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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 847 records · Page 47

The computer simulation of automobile use patterns for defining battery requirements for electric cars

The modeling process of a complex system, based on the calculation and optimization of the system parameters, is complicated in that some parameters can be expressed only as probability distributions. In the present paper, a Monte Carlo technique was used to determine the daily range requirements of an electric road vehicle in the United States from probability distributions of trip lengths, frequencies, and average annual mileage data. The analysis shows that a daily range of 82 miles meets to 95% of the car-owner requirements at all times with the exception of long vacation trips. Further, it is shown that the requirement of a daily range of 82 miles can be met by a (intermediate-level) battery technology characterized by an energy density of 30 to 50 Watt-hours per pound. Candidate batteries in this class are nickel-zinc, nickel-iron, and iron-air. These results imply that long-term research goals for battery systems should be focused on lower cost and longer service life, rather than on higher energy densities

Schwartz, H.-J.↗

Implications of Battery Storage for Solar Net-Metering Reforms

Compensation structures for residential solar PV are evolving toward a model that incentivizes the use of battery storage to maximize solar self-consumption. Using metered data from 1,800 residential customers across six U.S. utilities, we show that batteries operated solely in this manner often provide no grid value, due to misalignment with market prices. Incentivizing customers to discharge storage in response to market prices, particularly on infrequent peak load days would greatly enhance storage dispatch value. However, doing so requires consideration of local distribution network impacts. We illustrate a net billing design that yields a storage dispatch value equal to 50-70% of its maximum potential market value, without materially degrading solar self-consumption levels or increasing local grid stress.

Barbose, Galen↗

Physics-constrained deep neural network method for estimating parameters in a redox flow battery

Here, in this paper, we present a physics-constrained deep neural network (PCDNN) method for parameter estimation in the zero-dimensional (0D) model of the vanadium redox flow battery (VRFB). In this approach, we use deep neural networks to approximate the model parameters as functions of the operating conditions. This method allows the integration of VRFB computational models as the physical constraints in the parameter learning process, leading to enhanced accuracy of parameter estimation and cell voltage prediction. Using an experimental dataset, we demonstrate that the PCDNN method can estimate model parameters for a range of operating conditions and improve the 0D model prediction of voltage compared to the 0D model prediction with constant operation-condition-independent parameters estimated with traditional inverse methods. We also demonstrate that the PCDNN approach has an improved generalization ability for estimating parameter values for operating conditions not used in the training process.

25 ENERGY STORAGE↗

Cost-Optimal Pathways to 75% Fuel Reduction in Remote Alaskan Villages: Preprint

There are thousands of isolated, diesel-powered microgrids that deliver energy to remote communities around the world at very high energy costs. The Remote Communities Renewable Energy program aims to help these communities reduce their fuel consumption and lower their energy costs through the use of high penetration renewable energy. As part of this program, the REopt modeling platform for energy system integration and optimization was used to analyze cost-optimal pathways toward achieving a combined 75% reduction in diesel fuel and fuel oil consumption in a select Alaskan village. In addition to the existing diesel generator and fuel oil heating technologies, the model was able to select from among wind, battery storage, and dispatchable electric heaters to meet the electrical and thermal loads. The model results indicate that while 75% fuel reduction appears to be technically feasible it may not be economically viable at this time. When the fuel reduction target was relaxed, the results indicate that by installing high-penetration renewable energy, the community could lower their energy costs by 21% while still reducing their fuel consumption by 54%.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

How Inverter-Based Resources (IBRs) Affect Protection Relay Elements

Inverter-based resources (IBRs) exhibit fault responses that differ significantly from those of synchronous generators, which can challenge the reliable operation of many commonly used power system protection elements. The fault response of IBRs is primarily influenced by their control algorithms and configurations, but the impact of these controls on protection relays is not yet fully understood. This presentation provides a comprehensive study of how IBR modeling and controls affect transmission line protection. Key modeling and control aspects include the DC source, inverter model, power level control, current control, and current limiting. The study reveals that certain aspects - such as the type of DC source (battery, PV, or hybrid), inverter model (average vs. switching), and power level control methods (PQ dispatch vs. Vdc-Vac control for grid-following IBRs, and droop vs. VSM for grid-forming IBRs) - do not significantly affect relay response. However, faster control loops, such as current control and current limiting, do influence the relay behavior. Additionally, the study explores the effects of other factors, including momentary cessation, operating points, fast/slow current responses, and grid strength on relay performance. Finally, the study offers recommendations for both IBR and protection engineers to improve IBR fault response and enhance the reliability of protection systems.

