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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 523 records · Page 29

The Impact of Behind-the-Meter Heterogeneous Distributed Energy Resources on Distribution Grids

The increasing integration of distributed energy resources (DERs) on the electric grid brings new challenges and opportunities for utility grid operations. With the rapid deployment of DERs, there is emerging interest in integrating these controllable devices with utility operations at all levels for monitoring and management. To understand the challenges with increasing behind-the-meter (BTM) DERs and to identify the needs in deploying advanced controls, a comprehensive grid impact study is indispensable. This paper presents the analysis which help visualize the DER impact on the grid, identify the challenges and provides an insight into the new distribution management and control needs to enable reliable and resilient grid operations.

behind-the-meter↗

Dual Phase Soft Magnetic Laminates for Low-cost, Non/Reduced-Rare-Earth Containing Electrical Machines

To accelerate the mass market adoption of electric drive vehicles, the key technology barriers in electric motors are (1) magnet cost and rare-earth element price volatility; (2) non-rare-earth electric motor performance; and (3) materials property optimization. The goal of this project was to address these barriers by advancing a unique and innovative dual phase soft magnetic material technology and demonstrating the material in a 30-kW synchronous reluctance motor without using any permanent magnet for electric vehicles. Dual phase magnetic materials offer the electric motor designer the ability to locally control the magnetic saturation level in a motor laminate, while at the same time enhancing the mechanical strength of the laminate material, resulting in an enhancement in motor performance and efficiency. Scalable dual phase soft magnetic laminates manufacturing technologies were developed in collaboration with multiple US manufacturers. 1000 lbs of alloy sheet with a thickness of 0.25mm and width of 280 mm was manufactured within the specifications. Batch sizes of up to 240 laminates per run were produced from the alloy sheet. Two prototype motors with dual phase soft magnetic laminates were designed, built, and tested. The major goal of building the subscale prototype as a pathway to develop scalable manufacturing technologies for the dual phase soft magnetic laminates was met. The additional goal of building and testing the subscale prototype in order to validate the calculated performance with the tested motor performance was also met. For the full-scale 30kW continuous power synchronous reluctance motor prototype, the tested performance met the targets in terms of continuous power at the operating speeds up to 8000 rpm. Post-test studies were conducted and the root causes for the discrepancy between the predicted and tested peak power, continuous power at high speed range, and efficiency were identified. Further modeling study showed that the dual phase rotor machine has a 27% higher torque to active weight ratio than an equivalent performance silicon steel rotor machine. Application space and multiple discussions with traction motor and electric vehicle manufacturers for commercialization of the dual phase soft magnetic material technology were identified and conducted. An initial cost model was established based on the developed manufacturing technologies with the US manufacturers. Future paths for further cost reduction were identified, including increasing the market volume by broadening the applications of the dual phase soft magnetic laminate technology for electric machines in other energy sections such as oil & gas, heating, ventilation, and air conditioning (HVAC), and power generation.

33 ADVANCED PROPULSION SYSTEMS↗

Towards Secure Autonomous Vehicles: An Integrated Edge and Multi-Modal Machine Learning Framework for Intrusion Detection

Autonomous vehicles (AVs) are vulnerable to cyberattacks targeting both internal communication networks and external perception sensors. While edge-based intrusion de- tection for Controller Area Network (CAN) buses offers real-time protection, it cannot detect cross-modal threats. Conversely, multi-modal fusion approaches improve coverage but often lack efficiency for in-vehicle deployment. This thesis integrates two complemen- tary solutions: (1) a lightweight, edge-deployable machine learning framework for CAN bus intrusion detection, and (2) a late-fusion system combining CAN FD and LiDAR data. Together, they form a hierarchical defense capable of handling single-modality and coordi- nated attacks. Simulations show that CAN-only models reach 93% accuracy on simulated DoS, spoofing, replay, and fuzzy attacks, while the fusion system achieves 0.87 AUC and 0.82 F1-score at 2 ms latency. This unified framework establishes a scalable, explainable, and field-ready strategy for AV cybersecurity.

