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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Levelized cost of charging of extreme fast charging with stationary LMO/LTO batteries

Extreme DC fast charging for electric vehicles (EVs) could be competitive with the internal combustion engine refueling experience and enable longer-distance travel, which could help with EV adoption and decarbonization, but these systems have high capital costs and extremely variable high-power demands. Behind-the-meter systems (BTMS) could support extreme-fast-charging (XFC) stations to increase nationwide adoption of EVs. Here, this study examines the optimal break-even levelized cost of charging (LCOC) across 96 BTMS scenarios to enable low-wait XFC stations providing 200 miles of charge in 10 min. This research simulates LCOC via synthetic XFC-capable EV loads, machine-learned battery life models from testing data, and nonlinear optimal controls, co-minimizing complex utility costs and battery replacements. An aggregate optimal BTMS design treating each EV load as equal likely gives an optimal LCOC per utility rate, the average of which is $\$$0.59/kWh. In addition, the sensitivity of optimal and off-optimal design factors, the long-life LMO/LTO chemistry, and optimized controls are analyzed. The battery control model, based on battery stressors to compare chemistries, optimizes LMO/LTO resting state of charge and cycle depth without compromising cost reduction, which enables greater flexibility in operation. The LCOC savings due to replacement reduction are small, up to $\$$0.035/kWh (6%), with an average of $\$$0.02/kWh (3.5%). Compared with gasoline stations, the aggregate XFC station design achieves comparable speed, experience of service, and cost at $\$$3.81/gal gasoline, showing that EVs can replace gasoline vehicles even for longer-distance travel.

25 ENERGY STORAGE↗
DOE OSTI2023

State of battery health estimation based on swelling characteristics

There is disclosed an electrical device including a battery, and a battery management system. The battery management system includes a controller in electrical communication with a pressure sensor to monitor the state of health of the battery. The controller applies a method for determining the state of health that uses a non-electrical (mechanical) signal of force measurements combined with incremental capacity analysis to estimate the capacity fading and other health indicators of the battery with better precision than existing methods. The pressure sensor may provide the force measurement signal to the controller, which may determine which incremental capacity curve based on force to use for the particular battery. The controller then executes a program utilizing the data from the pressure sensor and the stored incremental capacity curves based on force to estimate the capacity fading and signal a user with the state of health percentage.

Stefanopoulou, Anna G.↗
DOE OSTI2022

Enhanced physics-constrained deep neural networks for modeling vanadium redox flow battery

Numerical simulation has become indispensable in advancing cost-effective process optimization and control of flow batteries. We propose an enhanced version of the physics-constrained deep neural network (PCDNN) approach to provide high-accuracy voltage predictions in the vanadium redox flow batteries (VRFBs). The purpose of the PCDNN approach is to enforce the physics-based zero-dimensional (0D) VRFB model in a neural network to assure model generalization for various battery operation conditions. However, limited by the simplifications of the 0D model, the PCDNN cannot capture sharp voltage changes in the extreme SOC regions. To improve the accuracy of voltage prediction at extreme ranges, we introduce a second (enhanced) DNN to mitigate the prediction errors carried from the 0D model itself and call the resulting approach enhanced PCDNN (ePCDNN). By comparing with experimental data, we demonstrate that the ePCDNN approach can accurately capture the voltage response throughout the charge–discharge cycle, including the tail region of the voltage discharge curve. The loss function for training the ePCDNN is designed to be flexible by adjusting the weights of the physics-constrained DNN and the enhanced DNN. In conclusion, this allows the ePCDNN framework to be transferable to battery systems with variable physical model fidelity.

25 ENERGY STORAGE↗
DOE OSTI2024

Cobalt-free composite-structured cathodes with lithium-stoichiometry control for sustainable lithium-ion batteries

Abstract Lithium-ion batteries play a crucial role in decarbonizing transportation and power grids, but their reliance on high-cost, earth-scarce cobalt in the commonly employed high-energy layered Li(NiMnCo)O 2 cathodes raises supply-chain and sustainability concerns. Despite numerous attempts to address this challenge, eliminating Co from Li(NiMnCo)O 2 remains elusive, as doing so detrimentally affects its layering and cycling stability. Here, we report on the rational stoichiometry control in synthesizing Li-deficient composite-structured LiNi 0.95 Mn 0.05 O 2 , comprising intergrown layered and rocksalt phases, which outperforms traditional layered counterparts. Through multiscale-correlated experimental characterization and computational modeling on the calcination process, we unveil the role of Li-deficiency in suppressing the rocksalt-to-layered phase transformation and crystal growth, leading to small-sized composites with the desired low anisotropic lattice expansion/contraction during charging and discharging. As a consequence, Li-deficient LiNi 0.95 Mn 0.05 O 2 delivers 90% first-cycle Coulombic efficiency, 90% capacity retention, and close-to-zero voltage fade for 100 deep cycles, showing its potential as a Co-free cathode for sustainable Li-ion batteries.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Operation and Control of Soft Switching Solid State Transformer as a Virtual Synchronous Machine for Photovoltaic Application