14 SOLAR ENERGY↗

A Comprehensive Study of the Impact of Inverter-Based Resource (IBR) Modeling and Control on Protection Relay Elements

Inverter-based resources (IBRs) exhibit fault responses that differ significantly from those of synchronous generators, which can challenge the reliable operation of many commonly used power system protection elements. The fault response of IBRs is primarily influenced by their control algorithms and configurations, but the impact of these controls on protection relays is not yet fully understood. This presentation provides a comprehensive study of how IBR modeling and controls affect transmission line protection. Key modeling and control aspects include the DC source, inverter model, power level control, current control, and current limiting. The study reveals that certain aspects - such as the type of DC source (battery, PV, or hybrid), inverter model (average vs. switching), and power level control methods (PQ dispatch vs. Vdc-Vac control for grid-following IBRs, and droop vs. VSM for grid-forming IBRs) - do not significantly affect relay response. However, faster control loops, such as current control and current limiting, do influence the relay behavior. Additionally, the study explores the effects of other factors, including momentary cessation, operating points, fast/slow current responses, and grid strength on relay performance. Finally, the study offers recommendations for both IBR and protection engineers to improve IBR fault response and enhance the reliability of protection systems.

14 SOLAR ENERGY↗

Review on modeling of the anode solid electrolyte interphase (SEI) for lithium-ion batteries

A passivation layer called the solid electrolyte interphase (SEI) is formed on electrode surfaces from decomposition products of electrolytes. The SEI allows Li + transport and blocks electrons in order to prevent further electrolyte decomposition and ensure continued electrochemical reactions. The formation and growth mechanism of the nanometer thick SEI films are yet to be completely understood owing to their complex structure and lack of reliable in situ experimental techniques. Significant advances in computational methods have made it possible to predictively model the fundamentals of SEI. This review aims to give an overview of state-of-the-art modeling progress in the investigation of SEI films on the anodes, ranging from electronic structure calculations to mesoscale modeling, covering the thermodynamics and kinetics of electrolyte reduction reactions, SEI formation, modification through electrolyte design, correlation of SEI properties with battery performance, and the artificial SEI design. Multi-scale simulations have been summarized and compared with each other as well as with experiments. Computational details of the fundamental properties of SEI, such as electron tunneling, Li-ion transport, chemical/mechanical stability of the bulk SEI and electrode/(SEI/) electrolyte interfaces have been discussed. This review shows the potential of computational approaches in the deconvolution of SEI properties and design of artificial SEI. We believe that computational modeling can be integrated with experiments to complement each other and lead to a better understanding of the complex SEI for the development of a highly efficient battery in the future.

25 ENERGY STORAGE↗

Status and Targets for Polymer-Based Solid-State Batteries for Electric Vehicle Applications

There is growing interest in the development of Li-metal-based solid state batteries, driven by their promise in improving the energy density to satisfy electric vehicle requirements. In this work, we examine the status of Solid polymer electrolytes (SPEs) based solid state batteries for electric vehicle applications using a continuum scale mathematical model. We examine LiFePO4(LFP) cathode/lithium metal anode batteries containing three different electrolytes, namely (1) a liquid electrolyte, (2) the polystyrene-b-poly(ethylene oxide) (SEO) block copolymer electrolyte, and (3) a single-ion conducting (SIC) block copolymer electrolyte, with the liquid electrolyte serving as the baseline for the comparison. By using an optimization procedure, we assemble "virtual" batteries to identify the optimal design that maximizes energy density while allowing the power requirements of electric vehicles (EVs) to be satisfied. Results show the present status of different SPEs are still below what is considered acceptable and further improvements are needed to achieve electric vehicle targets. The optimization studies conducted here show that for low transference number electrolytes (similar to 0.2) the conductivity target is 5 x 10(-3)S cm(-1), while for a unity transference number electrolyte this target decreases to 4 x 10(-4)S cm(-1). These targets provide guidance for polymer synthesis researchers to develop better polymers for use in EVs.

