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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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Stability and migration of charged oxygen interstitials in ThO2 and CeO2
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Effect of Fractal Silver Electrodes on Charge Collection and Light Distribution in Semiconducting Organic Polymer Films
Abstract not provided
Exchange bias effect in Au-Fe3O4 dumbbell nanoparticles induced by the charge transfer from gold
We have studied the origin of the exchange bias effect in the Au-Fe3O4 dumbbell nanoparticles in two samples with different sizes of the Au seed nanoparticles (4.1 and 2.7 nm) and same size of Fe3O4 nanoparticles (9.8 nm). The magnetization, small-angle neutron-scattering, synchrotron x-ray diffraction, and scanning transmission electron microscope measurements determined the antiferromagnetic FeO wustite phase within Fe3O4 nanoparticles, originating at the interface with the Au nanoparticles. The interface between antiferromagnetic FeO and ferrimagnetic Fe3O4 is giving rise to the exchange bias effect. The strength of the exchange bias fields depends on the interfacial area and lattice mismatch between both phases. We propose that the charge transfer from the Au nanoparticles is responsible for a partial reduction of the Fe3O4 into the FeO phase at the interface with Au nanoparticles. The Au-O bonds are formed, presumably across the interface to accommodate an excess of oxygen released during the reduction of magnetite
Charge Transfer and Built-in Electric Fields between a Crystalline Oxide and Silicon
Built-in electric fields across heterojunctions between semiconducting materials underpin the functionality of modern device technologies. Heterojunctions between semiconductors and epitaxially grown crystalline oxides provide a rich setting in which built-in fields can be explored. Here, we present an electrical transport and hard X-ray photoelectron spectroscopy study of epitaxial SrNbxTi1-xO3-d / Si heterojunctions.
Excited States Energies and Dynamics of Peridinin Analogues and the Nature of the Intramolecular Charge Transfer (ICT) State in Carbonyl-Containing Carotenoids
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Charge Carrier Dynamics of Photoexcited Co3O4 in Methanol: Extending High Harmonic Transient Absorption Spectroscopy to Liquid Environments
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Gold charge state distributions in highly ionized, low-density beam plasmas
We present a systematic study of Au charge state distributions (CSDs) from low density, nonlocal thermodynamic equilibrium plasmas created in the Livermore electron beam ion traps (EBIT-I and EBIT-II). X-ray emission from Ni-like to Kr-like Au ions has been recorded from monoenergetic electron beam plasmas having E{sub beam}=2.66, 2.92, 3.53, and 4.54 keV, and the CSDs of the beam plasmas have been inferred by fitting the collisionally excited line transitions and radiative recombination emission features with synthetic spectra. We have modeled the beam plasmas using a collisional-radiative code with various treatments of the atomic structure for the complex M- and N-shell ions and find that only models with extensive doubly excited states can properly account for the dielectronic recombination (DR) channels that control the CSDs. This finding would be unremarkable for plasmas with thermal electron distributions, where many such states are sampled, and the importance of DR is well established. But in an EBIT source, the beam is resonant with only a subset of such states having spectator electrons in orbitals with high principal quantum number n (8{<=}n{<=}20). The inclusion of such states in the model was also necessary to obtain agreement with observed stabilizing transitions in the x-ray spectra.
A Highly Efficient Control Framework for Centralized Residential Charging Coordination of Large Electric Vehicle Populations
The potential for widespread adoption of plug-in electric vehicles (PEVs) brings with it the potential for negative impacts on the electric grid from electric vehicle charging. Uncoordinated PEV charging may increase electricity demand during peak hours, which could create concerns for the grid as the number of PEVs increases. Therefore, it is important to coordinate charging to alleviate potential negative impacts. Centralized charging coordination is preferred by grid operator over distributed control strategies because it can systematically allocate energy across a large population of PEVs and achieve global coordination benefits. However, centralized methods presented in the literature to date require prohibitively expensive computational resources and lack realistic PEV charging models. As a result, they cannot achieve the efficiency and accuracy required to implement charging coordination in the real world. This paper introduces a highly efficient receding horizon control framework that enables dynamic charging coordination for large PEV populations. A two-stage hierarchical optimization routine is proposed that aggregates individual PEV charging flexibility to reduce the computational complexity of the optimization process. The control framework is based on high-fidelity, validated charging system models and charging behavior models derived from a real-world data set of residential charging activities collected from thousands of charging stations over multiple years. Case studies illustrate that the proposed charging control framework is capable of effectively coordinating the charging of millions of PEVs using a standard desktop computer.