97 MATHEMATICS AND COMPUTING↗

Sensor Fusion-Based Vehicle Detection and Tracking Using a Single Camera and Radar at a Traffic Intersection

Recent advancements in sensor technologies, in conjunction with signal processing and machine learning, have enabled real-time traffic control systems to adapt to varying traffic conditions. This paper introduces a new sensor fusion approach that combines data from a single camera and radar to achieve cost-effective and efficient vehicle detection and tracking. Initially, vehicles are independently detected and classified using the camera and radar. Then, the constant-velocity model within a Kalman filter is employed to predict vehicle locations, while the Hungarian algorithm is used to associate these predictions with sensor measurements. Finally, vehicle tracking is accomplished by merging kinematic information from predictions and measurements through the Kalman filter. A case study conducted at an intersection demonstrates the effectiveness of the proposed sensor fusion method for traffic detection and tracking, including performance comparisons with individual sensors.

47 OTHER INSTRUMENTATION↗

Improving the Power Outage Resilience of Buildings with Solar PV through the Use of Battery Systems and EV Energy Storage

Buildings with solar photovoltaic (PV) generation and a stationary battery energy storage system (BESS) may self-sustain an uninterrupted full-level electricity supply during power outages. The duration of off-grid operation is dependent on the time of the power fault and the capabilities of the home energy management system (HEMS). In this paper, building resilience is quantified by analyzing the self-sustainment duration for all possible power outages throughout an entire year. An evaluation method is proposed and exercised on a reference house in California climate zone 9 for which the detailed electricity usage is simulated using the EnergyPlus software. The influence of factors such as energy use behavioral patterns, energy storage capacity from the BESS, and an electric vehicle (EV) battery on the building resilience is evaluated. Varying combinations of energy storage and controllable loads are studied for optimally improved resilience based on user preferences. It is shown that for the target home and region with a solar PV system of 7.2 kW, a BESS with a capacity of 11 kWh, and an EV with a battery of 80 kWh permanently connected to the home, off-grid self-sustained full operation is guaranteed for at least 72 h.

14 SOLAR ENERGY↗

EV SALaD 2023 Demonstration: Best Practices and Mitigations for Protecting EVSE Infrastructure

The Electric Vehicle Secure Architecture Laboratory Demonstration (EV SALaD) program is a demonstration of cybersecurity best practices for high-power electric vehicle (EV) charging infrastructure led by Idaho National Laboratory (INL), in collaboration with other DOE National Laboratories participating in the EVs at Scale Consortium.a Sandia National Laboratories (SNL) and Pacific Northwest National Laboratory (PNNL) participated in the first 2-year (FY22-23) demonstration cycle for EV SALaD. This report documents the FY23 demonstration, the second in a series of demonstrations and collaborations in deploying and operating cybersecure EV charging infrastructure. It includes a summary of improvements from the FY22 demonstration, technical analysis of the FY23 demonstration, how the research demonstrates cyber-physical and cybersecurity best practices for high-power EV charging infrastructure, and related impacts to national and energy security. For EV SALaD, the FY22 demonstration focused on the detection, ranking, and prioritization of anomalous events for high-power EV charging. The FY23 demonstration additionally included the demonstration of cybersecurity best practices, which included protection and mitigation solutions to prevent, respond, and recover from anomalous events. During the demonstrations, the multi-lab EV SALaD team conducted a Test Effect Payload (TEP)b evaluation on extreme fast charger (XFC) hardware equipped with Cerberus, a detection and response solution, to demonstrate anomaly detection and mitigation cybersecurity best practices against cyber-enabled events.

33 ADVANCED PROPULSION SYSTEMS↗

Joint Optimization for Transport and Bucket Loading Phases of Automated Wheel Loaders

This article investigates optimization of fuel-efficiency and productivity for automated wheel loaders. A control-oriented model for both the transport phase and bucket loading phase is proposed. Here, the vehicle model includes an automatic gear shift schedule that can be incorporated into the optimization problem. Based on the model, the multistage optimization problem is formulated to simultaneously consider all phases of a short cycle with physical constraints. Cycle time and fuel efficiency are used as the weighted performance indexes in a multiobjective cost function. Bucket fill factor is included as a constraint during the bucket loading phase. A nonlinear programming problem is created with collocation using MATLAB and CasADi. The optimization solver IPOPT solves the problem to obtain the optimal state and control trajectories, which can be used as a reference for automated wheel loaders or even as a driver advisory for human-driven wheel loaders.