25 ENERGY STORAGE↗

Diagnostic-free onboard battery health assessment

Diverse usage patterns induce complex and variable aging behaviors in lithiumion batteries, complicating accurate health diagnosis and prognosis. Separate diagnostic cycles are often used to untangle the battery’s current state of health from prior complex aging patterns. However, these same diagnostic cycles alter the battery’s degradation trajectory, are time-intensive, and cannot be practically performed in onboard applications. Here, in this work, we leverage portions of operational measurements in combination with an interpretable machine learning model to enable rapid, onboard battery health diagnostics and prognostics without offline diagnostic testing and the requirement of historical data. We integrate mechanistic constraints within an encoder-decoder architecture to extract electrode states in a physically interpretable latent space and enable improved reconstruction of the degradation path. The health diagnosis model framework can be flexibly applied across diverse application interests with slight fine-tuning.

battery aging reconstruction↗

Modeling of Space Station power system components and their interactions

The authors demonstrate that the functional modeling approach is feasible in modeling large-scale spacecraft power systems such as the Space Station electric power system (EPS). The functional models for the solar array sequential shunt unit and the battery charging/discharging unit are presented. The functional modeling approach has also been applied to simulate other major EPS components. The usefulness of this approach in system-level studies has been demonstrated by incorporating these models into a power system model and simulating the system behavior under various conditions. The simulation results are consistent with those obtained experimentally. With larger time step size and reduced model complexity, the computation time required by the functional modeling approach is short. Functional models are effective in simulation studies of system-level issues, especially for large-scale power systems including many power electronic components.

Tam, Kwa-Sur↗

An Overview of the Design and Optimized Operation of Vanadium Redox Flow Batteries for Durations in the Range of 4–24 Hours

An extensive review of modeling approaches used to simulate vanadium redox flow battery (VRFB) performance is conducted in this study. Material development is reviewed, and opportunities for additional development identified. Various crossover mechanisms for the vanadium species are reviewed, and their effects on its state of charge and its state of health assessed. A stack design focusing on flow fields and an electrode design tailored to various flow fields are reviewed. An operational strategy that takes these parameters into account is reviewed for various operating envelopes, chosen based on end user preference in terms of minimizing capital cost or operation and maintenance cost. This work provides a framework for the design and operation of a VRFB for various grid services.

25 ENERGY STORAGE↗

From Microparticles to Nanowires and Back: Radical Transformations in Plated Li Metal Morphology Revealed via in Situ Scanning Electron Microscopy

We report that Li metal is the preferred anode material for all-solid-state Li batteries. However, a stable plating and stripping of Li metal at the anode–solid electrolyte interface remains a significant challenge particularly at practically feasible current densities. This problem usually relates to high and/or inhomogeneous Li-electrode–electrolyte interfacial impedance and formation and growth of high-aspect-ratio dendritic Li deposits at the electrode–electrolyte interface, which eventually shunt the battery. To better understand details of Li metal plating, we use operando electron microscopy and Auger spectroscopy to probe nucleation, growth, and stripping of Li metal during cycling of a model solid-state Li battery as a function of current density and oxygen pressure. We find a linear correlation between the nucleation density of Li clusters and the charging rate in an ultrahigh vacuum, which agrees with a classical nucleation and growth model. Moreover, the trace amount of oxidizing gas (≈10 –6 Pa of O 2 ) promotes the Li growth in a form of nanowires due to a fine balance between the ion current density and a growth rate of a thin lithium-oxide shell on the surface of the metallic Li. Interestingly, increasing the partial pressure of O 2 to 10 –5 Pa resumes Li plating in a form of 3D particles. In conclusion, our results demonstrate the importance of trace amounts of preexisting or ambient oxidizing species on lithiation processes in solid-state batteries.

