Search NASA⌕ Search

SEARCH · Search NASA

Results for “electrical connectivity”

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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Seeding the Electrothermal Instability through a Three-Dimensional, Nonlinear Perturbation

Electrothermal instability plays an important role in applications of current-driven metal, creating striations (which seed the magneto–Rayleigh-Taylor instability) and filaments (which provide a more rapid path to plasma formation). However, the initial formation of both structures is not well understood. Here, simulations show for the first time how a commonly occurring isolated defect transforms into the larger striation and filament, through a feedback loop connecting current and electrical conductivity. Simulations have been experimentally validated using defect-driven self-emission patterns.

42 ENGINEERING↗
DOE OSTI2024

Inertia Estimation Under High Penetration of Inverter-based Resources

Many types of renewable energy sources, especially solar and wind generation, are connected to the electric grid through power-electronic-based interfaces (inverters). These inverter-based resources (IBRs) are mechanically decoupled from the grid, which reduces system inertia and thus may compromise its stability and reliability. In this study, we examine the impact of high penetration of IBRs on the power grid’s inertia. To achieve this, we intentionally introduce disturbances into a simulation case study, such as a step load change, to observe and record the system’s frequency responses. This study offers a nuanced understanding of how the integration of IBRs affects grid stability, and it provides essential guidance for future grid management and resilience strategies.

Yadav, Ajay↗
DOE OSTI2024

Electrolyte and Cutoff Potential Effects on Cycle Life of Li4Ti5O12/LiNi0.9Mn0.1O2 Batteries for Behind-the-Meter Storage Applications

Behind-the-Meter Storage (BTMS) is a stationary battery energy storage system that is connected to the electrical distribution system on the customer's side of the utility's service meter. BTMS systems are used to store electrical energy from the grid as well as inconstant, renewable energy, such as local solar and wind generation. A successful BTMS system will allow the customer to pair their energy generation and storage to optimize electrical consumption from the grid, improving reliability and minimizing cost. For BTMS applications, batteries must be designed and optimized with different set of criteria from other leading segments of the Li-ion battery market, like transportation, due the system being stationary and proximal to the residential or commercial building it's benefitting. BTMS applications prioritize safety, cost (low/no-critical materials), reliability (20-year calendar life), and durability (10,000 cycle life), while having the ability to (minimally) compromise energy density and rate capability. Lithium titanate (Li4Ti5O12-, LTO) is a promising anode candidate for BTMS applications due to its high safety and capacity retention, while maintaining a reasonable 160 mAhg-1 reversable capacity and composition of relatively abundant materials. (1) Specifically, LTO has a high working voltage which helps to prevent Li dendrite formation, improving safety. Furthermore, LTO also has negligible lithiation-based volume change, leading to less mechanical pulverization, or loss of active material, upon cycling. For the cathode, materials with little or no Co are of high interest due to the high cost and low abundance of Co. LiMn2O4 (LMO) has been paired with LTO for BTMS applications in the past due to its safety, low cost (abundancy), and reasonably high operating voltage. (2-4) However, the low capacity of LMO limits energy density and specific energy. While not the highest priority for BTMS applications, increasing energy density will enable deployment in space constrained BTMS applications and decrease total cost. LiNi0.9Mn0.1O2 (LN-MO) is a recently developed material with promise due to its high operating voltage and relatively low price. (5) However, Ni-rich layered oxides, including LNMO, tend to struggle with capacity retention during high-voltage cycling due to mechanical pulverization, irreversible phase transitions, and unstable solid-electrolyte interphase. The study presented here focuses on building an understanding of how electrolyte solvent and varied cutoff potentials will impact the cycle life of LTO/LN-MO cells. Specifically, a comparison is provided between ethylene carbonate (EC), ethyl methyl carbonate (EMC), fluoroethylene carbonate (FEC), and Gen2 electrolyte solvents with 1M Lithium hexafluorophosphate (LiPF6) salt, cycling to two upper termination potentials, 2.6V and 2.7V. Electrochemical testing and diagnostics (e.g., differential capacity analysis, area specific impedance, constant voltage hold, and rate capability) and post-mortem characterization will be used to understand the aging behavior and failure mechanisms of the 8 cell combinations (four electrolytes and two voltage cutoffs). Cells with FEC electrolyte showed a lower initial capacity compared to cells with Gen2, EMC, and EC cycling at both voltages; however, the cells with FEC showed consistent trends in capacity retention with 2.6V and 2.7V termination potentials, while the cells with the other electrolytes showed much higher rates of capacity loss when cycling to the higher voltage. These results indicate that FEC may play a role in improving durability of high-voltage, Ni-rich electrode systems for use in high-cycle applications, such as BTMS.