42 ENGINEERING↗

Space vehicle with customizable payload and docking station

A “black box” space vehicle solution may allow a payload developer to define the mission space and provide mission hardware within a predetermined volume and with predetermined connectivity. Components such as the power module, radios and boards, attitude determination and control system (ADCS), command and data handling (C&DH), etc. may all be provided as part of a “stock” (i.e., core) space vehicle. The payload provided by the payload developer may be plugged into the space vehicle payload section, tested, and launched without custom development of core space vehicle components by the payload developer. A docking station may facilitate convenient development and testing of the space vehicle while reducing handling thereof.

Judd, Stephen↗

High-Fidelity Analysis of EV Integration on Real Utility Feeders in Colorado

Residential electric vehicle (EV) charging has the potential to alter long-held assumptions on load characteristics impacting distribution grid planning, operations, and design standards. This study identifies analysis and control methods to increase the affordability of residential EV charging both for Xcel Energy and their customers. The project also provides solutions for more reliable grid interconnection that can support a reliable utility business model prepared for increasing EV charging load in the coming years. For this project, we referenced Level 2 alternating current (AC) onboard charging profiles for various vehicle models and high-fidelity charging data collected at the experimental setup established at the EV Research Infrastructure Laboratory at the National Renewable Energy Laboratory (NREL). Next, we developed EV adoption models for 2030 and 2040 for the Boulder and Aurora regions in Colorado. Moreover, we evaluated different smart charging control algorithms and compared their performance. We developed time-of-use (TOU)-based and grid-aware active EV charging control methods and integrated them within the study region to understand field impacts. Diving deeper, we selected 10 feeders in Boulder and Aurora for high-fidelity grid modeling down to the house level. We executed detailed grid analysis comparing the smart charge management (SCM) algorithms we developed. Finally, we created a novel tool, Electric Vehicle Infrastructure--Distribution System Integration Tool (EVI-DiST), to integrate all the approaches in a single software environment to provide easy integration, fast simulation, and detailed evaluation capability for utility engineers and other stakeholders.

33 ADVANCED PROPULSION SYSTEMS↗

Control, Fault Management, and Grid Support Functionality of an MV AC-DC Solid State Transformer based EV Extreme Fast Charging Station

Electric vehicles (EVs) have become increasingly popular in recent times while revolutionizing the consumer and commercial transportation market. The development of charging infrastructure has become one of the priorities for increasing the adoption of EVs. Extreme fast charging (XFC) technology can reduce the so-called ’range anxiety’ of consumers as they significantly reduce the charging time. With the advent of wide band-gap (WBG) power devices and improvement in power electronic converters, medium voltage (MV) solid state transformer (SST) based XFC system has the potential to replace the traditional XFC stations because of the lower footprint, ease of installation, enhanced control feature, and better system efficiency. The control system design is one of the critical aspects of the SST development process. Careful consideration and detailed analysis are required to find out suitable control method for the SST based on its topology among different centralized and decentralized control architectures. Also, the control parameters selection and potential improvement to the transient response of the controller ought to be investigated. Another major concern of the SST is different types of internal fault which reduces the overall reliability of the XFC system. As a result, designing a robust protection system is essential. Among different fault modes, open circuit switch faults have received significant attention as an active research area because of their likelihood and severe effects on converters. Therefore, the power stages used in the XFC system require functional and accurate open circuit switch fault management methods. An equally significant aspect of this SST based XFC is its compatibility in a microgrid where there is no synchronous generator present. When the grid is not available, the XFC SSTs can provide grid forming capability and continue supplying the critical loads in islanded mode. The transition between grid connected and islanded mode, especially the grid resynchronization process has to be carefully performed for the safety of the microgrid components. The challenges posed by the aforementioned issues have inspired the work done in this dissertation. Here, a 13.2 kV, 1 MVA, AC/DC SST for the XFC system is examined and a comparative analysis is conducted to select the control architecture based on feasibility of implementation and performance. A detailed control parameter design process is demonstrated considering the sensor dynamics and delay. The selected decentralized control method is augmented by introducing a novel sensor-less load current feedforward method to provide better voltage regulation at the DC bus during a change of load. Next, in the fault management section, a hierarchical failure mode effect analysis (FMEA) is proposed to enable a systematic design of the internal fault protection of the XFC SST as there are limited examples in the literature regarding the analysis of the safety and design of the protection of a power electronic converter system. Novel open circuit switch fault management methods for the converters in the system are presented. Finally, XFC SST based MV microgrid operations in grid connected mode and islanded mode are explored. A secondary control method for grid resynchronization is presented and a design process of control parameters is shown to ensure the stability of the secondary voltage and frequency regulation.

