiple kilometers per second to zero in order to safely land on the surface of a planetary body. During this phase known as planetary reentry, the spacecraft undergoes high speed above Mach 5 up to Mach 30. This hyper-sonic flight regime imposes a strong bow shock in front of the vehicle that imparts extreme aerodynamic and thermal effects. In addition, during portions of this regime, a plasma is formed in the post-shock flow-field around the vehicle due to these high temperatures. Interaction between an applied magnetic field with this electrically conductive fluid, or magnetohydrodynamic (MHD) interaction, can be utilized to convert kinetic energy from the flow into storable electrical energy. Onboard MHD energy generation can benefit the spacecraft by increasing the power of active thermal control components and vehicle control systems during reentry. MHD interaction also exerts a Lorentz body force on the plasma flow that can be manipulated to act as an additional drag force through the vehicle body. MHD drag augmentation can benefit the spacecraft with an additional control mechanism that operates without moving parts. This can be utilized at higher altitudes and subsequently reduce convective heat transfer to the vehicle. MHD interaction with plasma flow suggests that both power generation and drag augmentation can be integrated together in one design. Modern numerical studies have only demonstrated the viability and potential of MHD energy generation and drag modulation separately for implementation into future spacecraft designs [1] [2] [3]. Steeves et. al. presented one possible generator design specifically for reentry vehicles that utilized a modular panel with two embedded electromagnets and two extruding electrodes for air plasma to flow between. Fujino et. al. presented results that indicated increased total drag with a permanent magnet embedded in the blunt body of the Orbital Reentry Experiment (OREX) trajectory. Furthermore, experimental investigations of these two MHD applications have been limited and separate due to the difficult technical nature of experimental de-sign and analysis. For MHD energy generation, there have been two designs which used a cylindrical fore-body with two embedded permanent magnets and two outward facing curved electrodes for tangency to an artificially ionized plasma that flowed along the body length [4] [5]. The first design was studied using an air microwave (MW) ionized supersonic plasma wind tunnel and the second design used radio frequency (RF) ionization of Argon, but both physically demonstrated the feasibility of MHD energy generation in reentry plasma conditions. For MHD drag modulation, one study involved a small-scale cylindrical blunt body embedded with permanent magnets immersed in plasma flow in an arcjet tunnel [6], and another utilized a spherical permanent magnet enclosed with a spherical forebody that was evaluated in a shock expansion tunnel [7]. Both experimental studies provided physical evidence of drag augmentation due to MHD interactions. Therefore, because of the multi-faceted effects of MHD along with both applications having been deemed feasible and beneficial during reentry, this indicates that a coupled power generation and drag modulation design could be achievable. The axi-symmetric nature of blunt bodies for reentry suggests that a spherical set of two ring electrodes near the nose along the body axis. Based on first principles, flow along the walls of the spherical body can then produce MHD interactions between the electrodes. As a result, two currents are generated: a Hall current that produces power and a primary inductive current that augments the drag force. The goal of this work is to provide a simulated design of a coaxial-electrode con-figuration for power generation and drag modulation for experimental testing.

E. Leong↗

NASA NTRS2010

Lunar Surface Operations with Dual Rovers

Lunar Electric Rovers (LER) are currently being developed that are substantially more capable than the Apollo vehicle (LRN ,"). Unlike the LRV, the new LERs provide a pressurized cabin that serves as short-sleeve environment for the crew of two, including sleeping accommodations and other provisions that allow for long tern stays, possibly up to 60 days, on the hear surface, without the need to replenish consumables from some outside source, such as a lander or outpost. As a consequence, significantly larger regions may be explored in the future and traverse distances may be measured in a few hundred kilometers (1, 2). However, crew safety remains an overriding concern, and methods other than "walk back", the major operational constraint of all Apollo traverses, must be implemented to assure -at any time- the safe return of the crew to the lander or outpost. This then causes current Constellation plans to envision long-tern traverses to be conducted with 2 LERs exclusively, each carrying a crew of two: in case one rover fails, the other will rescue the stranded crew and return all 4 astronauts in a single LER to base camp. Recent Desert Research and Technology Studies (DRATS) analog field tests simulated a continuous 14 day traverse (3), covering some 135 km, and included a rescue operation that transferred the crew and diverse consumables from one LER to another these successful tests add substantial realism to the development of long-term, dual rover operations. The simultaneous utilization of 2 LERs is of course totally unlike Apollo and raises interesting issues regarding science productivity and mission operations, the thrust of this note.