electrolyte↗
DOE OSTI2020

Decision Support Tool for Planning Neighborhood-Scale Deployment of Low-Speed Shared Automated Shuttles

Increasing interest and investment in connected, automated, and electric vehicles as well as mobility-as-a-service (MaaS) concepts are paving the way for the next major transformation in transportation through automated and shared mobility. The initial excitement toward rapid deployment and adoption of automated vehicles (AVs) has subsided, and low-speed automated shuttles are emerging as a more pragmatic pathway for introducing automated mobility in geofenced districts. Such shuttles hold the promise to provide a viable alternative for serving short trips in urban districts with high travel densities. As interest in low-speed automated shuttle systems (to improve urban mobility) increases, the need for tools that can inform communities in relation to benefits or disadvantages of automated shuttle deployments is imminent. However, most of the existing transportation planning and simulation tools are not capable of handling emerging shared automated mobility options. This paper presents a microscopic simulation toolkit that can be used by cities and communities to plan for the deployment of low-speed automated shuttles systems, as well as other shared mobility options. Labeled as the Automated Mobility District modeling and simulation toolkit, the proposed decision support tool intends to help cities evaluate the mobility and sustainability impacts of deploying shared automated vehicles (SAVs) in geofenced regions. This paper describes the toolkit, as well as a sample scenario analysis for the deployment of low-speed automated shuttles in Greenville, South Carolina, U.S. Results from the scenario study demonstrate the effectiveness of the proposed simulation toolkit in planning for advanced mobility systems.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

High-bandwidth image-based predictive laser stabilization via optimized Fourier filters

Controlling the delivery of kHz-class pulsed lasers is of interest in a variety of industrial and scientific applications, from next-generation laser-plasma acceleration to laser-based x-ray emission and high-precision manufacturing. The transverse position of the laser pulse train on the application target is often subject to fluctuations by external drivers (e.g., room cooling and heating systems, motorized optics stages and mounts, vacuum systems, chillers, and/or ground vibrations). For typical situations where the disturbance spectrum exhibits discrete peaks on top of a broad-bandwidth lower-frequency background, traditional PID (proportional-integral-derivative) controllers may struggle, since as a general rule PID controllers can be used to suppress vibrations up to only about 5%–10% of the sampling frequency. Here, a predictive feed-forward algorithm is presented that significantly enhances the stabilization bandwidth in such laser systems (up to the Nyquist limit at half the sampling frequency) by online identification and filtering of one or a few discrete frequencies using optimized Fourier filters. Furthermore, the system architecture demonstrated here uses off-the-shelf CMOS cameras and piezo-electric actuated mirrors connected to a standard PC to process the alignment images and implement the algorithm. To avoid high-end, high-cost components, a machine-learning-based model of the piezo mirror’s dynamics was integrated into the system, which enables high-precision positioning by compensating for hysteresis and other hardware-induced effects. A successful demonstration of the method was performed on a 1 kHz laser pulse train, where externally-induced vibrations of up to 400 Hz were attenuated by a factor of five, far exceeding what could be done with a standard PID scheme.

Natal, Joseph↗
DOE OSTI2020

A Decision Support Tool for Planning Neighborhood-Scale Deployment of Low-Speed Shared Automated Shuttles