Possibility for control and operation of a three-phase solid state soft switching transformer based as a virtual synchronous machine or synchronverter has been investigated in this paper. The soft switching solid state transformer is used as an interface between the ac grid and a photovoltaic power generation unit supported by a battery bank. The control architecture investigated in this paper is that of a synchronverter to achieve inertial support to the grid and local loads. The operation of the soft switching solid state transformer has also been investigated as a V S M during unbalanced/distorted grid voltage condition. Control objective to achieve oscillation free power transfer between the ports (photovoltaic, battery and grid) has been achieved. The presented architecture has been verified for several important case studies via numerical simulations based on MATLAB/Simulink domain.

grid current controller↗
DOE OSTI2023

Design Considerations of a Coordinative Demand Charge Mitigation Strategy

This paper presents a coordinative demand charge mitigation (DCM) strategy for reducing electricity consumption during system peak periods. Available DCM resources include batteries, diesel generators, controllable loads, and conservation voltage reduction. All resources are directly controlled by load serving entities. A mixed integer linear programming based energy management algorithm is developed to optimally coordinate of DCM resources considering the load payback effect. To better capture system peak periods, two different kinds of load forecast are used: the day-ahead load forecast and the peak-hour probability forecast. Five DCM strategies are compared for reconciling the discrepancy between the two forecasting results. The DCM strategies are tested using actual utility data. Simulation results show that the proposed algorithm can effectively mitigate the demand charge while preventing the system peak from being shifted to the payback hours. We also identify the diminishing return effect, which can help load serving entities optimize the size of their DCM resources.

Hu, Rongxing↗
DOE OSTI2021

A control oriented comprehensive degradation model for battery energy storage system life prediction

In order to ensure that stationary battery energy storage systems (BESSs) provide reliable energy buffering, both for power quality and economic purposes, the degradation must be considered. Cell degradation involves various side reactions and is highly dependent on its operating conditions. To accurately track cell degradation and predict its impact on battery behavior, a comprehensive physics-based degradation model based on an electrolyte phase-enhanced single particle (SP) model is developed. Key degradation physics, namely solid electrolyte interphase (SEI) layer formation and growth, Li plating on the graphite anode, and Mn dissolution on cathode of nickel-cobalt-manganese oxide (NMC622) are considered. The model is validated against experimental capacity data. The results reveal that the deposition rate of both SEI layer and Li metal increase as the charge voltage increases. At the cathode side, the solvent oxidation rate determines the Mn dissolution rate. As a result, the volume fraction of NMC622 in the cathode continually decreases at a gradually increasing rate.

25 ENERGY STORAGE↗
DOE OSTI2024

Robust battery interphases from dilute fluorinated cations

Controlling solid electrolyte interphase (SEI) in batteries is crucial for their efficient cycling. Herein, we demonstrate an approach to enable robust battery performance that does not rely on high fractions of fluorinated species in electrolytes, thus substantially decreasing the environmental footprint and cost of high-energy batteries. In this approach, we use very low fractions of readily reducible fluorinated cations in electrolyte (~0.1 wt%) and employ electrostatic attraction to generate a substantial population of these cations at the anode surface. As a result, we can form a robust fluorine-rich SEI that allows for dendrite-free deposition of dense Li and stable cycling of Li-metal full cells with high-voltage cathodes. Our approach represents a general strategy for delivering desired chemical species to battery anodes through electrostatic attraction while using minute amounts of additive.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

LuSEE-night power distribution system design

The Lunar Surface Electromagnetic Experiment at Night (LuSEE-Night) is a low-frequency, 0.5 to 50 MHz, radio experiment on the radio-quiet far side of the Moon. The instrument will be launched by NASA Commercial Lunar Payload Services in 2026. The LuSEE-Night instrument core is composed of a radio frequency spectrometer (SPT) processing signals from four antennas, the Data Controller Board (DCB), low electromagnetic interference (EMI) Picket Fence Power Supply (PFPS), and Power Distribution Unit (PDU). The battery powers the instrument during the lunar night and stores energy harvested by the solar panel array during the lunar day. The battery charging is controlled by the Power Conditioning and Distribution Unit (PCDU). The unregulated power is supplied either by the SpaceCraft (S/C) or the battery and gets distributed to the PFPS, communication radio, heaters, and deployables through the PDU. The PFPS generates all regulated low-voltage rails using switching regulation synchronized to the LuSEE-Night clock, which ensures self-generated EMI will be confined to well-defined frequency bins. Here, we discussed the unregulated power distribution system architecture and functionality. The PDU engineering and flight modules are developed and characterized to confirm compliance with LuSEE-Night requirements. At the time of writing, all power subsystem components have been integrated into the payload.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