30 DIRECT ENERGY CONVERSION↗

Time-Varying Output Delay Compensation-A Model-Free Approach and its Application on Cooperative On-Ramp Merging

This paper presents a model-free approach to compensate for time-varying output delay in networked control systems. The proposed architecture combines a model-free observer and the Smith predictor. The model-free observer estimates the current state while handling modeling errors and uncertainties of the system. The Smith predictor moves the effect of time delay outside the control closed-loop using the estimated delayed output and the actual output of the plant. The proposed method is applied to a cooperative on-ramp merging problem. First, an ultra-local model predictive control is implemented to provide a computationally efficient online speed planner agnostic to the vehicle dynamics. After that, a model-free observer is designed to estimate the current state. Finally, the proposed architecture is tested against a time-varying output delay with an upper bound of 200 milliseconds. The results demonstrate the effectiveness of the proposed method with improved tracking of intervehicle distance.

Waleed khan, Muhammad [The University of Texas at ↗

Cooperative On-Ramp Merging with Time-Varying Vehicle-to-Vehicle Communication Delay Compensation via a Model-Free Approach

Cooperative merging strategies enabled by vehicle-to-vehicle (V2V) communication have shown promise in addressing congestion, fuel inefficiency, and collision risks. However, their performance can be severely degraded by time-varying and uncertain communication delays-an issue often overlooked in existing research, which primarily focuses on merging sequence determination and trajectory planning. Furthermore, practical considerations such as heterogeneous vehicle dynamics, varying road conditions, and real-time implementation complexities are frequently neglected. This paper presents a model-free, online planning framework for cooperative on-ramp merging of connected and automated vehicles (CAVs), explicitly accounting for time-varying V2V communication delays. Without relying on detailed vehicle dynamics, the proposed method introduces a data-driven delay compensation scheme. A co-simulation platform integrating high-fidelity vehicle dynamics, traffic simulation (SUMO), and V2V communication within MATLAB/Simulink is developed to evaluate the proposed method. Simulation results demonstrate that unaddressed V2V communication delays significantly impair merging performance. In contrast, the proposed framework enhances intervehicle distance tracking and maintains low CO2 emissions and fuel consumption, under communication delay across different communication frequencies. In conclusion, its lightweight design also facilitates real-time implementation, making it well-suited for deployment in practical CAV systems.

Accounting↗

Estimation of Arrivals on Green at Signalized Intersections Using Stop-Bar Video Detection

Across the world, traffic congestion is increasing with alarming rapidity. Traffic signal control effectiveness, in coordinated networks, is often investigated in relation to the type of vehicle arrivals at the signalized intersections. Recently, several transportation agencies have switched from traditional loop detectors to video detection. When video cameras are accompanied by computer vision, one can extract more information about traffic “dynamics” than by using traditional inductive loop detectors. Collecting arrival times of multiple vehicles after the first arrival at the stop-bar detector might be challenging when using inductive loop detectors (since after the first arrival, detector status is always occupied). However, emerging video detection systems allow tracking of each vehicle’s entrance time in the detection zone, departure time from the detection zone, and the type of vehicle. This information can be used to estimate vehicular arrival and departure times, which then can be fed into machine learning algorithms to estimate arrivals on green (AOG). However, such research ideas have not been documented so far. Thus, this paper presents an estimation model for AOG, which was developed using multigene genetic programming. A robust experimental dataset was collected from a highly calibrated and validated microsimulation model of an 11-intersection corridor in Chattanooga, TN. The results of the model’s performance analysis showed the high accuracy of the training-, testing-, and validation datasets. The practical benefit of this model is that it can be applied to estimate arrival types at intersections where only stop-bar video detection exists.