Increasing interest and investment in connected, automated, and electric vehicles, and mobility-as-a-service concepts are paving the way for the next major shift in transportation through automated and shared mobility. The initial excitement towards rapid deployment and adoption of automated vehicles has subsided, and low-speed automated shuttles are emerging as a more pragmatic pathway for introducing automated mobility in geo-fenced districts. Such shuttles hold the promise to provide a viable alternative for serving short trips in urban districts with high travel densities. As interest in low-speed automated shuttle systems (to improve urban mobility) increases, the need for tools that can inform communities regarding benefits or dis-benefits of automated shuttle deployments is imminent. However, most of the existing transportation planning and simulation tools are not capable of handling emerging shared automated mobility options. This presentation presents a microscopic simulation toolkit that can be used by cities and communities to plan for the deployment of low-speed automated shuttles systems, as well as other shared mobility options. Labeled as the Automated Mobility District (AMD) modeling and simulation toolkit, the proposed decision support tool can help cities evaluate the mobility and sustainability impacts of deploying shared automated vehicles in geofenced regions. This paper presents a description of the toolkit, as well as a sample scenario analysis for the deployment of low-speed automated shuttles in Greenville, South Carolina. Results from the scenario study demonstrate the effectiveness of the proposed simulation toolkit in planning for advanced mobility systems.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

Grid regulation services for energy storage devices based on grid frequency

Disclosed herein are representative embodiments of methods, apparatus, and systems for charging and discharging an energy storage device connected to an electrical power distribution system. In one exemplary embodiment, a controller monitors electrical characteristics of an electrical power distribution system and provides an output to a bi-directional charger causing the charger to charge or discharge an energy storage device (e.g., a battery in a plug-in hybrid electric vehicle (PHEV)). The controller can help stabilize the electrical power distribution system by increasing the charging rate when there is excess power in the electrical power distribution system (e.g., when the frequency of an AC power grid exceeds an average value), or by discharging power from the energy storage device to stabilize the grid when there is a shortage of power in the electrical power distribution system (e.g., when the frequency of an AC power grid is below an average value).

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Modeling and Simulation of Automated Mobility Districts

Increasing interest and investment in connected, automated, and electric vehicles (CAEVs), and mobility-as-a-service (MaaS) concepts are paving the way for the next major shift in transportation through automated and shared mobility. The initial excitement towards rapid deployment and adoption of automated vehicles has subsided, and low-speed automated shuttles are emerging as a more pragmatic pathway for introducing automated mobility in geo-fenced districts. Such shuttles hold the promise to provide a viable alternative for serving short trips in urban districts with high travel densities. As interest in low-speed automated shuttle systems (to improve urban mobility) increases, the need for tools that can inform communities regarding benefits or dis-benefits of automated shuttle deployments is imminent. However, most of the existing transportation planning and simulation tools are not capable of handling emerging shared automated mobility options. This presentation provide the details of a microscopic simulation toolkit that can be used by cities and communities to plan for the deployment of low-speed automated shuttles systems, as well as other shared mobility options. Labeled as Automated Mobility District (AMD) modeling and simulation toolkit, the proposed decision support tool intends to help cities evaluate the mobility and sustainability impacts of deploying shared automated vehicles in geofenced regions.The AMD modeling and simulation task is funded through DOE's SMART Mobility Consortium. This presentation outlines the progress of the AMD modeling and simulation task in FY19, including case studies conducted in Greenville, SC, and Austin, TX.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Battery energy storage control systems and methods for a grid tie inverter coupled to a photovoltaic system

A distributed control system uses a central controller in Internet communication with a local controller to manage grid tie attachment with a battery to form an integrated battery energy storage system (BESS). The BESS is capable of charging or discharging the battery, as well as correcting grid phase with volt amp reactive (VAR) leading or lagging operation modes. Examples shown include simple BESS charging and discharging, BESS integrated with renewable energy sources (here photovoltaic), and direct current fast charge (DCFC) connections with an electric vehicle.

Gadh, Rajit↗
DOE OSTI2022

Si-based CTE-matched substrate for laser diode packaging

A Cu—Si—Cu substrate having a silicon substrate, copper plating on opposite sides of the silicon substrate, and copper vias extending thru the silicon substrate to electrically and thermally connect the copper platings together. The thicknesses of the silicon substrate and the copper platings are selected so that a coefficient of thermal expansion (CTE) of the Cu—Si—Cu substrate is substantially the same as a CTE of a material to be mounted on the Cu—Si—Cu substrate.