Horz, Friedrich↗

NASA NTRS2017

Legacy of the Asteroid Redirect Robotic Mission (ARRM)

NASA’s proposed Asteroid Redirect Robotic Mission (ARRM) began with the recognition in a 2010 NASA study that emerging high-power solar electric propulsion technology could be used to rendezvous with, capture, and return an entire, very small (~10,000 kg), near Earth asteroids to the International Space Station. A 2011 workshop by the Keck Institute for Space Studies (KISS) extended the earlier NASA study to asteroid masses of order 500,000 kg by returning them to cislunar space. Subsequent detailed NASA studies in 2013-2014 confirmed the feasibility of this concept. This led to the establishment of the Asteroid Redirect Mission program that consisted of a robotic mission to return multiple tons of asteroid material to cislunar space and a crewed mission to rendezvous with the robotic vehicle, perform two extra vehicular activities (EVAs), collect samples of the asteroid material, and return this material to Earth. Implementation of ARRM got midway through Phase B before being cancelled in April 2017. Although ARRM was cancelled, it has left a near-term legacy of positive impacts to the human spaceflight community, the planetary defense community, the deep space science community, and asteroid mining interests.

Brophy, John R.↗

NASA NTRS2005

Health Management Applications for International Space Station

Traditional mission and vehicle management involves teams of highly trained specialists monitoring vehicle status and crew activities, responding rapidly to any anomalies encountered during operations. These teams work from the Mission Control Center and have access to engineering support teams with specialized expertise in International Space Station (ISS) subsystems. Integrated System Health Management (ISHM) applications can significantly augment these capabilities by providing enhanced monitoring, prognostic and diagnostic tools for critical decision support and mission management. The Intelligent Systems Division of NASA Ames Research Center is developing many prototype applications using model-based reasoning, data mining and simulation, working with Mission Control through the ISHM Testbed and Prototypes Project. This paper will briefly describe information technology that supports current mission management practice, and will extend this to a vision for future mission control workflow incorporating new ISHM applications. It will describe ISHM applications currently under development at NASA and will define technical approaches for implementing our vision of future human exploration mission management incorporating artificial intelligence and distributed web service architectures using specific examples. Several prototypes are under development, each highlighting a different computational approach. The ISStrider application allows in-depth analysis of Caution and Warning (C&W) events by correlating real-time telemetry with the logical fault trees used to define off-nominal events. The application uses live telemetry data and the Livingstone diagnostic inference engine to display the specific parameters and fault trees that generated the C&W event, allowing a flight controller to identify the root cause of the event from thousands of possibilities by simply navigating animated fault tree models on their workstation. SimStation models the functional power flow for the ISS Electrical Power System and can predict power balance for nominal and off-nominal conditions. SimStation uses realtime telemetry data to keep detailed computational physics models synchronized with actual ISS power system state. In the event of failure, the application can then rapidly diagnose root cause, predict future resource levels and even correlate technical documents relevant to the specific failure. These advanced computational models will allow better insight and more precise control of ISS subsystems, increasing safety margins by speeding up anomaly resolution and reducing,engineering team effort and cost. This technology will make operating ISS more efficient and is directly applicable to next-generation exploration missions and Crew Exploration Vehicles.