CRADA Final Report: Open Microgrid Platform

Current microgrid control technology is mostly proprietary, expensive, and inflexible. An open-source, vendor-neutral, publish-subscribe controller will significantly lower the barrier to entry for new technologies and market entrants: inverter, battery, and load control manufacturers; cloud and services providers; and energy aggregators. An OpenFMB controller can significantly reduce the acquisition, integration, and ongoing operating and maintenance costs and increase revenue opportunities for energy producers and consumers. It allows distributed energy resource (DER) owners to replace individual DER components as richer-function, lower-cost devices become available or to incorporate new forecast and optimization algorithms as they are developed. A standard, secure, full-function DER field controller will also provide a low-cost means for grid operators to effectively manage the variability and uncertainty of solar photovoltaics (PV). Under the terms of this CRADA, ORNL has worked with Open Energy Solutions (OES) to advance the transition of ORNL’s existing open-source microgrid controller into a platform geared toward mainstream implementation. Using a more prevalent and memory-safe programming language, Rust, OES has converted ORNL’s current generation on-grid optimization into an application more suitable for industry use. The results of the ported optimization were analyzed by inputting the same arguments in both the current-generation and next-generation optimizers and verifying that the results were equivalent.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Control Design and EMT Simulation Toward the Restoration of Faulted Wind-Dominant Grids

Present power engineers have been challenged to employ electromagnetic transient (EMT) simulations to study the restoration of wind-dominant grids. This paper addresses this hurdle by developing strategies to: (i) reliably control the dc-link voltage of grid-forming wind turbines with dc-coupled batteries, (ii) tune controllers to stably interconnect wind power plants into a grid under recovery, and (iii) autonomously make restoration decisions if transmission faults occur during restoration. These contributions are assessed via EMT simulations of wind-dominant versions of the WSCC 9-bus grid and a 22-bus power system. Furthermore, this paper is significant to address recommendations by the North American Electric Reliability Corporation.

17 WIND ENERGY↗
DOE OSTI2022

Study of Inverter Control Strategies on the Stability of Low-Inertia Microgrid Systems

This paper investigates the stability of low-inertia microgrid systems with two control strategies that have different percentages of grid-forming (GFM) inverters. The first control strategy has approximately 50% GFM inverters, and all the battery inverters are working in GFM control mode. Originally, the second control strategy has approximately 10% GFM inverters, with only two battery inverters working in GFM control mode and the rest working in grid-following (GFL) PQ control mode based on current control, which cannot stabilize the microgrid system. Then, the second control strategy is modified to change the GFM inverters from droop control to isochronous control and the GFL battery inverters from traditional current control to voltage control for power control. Both control strategies can maintain system stability; however, the first control strategy can better handle contingency events. The study indicates that 1) a microgrid system with a higher percentage of GFM inverters has better stability; and 2) a microgrid with a lower percentage of GFM inverters can have poor stability, but improved control strategies in inverters can improve system stability. This study improves the understanding of how different percentages of GFM inverters and inverter control strategies affect the system stability of low-inertia microgrids.

droop control↗
DOE OSTI2022

Study of Inverter Control Strategies on the Stability of Low-Inertia Microgrid Systems: Preprint

This paper investigates the stability of low-inertia microgrid systems with two control strategies that have different percentages of grid-forming (GFM) inverters. The first control strategy has approximately 50% GFM inverters, and all the battery inverters are working in GFM control mode. Originally, the second control strategy has approximately 10% GFM inverters, with only two battery inverters working in GFM control mode and the rest working in grid-following (GFL) PQ control mode based on current control, which cannot stabilize the microgrid system. Then, the second control strategy is modified to change the GFM inverters from droop control to isochronous control and the GFL battery inverters from traditional current control to voltage control for power control. Both control strategies can maintain system stability; however, the first control strategy can better handle contingency events. The study indicates that 1) a microgrid system with a higher percentage of GFM inverters has better stability; and 2) a microgrid with a lower percentage of GFM inverters can have poor stability, but improved control strategies in inverters can improve system stability. This study improves the understanding of how different percentages of GFM inverters and inverter control strategies affect the system stability of low-inertia microgrids.

droop control↗
DOE OSTI2022

Study of Inverter Control Strategies on the Stability of Low-Inertia Microgrid Systems

This paper investigates the stability of low-inertia microgrid systems with two control strategies that have different percentages of grid-forming (GFM) inverters. The first control strategy has approximately 50% GFM inverters, and all the battery inverters are working in GFM control mode. Originally, the second control strategy has approximately 10% GFM inverters, with only two battery inverters working in GFM control mode and the rest working in grid-following (GFL) PQ control mode based on current control, which cannot stabilize the microgrid system. Then, the second control strategy is modified to change the GFM inverters from droop control to isochronous control and the GFL battery inverters from traditional current control to voltage control for power control. Both control strategies can maintain system stability; however, the first control strategy can better handle contingency events. The study indicates that 1) a microgrid system with a higher percentage of GFM inverters has better stability; and 2) a microgrid with a lower percentage of GFM inverters can have poor stability, but improved control strategies in inverters can improve system stability. This study improves the understanding of how different percentages of GFM inverters and inverter control strategies affect the system stability of low-inertia microgrids.

droop control↗