Patra, Susant↗
DOE OSTI2023

Energy Data from Heat Pumps Installed in Juneau, AK

Heat pumps offer a great low carbon emission method to heat homes. Thermalize Juneau 2021 was a clean energy campaign that helped homeowners in Juneau, Alaska install heat pumps into their homes. Juneau is located near the climactic limit of many heat pumps, and we were interested in how well the heat pumps can function in cold climates. This was done by using Sense meters to remotely monitor the energy usage of 10 homes with heat pumps. The Sense meters are small devices that connect to the electrical panel and monitor the energy use of multiple appliances through machine learning. First, we recorded the energy usage of a heat pump in the lab using both the Sense meter and the existing lab datalogger. Both recorded very similar energy usage data which confirmed that the Sense meter can accurately measure the fluctuations in the heat pump energy use. Next, we looked at the energy data from the Sense meters in the homes with heat pumps and paired it with local weather data to see how well the heat pumps functioned in the cold weather.

Alaska↗
DOE OSTI2024

Energy storage system

A system, a method, and a computer program product for providing heterogeneous unifying battery storage. A state-of-health value of a battery is determined. The state-of-health value of the battery is less than an original capacity value of the battery. The battery is connected to an electrical power source for re-conditioning. A target state-of-health value for the battery and a number of cycles required to achieve the target state-of-health value of the battery are determined. Each cycle in the number of cycles includes at least one of: a charging the battery and a discharging the battery. The battery is re-conditioned by cycling the battery using the determined number of cycles. Cycling includes drawing electrical power from the electrical power source.

Tong, Shijie↗
DOE OSTI2024

Multi-range vehicle speed prediction using vehicle connectivity for enhanced energy efficiency of vehicles

An integrated speed prediction framework based on historical traffic data mining and real-time V2I communications for CAVs. The present framework provides multi-horizon speed predictions with different fidelity over short and long horizons. The present multi-horizon speed prediction is integrated with an economic model predictive control (MPC) strategy for the battery thermal management (BTM) of connected and automated electric vehicles (EVs) as a case study. The simulation results over real-world urban driving cycles confirm the enhanced prediction performance of the present data mining strategy over long prediction horizons. Despite the uncertainty in long-range CAV speed predictions, the vehicle level simulation results show that 14% and 19% energy savings can be accumulated sequentially through eco-driving and BTM optimization (eco-cooling), respectively, when compared with normal-driving and conventional BTM strategy.

Amini, Mohammad Reza↗
DOE OSTI2022

An Inrush Current Limiting Method for Grid-Connected Converters Considering Grid Voltage Disturbances

To support the electric power grid, some grid-connected converters are required to ride through abnormal grid conditions, including voltage disturbances. However, at the moment, when a grid voltage disturbance happens, a large inrush current could be induced due to the large difference between the grid and converter output pulsewidth modulation (PWM) voltages. This inrush current could be more severe in the faster switching SiC-based multilevel converter, which only needs a small filter inductance to meet its normal operation requirements, such as harmonics and peak ripple currents. In this article, a PWM mask method is used to limit the inrush current. With this method, the inrush current can be effectively limited to a preset value and can help the converter ride through grid voltage disturbances. Furthermore, the method is validated through experiments conducted on a single-phase SiC-based five-level converter considering low voltage, high voltage, and phase angle disturbances.

42 ENGINEERING↗
DOE OSTI2022

Carbon and energy cost impacts of electrification of space heating with heat pumps in the US

In order to meet climate goals, it will be necessary to significantly reduce the greenhouse gases emitted by homes. A key factor in the US is to reduce the on-site combustion of fossil fuels for heating end-uses and to replace this with use of electric heat pump technologies connected to a low-carbon grid. The replacement of natural gas furnaces with electric heat pumps is a key home decarbonization strategy. However, the potential for space heating electrification to reduce greenhouse gas emissions depends on the carbon dioxide equivalent (CO 2 e) content of the electricity used by the heat pump. This varies considerably depending on the source of electricity, with large state to state variability. Furthermore, household energy costs are likely to be impacted by the electrification of space heating, because retail energy prices for both natural gas and electricity in each state vary by factors of seven and four, respectively. Contractors, energy programs, government and building code officials, as well as consumers need clear indications of the likely CO 2 e and energy cost impacts of proposed electrification projects, because these will affect decarbonization choices and rationales around scaled heating electrification. Government and utility programs also need to be aware of the likely outcomes of any supported/incentivized measures. Here, in this paper, we investigate these effects by looking at new metrics to analyze the change in CO 2 e emitted and the cost to meet home heating loads when switching from a natural gas furnace to a heat pump for the contiguous 48 states of the mainland US.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