Engineering↗

Poly(oxymethylene) Ethers as a High Cetane, Low Sooting Biofuel Blendstock for Use in Medium to Heavy Duty Mixing Controlled Compression Ignition Engines

Compression ignition (CI) engines are currently the most common prime mover for medium and heavy duty vehicles; these engines contribute roughly a quarter of US greenhouse gas emissions from transportation, and even higher percentages of particulate and nitrogen oxide emissions. As a result, there have been significant efforts made to reduce these emissions, particularly through selection of low-emissions alternative fuels. Oxymethylene ethers (OMEs) are a class of molecule, typically structured R-O-(CH2O)n-R', which have been considered as a possible blendstock in CI fuels for the goal of soot reduction. Generally, past work has focused on methyl-terminated OMEs, CH3-O-(CH2O)n-CH3, which by virtue of containing no C--C bonds, produce negligible soot. These molecules show significant reductions in soot emission from engines when blended in moderate to high ratios with traditional diesels, however, they have been shown to have inferior physical properties and poor compatibility with some legacy systems. Recent theoretical work has shown that OMEs with non-methyl alkyl groups may have superior performance, albeit at the cost of increased soot formation. In this work, a variety of OMEs with terminating alkyl groups from methyl to butyl are considered for their suitability as CI fuels. The synthesis of these extended OMEs is studied, including formation of n=1 OMEs from common chemical sources, and extension of the chain length to heavier molecules, via reactions over acidic ion exchange resins. Following the synthesis, the properties of these OMEs are studied with respect to their engine applicability. It is found that heavier (propyl- and butyl-terminated) OMEs have superior properties for diesel compatibility, particularly in reactivity, volatility, and water solubility. Extended-alkyl OMEs are found to have higher soot production than methyl-terminated OMEs, but remain superior to diesel soot production on a per-unit-energy basis. A sample of a butyl-terminated OME mixture, n=2-4, is selected as the ideal OME blend for close compatibility with legacy diesel systems. This mixture is blended with certified diesel and tested for ASTM D975 compatibility, passing all required tests but lubricity; decreased heat of combustion is observed but not governed by the diesel standard. Fundamental combustion tests of various mid-weight OMEs are performed in a rapid compression machine, where it is shown that low-temperature chemistry causes a region of decreased dependence of ignition delay on temperature, consistent with methyl-terminated OME behavior. An isopropyl-terminated OME is observed to have low reactivity compared to other OMEs; this fuel is investigated via further rapid compression machine testing and CFR engine testing. It is found that this OME has strong negative-temperature-coefficient ignition behavior - a first for OMEs - and has reactivity lower than other OMEs, but insufficient for direct spark ignition engine testing.

09 BIOMASS FUELS↗

Mission aware cyber safe mode for spacecraft

Mission-Aware Cyber Safe Mode (MACSM) is spacecraft resilience architecture that enables autonomous containment of software-level cyber intrusions while maintaining control authority and mission continuity. It is analogous to traditional safe modes that preserve vehicle survival by shutting down non-essential subsystems in response to faults or environmental stress.

97 MATHEMATICS AND COMPUTING↗

Autonomous Energy Systems: A Distributed Approach to Control Millions of Energy Devices

Energy systems of all sizes are becoming increasingly complex. The National Renewable Energy Laboratory has developed new controls that will support real-time operations and management of renewables, storage, electric vehicles and loads for grid efficiency and resilience. This fact sheet presents an overview of these autonomous energy systems.