Grid Impact Analysis of Heavy-Duty Electric Vehicle Charging Stations
This paper presents a grid impact analysis of heavy-duty electric vehicle (EV) charging stations. In this work, heavy-duty EVs have battery capacities high enough to provide a range of 250-500 miles on a single charge, such as long-haul trucks. Heavy-duty EVs will require extremely fast charging rates to reduce charging time and will induce very high charging loads (at the multiple-megawatt scale) if several vehicles charge at the same time. Therefore, analysis is needed to understand the impact of charging station loads on the electric power grid and set the baseline for developing mitigation plans and necessary system upgrades. We develop a systematic procedure to analyze the potential impact of the placement of charging stations on the grid. Charging load is modeled using a DC fast-charging station model. A voltage load sensitivity matrix approach is leveraged to investigate the challenges of placing charging stations on the feeder. Given the charging load profiles and suggested charging station locations, time-series simulations are performed on various connection points on the feeder to understand the impact. The analysis is performed on both the IEEE 34-bus system and a realistic feeder from California. Initial mitigation solutions are developed based on insights from this analysis.
Optimal charging scheduling and management for a fast-charging battery electric bus system
Herein we discuss how battery electric buses (BEBs) are rapidly being embraced by public transit agencies because of their environmental and economic benefits. To address the problems of limited driving range and time-consuming charging for BEBs, manufacturers have developed rapid on-route charging technology that utilizes typical layovers at terminals to charge buses in operation using high power. With on-route fast-charging, BEBs are as capable as their diesel counterparts in terms of range and operating time. However, on-route fast-charging makes it more challenging to schedule and manage charging events for a BEB system. First, on-route fast-charging may lead to high electricity power demand charges. Second, it may increase electricity energy charges because of charging that occurs during on-peak hours. Without careful charging scheduling and management, on-route fast-charging may significantly increase fuel costs and reduce the economic attractiveness of BEBs. The present study proposes a network modeling framework to optimize the charging scheduling and management for a fast-charging BEB system, effectively minimizing total charging costs. The charging schedule determines when to charge a BEB, while the charging management strategically controls the actual charging power. Charging costs include both electricity demand charges and energy charges. The charging scheduling and management problem is first formulated as a nonlinear nonconvex program with time-continuous variables. A discretizing method and a linear reformulation technique are then adopted to reformulate the model as a linear program, which can be easily solved using off-the-shelf solvers, even for large-scale problems. Finally, the model is demonstrated with extensive numerical studies based on two real-world bus networks. The results demonstrate that the proposed model can effectively determine the optimal charging scheduling and management for a fast-charging BEB system, which carries the potential for use in large-scale real-world bus networks.
Workplace Charging Case Study: Charging Station Utilization at a Work Site with AC Level 1, AC Level 2, and DC Fast Charging Units
This paper describes the use of electric vehicle charging stations installed at a large corporate office complex. It will be published to the INL website for viewing by the general public.