25 ENERGY STORAGE↗

Impact of Fast Charging on Life of EV Batteries; NREL (National Renewable Energy Laboratory)

Installation of fast charging infrastructure is considered by many as one of potential solutions to increase the utility and range of electric vehicles (EVs). This is expected to reduce the range anxiety of drivers of EVs and thus increase their market penetration. Level 1 and 2 charging in homes and workplaces is expected to contribute to the majority of miles driven by EVs. However, a small percentage of urban driving and most of inter-city driving could be only achieved by a fast-charging network. DC fast charging at 50 kW, 100 kW, 120 kW compared to level 1 (3.3 kW) and level 2 (6.6 kW) results in high-current charging that can adversely impact the life of the battery. In the last couple of years, we have investigated the impact of higher current rates in batteries and potential of higher temperatures and thus lower service life. Using mathematical models, we investigated the temperature increase of batteries due to higher heat generation during fast charge and have found that this could lead to higher temperatures. We compared our models with data from other national laboratories both for fine-tuning and calibration. We found that the incremental temperature rise of batteries during 1C to 3C fast charging may reduce the practical life of the batteries by less than 10% over 10 to 15 years of vehicle ownership. We also found that thermal management of batteries is needed for fast charging to prevent high temperature excursions leading to unsafe conditions.

33 ADVANCED PROPULSION SYSTEMS↗

Energy Storage Annual Progress Report for FY15

The Energy Storage research and development (R&D) subprogram within the DOE Vehicle Technologies Office (VTO) provides support and guidance for projects focusing on batteries for plug-in electric vehicles (PEVs) in support of the EV Everywhere Grand Challenge. PEVs could have a significant impact on the nation's goal of reducing dependence on imported oil and gaseous pollutant emissions. The Energy Storage program targets overcoming technical barriers to enable market success, including: (1) significantly reducing battery cost; (2) increasing battery performance (power, energy, durability); (3) reducing battery weight and volume; and (4) increasing battery tolerance to abusive conditions such as short circuit, overcharge, and crush. The National Renewable Energy Laboratory (NREL) supports the VTO's Energy Storage program by evaluating the thermal performance of cells and packs, developing electrochemical-thermal models to accelerate the design cycle for developing batteries, investigating the behavior of lithium-ion batteries under abuse conditions such as crush, enhancing the durability of electrodes by coatings such as atomic layer deposition, synthesis of materials for higher energy density batteries, and conducting techno-economic analysis of batteries in various electric-drive vehicles. This report describes the progress made by NREL on the research and development projects funded by the DOE VTO Energy Storage subprogram in FY15.

25 ENERGY STORAGE↗

A Kinetic Model for Dissolution of Zinc Oxide Powder Obtained from Waste Alkaline Batteries in Sodium Hydroxide Solutions

The determination of individual dissolution behaviors of zinc and manganese in waste alkaline battery powders is an important subject from the points of the leaching yield, design of leaching reactor, and separation and recovery steps of hydrometallurgical process. In the current study, we investigated the dissolution kinetics of zinc oxide powder. Zinc oxide was obtained from waste alkaline batteries, and sodium hydroxide solutions were used as solvent. In the experiments, the effects of solution concentration, reaction temperature, stirring speed, solid-to-liquid ratio, and particle size on the dissolution of zinc oxide were investigated. It was demonstrated that the dissolution increased with the increasing concentration, reaction temperature, and stirring speed, and with the decreasing solid-to-liquid ratio and particle size. In consequence of the kinetic analysis performed, it was found that the dissolution kinetics of zinc powder obeyed the Avrami model. Activation energy for the process was determined to be 19.42 kJ/mol. Zinc ions in the resulting solution after dissolution process was recovered in the form of hydroxy-carbonate product by precipitation method. Zinc oxide was produced by isothermal decomposition of hydroxy-carbonate product.

36 MATERIALS SCIENCE↗

A Day at the Races: NREL Hosts Colorado Middle School Students With STEM Skills

Technology and imagination came together at the National Renewable Energy Laboratory on May 20 when 53 teams from 18 Colorado middle schools turned a parking lot into a raceway. The students used the technological know-how picked up in science, technology, engineering, and math (STEM) classes to design and build model electric cars. Powered either by a solar panel or a lithium-ion battery, each car competed in time trials and double elimination races. The final races, between eight cars competing in each category, were over in less than 10 seconds.

14 SOLAR ENERGY↗