AES↗

Electric Vehicle Managed Charging: Forward-Looking Estimates of Bulk Power System Value

When and where electric vehicle charging occurs has significant implications for power systems supporting widespread electric vehicle deployment with high shares of wind and solar generation. Numerous studies have estimated the value of scheduling or otherwise managing electric vehicle charging in such power systems. This study improves on those earlier works by leveraging detailed simulation models for electric vehicle adoption, electric vehicle use, electric vehicle charging, and bulk power system operations; and linking them with methods for describing charging flexibility at both the individual vehicle and aggregate levels. This study closely analyzes electric vehicle managed charging (EVMC) performance along the dimensions of flexibility type (within-charging session or within-week scheduling), dispatch mechanism (direct load control or one of several price-based mechanisms), and participation rate, under the assumptions of ubiquitous chargers and all trips completed on time. The study is located in a passenger light-duty vehicle adoption scenario with 100% electric vehicle sales by 2035, and in an envisioned 2038 New England power system for which within-region generation is 84% clean.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Powering the Blue Economy: A Survey of Station-Keeping Methods for Mooringless Platforms

The term “ocean platform” is used to reference everything from stationary, typically moored, buoys to mobile water vehicles, whether they operate on the ocean’s surface or underwater. For certain applications for which relatively stationary station-keeping conditions are desired, the use of mooring systems is not always a viable alternative either for economic, environmental, regulatory, or otherwise practical reasons, or a combination thereof, (e.g., short deployments, sensitive ecosystems, very deep project sites). Maintaining a platform at a single waypoint or reference location without being moored would require additional control systems and a power source to counteract the drift forces that would naturally displace it. Mobile platforms, which are usually untethered except for remotely operated vehicles, typically require energy input to power their station-keeping capabilities so that they hold or control their location in the ocean. Currently, most of these platforms use combustion engines or batteries for this purpose, which, depending on the specific systems, may be costly, pollute the environment, or create limitations on the length of the deployment. However, powering this kind of platforms with surrounding renewable resources (waves, currents, winds, or sun) has been identified as a promising solution to expand their application. The intent of this report is to investigate station-keeping methods for various ocean platforms that are not moored or otherwise anchored to the ocean floor, or another platform or vessel, paying particular interest to technologies that use marine renewable resources to power their operation, because that is of particular interest to the U.S. Department of Energy’s Powering the Blue Economy (PBE) initiative. As a first step, 72 articles and technical reports related to mooringless station-keeping methods were collected for review. The preliminary literature review provided a broad overview of common themes across the literature from which a descriptive methodology for analyzing various platforms was developed. That is, station-keeping methods were categorized based on their predominant energy source and consumption (renewable, nonrenewable, or hybrid if the platform uses renewable and nonrenewable resources equally), and their localization strategy (drift reduction, “path-planning or “waypoint-holding”). In addition, platform types were segregated into the following groups: buoys, surface drifters, and unoccupied surface vehicles (USVs); offshore renewable energy systems; and unoccupied underwater vehicles (UUVs). The main types of station-keeping methods encountered in this report achieve their intended localization strategy by means of drift mitigation, steering, and/or propulsion. Drift mitigation is commonly accomplished via drogues and sea anchors. Stand-along steering subsystems use control surfaces (e.g., ship rudder, wing sail, etc.) that react to ocean currents, waves, or winds to provide varying-degrees of course adjustments. Combined steering and propulsion subsystems include differential thrusters, directional thrusters separate from a primary thruster that cause the platform to pitch up/down or yaw clockwise/counterclockwise, or vectored thrusters that direct the propulsion in a range of directions relative to the platform’s local coordinate system. Propulsion is often achieved by running a motor and applying active control strategies but can also involve buoyancy shifts and using sails to generate lifting forces that propel a platform in a desired direction. Future research is primarily expected to take place in the form of a technoeconomic analysis that would aim to determine the technological viability, cost, and added value of mooringless station-keeping use cases identified through this research, including docking for UUV recharging or for georeferencing drifter buoys, deep-sea floating wind farms, U.S. Navy sonar arrays, and a Pacific Ocean wave buoy network.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