EV Charging Infrastructure Energization An Overview of Approaches for Simplifying and Accelerating Timelines to Processing EV Charging Load Service Requests
The United States has seen significant growth in electric vehicle (EV) adoption, leading to increased demand for EV charging infrastructure. Over the past decade, EV charging infrastructure site developers, site hosts, and electric distribution utilities have navigated the process to integrate chargers onto the electric grid. Site developers and site hosts have raised the alarm that the integration process for high-powered EV charging projects does not meet the needs of the EV market for timeliness or cost. High-powered charging stations typically require a load service request or an agreement with the local utility to connect to the grid. The process of energizing a new high-powered charging site can be complex and time-consuming, often taking up to 2 years. This timeline is the result of current utility energization processes having been designed for construction projects that take longer to build (i.e., buildings). The specific challenges stem from various factors, including compartmentalization in application processes, the integration of EV charging process approvals with other distributed energy resources (DERs), and the need to ensure grid reliability. The energization process needs to evolve to meet the growing demand for high-powered EV charging. This white paper compiles information gathered through various conversations with key stakeholders, including utilities, utility regulators, EV charging operators, site developers, and authorities having jurisdiction (AHJ) as well as through an extensive literature review. This document identifies the challenges and provides potential solutions to streamline the process of connecting EV charging infrastructure to the power grid in the United States, serving as a starting point for future conversations around these solutions. The solutions noted in this white paper require collaborative efforts among utilities, regulators, and EV charging infrastructure developers to streamline the grid connection process for EV charging infrastructure. They are broadly organized into four areas: 1. Increase data access and transparency: Develop automated load service request tools, integrate hosting capacity and load service request analyses, incorporate EV adoption forecasts, and provide transparency on the processing queue. 2. Improve energization processes and timing: Create fast-track options based on prescreening criteria, provide flexibility or phased approvals in the load service request/interconnection process, build internal knowledge within utilities about EV charging technologies, and provide standardized workforce training. 3. Promote economic efficiency: Right size distribution components to accurately reflect the load requirements of EV charging infrastructure, make proactive investments in grid infrastructure based on EV adoption forecasts and growth projections, and consider energy equity and environmental justice factors such as equitable access to EV charging when planning infrastructure. 4. Improve grid reliability and resilience: Use load management/power control systems (PCS) at EV charging stations, adopt and implement harmonized standards for communication protocols and information models between the EV charging and grid control infrastructure, and address cybersecurity considerations by implementing robust security measures and standards for EV charging infrastructure—with particular emphasis on clarifying the security requirements for the interface to the grid. The objective of the solutions proposed in this white paper is to accelerate the timeline and decrease costs associated with connecting EV charging infrastructure to the grid. Electric utilities, utility regulators, EV charging infrastructure developers, and site hosts will first need to understand which solutions are available in their service territory, and if warranted, which combination of solutions would support their specific needs. Through the successful implementations of solutions at scale detailed here, industry will demonstrate a new and innovative ecosystem where timely deployment and energization of EV charging infrastructure with greater grid resiliency and reliability is a reality.
Quasi-Dynamic Electromagnetic Field Safety Analysis and Mitigation for High-Power Dynamic Wireless Charging of Electric Vehicles
Dynamic wireless charging of electric vehicles (EV) is an emerging charging technology to enable non-contact wireless charging while the vehicle is moving. Compared to stationary wireless charging, in-motion wireless charging involves dynamic processes in which an EV is passing over the charging pads (transmitters). This in motion process makes the dynamic electromagnetic (EM) environment more complicated, and EM safety needs to be ensured under all circumstances. This is due to the fact that the entire vehicle body may be exposed to magnetic fields while the vehicle moves over the energized transmitter. This paper investigates several typical charging scenarios when EVs approach, pass over, and move away from the charging pads. Quasi-dynamic models, which are preliminarily verified by coils’ inductance measurements, are developed to analyze the dynamic process. Based on the quasi-dynamic analysis, shielding solutions are also studied to ensure EM safety for the dynamic wireless charging processes.
Model-Instructed Design of Novel Charging Protocols for the Extreme Fast Charging of Lithium-Ion Batteries Without Lithium Plating
Relatively long recharge time of high-energy density lithium-ion batteries (LIBs) is one of the major obstacles to the widespread deployment of electric vehicles (EVs). Excessive fast charge of LIBs can cause severe safety issues, the most significant of which is lithium plating. In addition to the consumption of cyclable lithium, dendrite-like lithium plating can cause short-circuiting within the cell, which could lead to catastrophic failure. In addition to the developments of advanced electrolytes, active materials and electrodes, the fast charging capability of LIBs can be improved by using optimized charging protocol. In this paper, the Pseudo2D battery model is first used to screen some conventional charging protocols proposed for fast charging, including the constant-current constant-voltage charging (CCCV), constant-power constant-voltage charging (CPCV), multi-stage constant-current charging, and pulse current charging. A semi-optimal charging protocol is then developed by automatically modifying the charge current such that the cell is charged at close-to-maximum current without lithium plating. Based on the features of the semi-optimal protocol, two practical novel fast charging protocols are proposed which allow charging the cell at a higher rate without lithium plating. Through simulation, we show that the no-plating capacity after 10 min charge can be improved by up to ~10.7% compared to CCCV charging for a 2.5 mAh cm -2 cell and ~18.8% for a 4 mAh cm -2 cell, when the proposed charging protocols are used.