Alena, Richard↗

DOE OSTI2021

OpenDSS-wrapper (Distribution System Co-simulator with Distributed Energy Resource Controls)

Electric grid transformation with the proliferation of distributed energy resources (DER), such as solar photovoltaic (PV), wind, advanced energy storage technologies, and electric vehicles, and the growing use of communication technologies in both transmission and distribution systems are increasing the need to capture the interactions among these systems. Advanced modeling, control, and simulation tools that can perform co-simulation of electric power systems with other domains become indispensable to accurately model these interactions. To address this need, we have developed a codebase that integrates an electric power distribution system simulator, DER models, and DER controls. The codebase is based on OpenDSS, a distribution system simulator, and an existing open source co-simulation framework called HELICS. The contribution and uniqueness of the proposed codebase is that it tailors the generic HELICS framework specifically for distribution grid-related applications. The codebase includes an OpenDSS wrapper that controls the simulation, implements advanced DER controls, and extracts power flows, voltages, and other power system element information from the the distribution network modeled in OpenDSS. Sample HELICS federates, including a federate for OpenDSS, are provided that can communicate messages through the HELICS interface. Sample federates can be modified and additional HELICS federates can be added by the user depending on their use case requirements. SEE ALSO: https://github.com/NREL/dss-cosim

Blonsky, Michael↗

DOE OSTI2024

Opportunities for Process Intensification with Membranes to Promote Circular Economy Development for Critical Minerals

Critical minerals are essential to the future of clean energy, especially energy storage, electric vehicles, and advanced electronics. In this paper, we argue that process systems engineering (PSE) paradigms provide essential frameworks for enhancing the sustainability and efficiency of critical mineral processing pathways. As a concrete example, we review challenges and opportu-nities across material-to-infrastructure scales for process intensification (PI) with membranes. Within critical mineral processing, there is a need to reduce environmental impact, especially con-cerning chemical reagent usage. Feed concentrations and product demand variability require flex-ible, intensified processes. Further, unique feedstocks require unique processes (i.e., no one-size-fits-all recycling or refining system exists). Membrane materials span a vast design space that allows significant optimization. Therefore, there is a need to rapidly identify the best opportunities for membrane implementation, thus informing materials optimization with process and infrastructure scale performance targets. Finally, scale-up must be accelerated and de-risked across the materials-to-process levels to fully realize the opportunity presented by membranes, thereby fostering the development of a circular economy for critical minerals. Tackling these challenges requires integrating efforts across diverse disciplines. We advocate for a holistic molecular-to-systems perspective for fully realizing PI with membranes to address sustainability challenges in critical mineral processing. The opportunities for PI with membranes are excellent applications for emerging research in machine learning, data science, automation, and optimization.

Dougher, Molly↗

NASA NTRS2001

Baseline Testing of the Ultracapacitor Enhanced Photovoltaic Power Station

The NASA John H. Glenn Research Center is developing an advanced ultracapacitor enhanced photovoltaic power station. Goals of this effort include maximizing photovoltaic power generation efficiency and extending the life of photovoltaic energy storage systems. Unique aspects of the power station include the use of a solar tracker, and ultracapacitors for energy storage. The photovoltaic power station is seen as a way to provide electric power in remote locations that would otherwise not have electric power, provide independence form utility systems, reduce pollution, reduce fossil fuel consumption, and reduce operating costs. The work was done under the Hybrid Power Management (HPM) Program, which includes the Hybrid Electric Transit Bus (HETB), and the E-Bike. The power station complements the E-Bike extremely well in that it permits the charging of the vehicle batteries in remote locations. Other applications include scientific research and medical power sources in isolated regions. The power station is an inexpensive approach to advance the state of the art in power technology in a practical application. The project transfers space technology to terrestrial use via nontraditional partners, and provides power system data valuable for future space applications. A description of the ultracapacitor enhanced power station, the results of performance testing and future power station development plans is the subject of this report. The report concludes that the ultracapacitor enhanced power station provides excellent performance, and that the implementation of ultracapacitors in the power system can provide significant performance improvements.

Eichenberg, Dennis J.↗