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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Development of a Hardware-in-The-Loop Testbed for a Decentralized, Data-Driven Electric Vehicle Charging Control Algorithm

This study presents the design of an electric vehicle (EV)-grid integration (EVGI) hardware test-bed to implement smart EV charging algorithms. Here, the proposed test-bed also allows to create different grid events via flexible integration of other power hardware (e.g., controllable loads and battery energy storage systems) and test their impacts on EV charging. The design uses a real-time digital simulator to realize a complex distribution grid model with primary and secondary networks. A grid simulator physically realizes the selected nodes of the simulated grid to power an actual EV, forming a hardware-in-the-loop (HIL) test setup. The EV-grid integration is demonstrated based on the custom hardware and software implementation of the J1772 charging protocol using dSPACE MicroLabBox, operating as a custom EV Supply Equipment (EVSE). The HIL test-bed features a novel testing platform for accurate implementation and analysis of scalable charging algorithms. To this end, a data-driven, decentralized, model-free charging controller based on the Additive Increase and Multiplicative Decrease (AIMD) algorithm is presented and validated on an EV using the HIL test-bed. We tested the proposed algorithm under various case studies, and presented a comparison study with an existing droop-based, decentralized charging solution. The results showed that the EV successfully performed charging commands generated by the EVSE and regulated its charging power to effectively reduce the system loading caused by high EV penetration.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

Quantifying policy gaps for achieving the net-zero GHG emissions target in the U.S. light-duty vehicle market through electrification

The U.S. light-duty vehicle (LDV) industry, a major greenhouse gas (GHG) emitting sector, is embracing decarbonization. Considering only electrification pathways, this study uses publicly-available tools – MA3T and VISION on vehicle market penetration, fleet accounting and life-cycle analysis to quantify the policy gaps for LDVs to achieve the net-zero GHG emissions target in nine vehicle penetration cases under two electricity mix scenarios, including the U.S. administration's decarbonization strategy – 100% clean electricity by 2035. The MA3T model is a multinomial discrete choice model for market share projection by vehicle technology, and the VISION is a vehicle stocks and GHG emissions projection model by using vehicle and travel characteristics. This study projects the impacts of technology and policy enforcement on shaping the dynamics and decarbonization of the LDV market. Additionally, achieving the expected improvement of battery technology and charging infrastructure is critical but can only reduce the 2050 GHG emissions to 48–54% of the 2020 level under the electricity renewable mix scenario. It is almost impossible to achieve a 100% battery electric vehicle stock by 2050 and the 2050 net-zero target in the LDV industry unless ban of internal combustion engine technology is implemented starting in 2035 and under the 2035 100% clean electricity scenario. These extreme conditions also sacrifice most from the consumer welfare perspective. A greater policy forcing intensity accelerates plug-in electric vehicle penetration, while with declining marginal effect and reduced consumer welfare. Among the investigated policy scenarios, the policy forcing intensity equivalent to a fuel tax of $1–2 per gasoline gallon reduces the most GHG emissions while keeping a positive consumer welfare.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

Flexible Grid-Based Electrolysis Hydrogen Production for Fuel Cell Vehicles Reduces Costs and Greenhouse Gas Emissions

Hydrogen fuel cell electric vehicles (FCEVs) have been proposed as an option for lowering carbon dioxide (CO 2 ) and pollutants emissions from the transportation sector, when implemented in combination with green hydrogen production methods such as water electrolysis powered by renewable electricity. FCEVs also have the added advantages of high specific energy density and rapid refueling, two important challenges that battery electric vehicles have not yet fully overcome. Moreover, flexible operation of electrolysis could support the grid and lower electricity costs. In this paper, we simulate time-varying FCEV hydrogen refueling demand for light, medium- and heavy-duty vehicles met using electrolysis systems distributed throughout the Western U.S. power system. We find that by oversizing electrolyzers the resulting load flexibility results in different hydrogen generation temporal profiles, average electricity costs, renewable curtailment levels, and CO2 emissions. Our results indicate that increasing hydrogen production flexibility lowers hydrogen and electricity generation cost and CO 2 emissions, but there is a tradeoff between lowering operational cost and increasing electrolyzer capital cost, yielding a minimum total system cost at a size corresponding to between 80% and 90% annual capacity factor assuming a future electrolyzer cost of $300/kW.

25 ENERGY STORAGE↗
DOE OSTI2023

Silicon Carbide Inverter for Off-Road Heavy-Duty Applications: The Importance of Thermal and Thermomechanical Design in Power Electronics Packaging

Electrification of drivetrain systems is now seen as a major opportunity by the transportation industry across the globe to reduce the greenhouse gas emissions and revolutionize the travel patterns of millions of people. The cumulative number of plug-in hybrid and battery electric vehicles (EVs) sold in the United States has now surpassed 2 million in 2021, according to the International Energy Agency. The introduction of EVs in different classes of passenger vehicles and the continued drop in prices spurred by government incentives have attracted the attention of consumers despite certain barriers, such as higher initial cost and range anxiety. In the United States, the EV market share is now growing at an exponential pace, with the domestic automakers allocating a lion's share of new and future car sales to EVs. Additionally, different market studies project decreasing cost and rising sales of medium- and heavy-duty electric trucks. Although electrification initiatives are strongly pursued in the on-road passenger vehicle market, off-highway sectors, such as construction, mining, and agriculture, are also gradually implementing electric drivetrain technologies in their machineries. As EVs grow in popularity on a global scale, innovative drivetrain technologies must meet the increasing energy demand by significantly increasing system efficiency.

ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2023

MODELING AND OPTIMIZATION OF A PCM-BASED OCEAN THERMAL ENERGY HARVESTER FOR POWERING UNMANNED UNDERWATER VEHICLES

As oceans cover over 70% of the planet’s surface, they represent a large reservoir of resources that remained vastly untapped. Uncrewed Underwater Vehicles (UUVs) are becoming key technology for ocean exploration. Ocean thermal gradient is a permanent and reliable energy source that can be used to power UUVs using phase change material (PCM)-based thermal engines. However, the main drawback of this technology is its low conversion efficiency. When using PCM-based thermal engines to power UUVs, there are different energy conversion stages, thermal-hydraulic, hydraulic-kinetic, kinetic-electrical, dependent of a wide variety of parameters. Thus, optimization of the overall energy conversion is still a challenge for powering the increasing energy demanding UUVs for long missions. The goal of this study is to propose a PCM-based ocean thermal energy harvesting system for powering the Solo II float. Using the ocean thermal energy reduces the cost for battery replacement and expands the float’s mission time. For this purpose, we developed a multiphysics model for a system consisting of thermal material, hydraulic, and electrical systems. This system is designed to provide the electrical power needed for the instruments aboard the underwater vehicle. The models of the hydraulic and the electric systems are implemented in MATLAB-Simulink/Simscape environment. The final model developed can provide 13.66 kJ of electrical energy, which is more than 1.5 times the energy requirement per cycle for the SOLO II float.

Ouro-Koura, Habilou↗
DOE OSTI2025

Clean Cities and Communities Partnership 2023 Activity Report

This is the 2023 report for the Clean Cities and Communities (CC&C) partnership. It tracks the metrics that have been reported by individual coalitions and aggregated to the national level. It looks at the various outreach activities, grant activities, and implementation of clean transportation technologies. Such technologies include natural gas vehicles, electric vehicles, propane vehicles, hydrogen fuel cell vehicles, biodiesel, ethanol, idle reduction technologies, fuel economy improvement technologies, vehicle-miles-traveled reduction technologies, and off-road technologies. The CC&C partnership had an energy use impact of over 1 billion gallons in 2023 and reduced emissions by nine million tons. Outreach, engagement, and training activities increased 18% from last year.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Advancing Federal Infrastructure Through Innovation: Selecting Electric Vehicle Charging Infrastructure Wisely

The Biden Administration's issuance of Executive Orders directly addressing and accelerating Federal fleet electrification places an onus on both fleet and facility managers. This panel will help fleet and facility personnel understand how to select EVSE infrastructure in terms of implementation, energy management, and costs of procurement, installation/deployment, and electricity. The panel will cover technology aspects to include managed EVSE, bi-directional charging, implications on local electrical systems and storage needs in certain cases to buffer power demand. Discussion will include various considerations relevant to ensuring adequate EVSE, balancing infrastructure needs, and upgrades with fleet needs. The panelists will discuss how to provide sufficient infrastructure support, including which stakeholders to involve, procurement impediments, easement locations, and requirements that arise during the design and implementation process.

ADVANCED PROPULSION SYSTEMS,ENERGY PLANNING, POLIC↗
DOE OSTI2024

Improving Efficiency of Off-Road Vehicles by Novel Integration of Electric Machines and Advanced Combustion Engines

Modern off-road equipment will increasingly rely on electrified implements that will deliver precision control with a smaller footprint than hydraulics. The primary energy converter, however, will be an onboard reciprocating internal combustion engine because of the power density of hydrocarbon fuels in comparison to electrical energy storage and the remote locations where much of this equipment is deployed. Adding energy storage and electric machines creates opportunities to improve efficiency while reducing emissions. This program investigated approaches to take advantage of the extra flexibility that an enhanced electrical system to enable high-efficiency, low-emissions combustion technologies. The current program evaluated hybridization of both the torque application and air-handling systems to maximize efficiency while minimizing cost. This program designed, analyzed and tested a hybrid off-road vehicle consisting of a series electric powertrain with energy storage, an electrified air system, and a 33% downsized diesel engine. Detailed comparisons were made between the base powertrain and the developed powertrain using powertrain simulations, engine testing, and vehicle testing. The key results of the study are: • The resulting vehicle reduces fuel consumption by 5% to 15% at equal productivity. The primary improvements were due to recovery of regenerative braking losses for cycles where large transients are encountered. • The electrified air system was an enabler to allow engine downsizing. This was most important for duty-cycles where the engine primarily operated at moderate loads and had few low speed high torque conditions. • Engine level improvements showed re-optimization of the powertrain is possible when electrified air handing is available. Increased exhaust gas recirculation and advanced injection timing allowed up to a 15% reduction in brake specific fuel consumption at equal NOx and transient response. Compared to the larger engine, the downsized engine achieves up to an 18% reduction in brake specific fuel consumption over the non-road transient cycle. • The life cycle analysis and total cost of ownership study showed that the hybrid powertrain has the potential to reduce 5-year CO2 and total cost of ownership by ~6% over the baseline vehicle. The results also indicated that a pure battery electric vehicle is not feasible in this application and is likely to increase the CO2 emissions due to the CO2 from battery production. A hybrid powertrain with low carbon fuels shows the potential to substantially reduce CO2 and total cost of ownership.

02 PETROLEUM↗
DOE OSTI2024

Cybersecurity Lessons Learned from Vehicle to Grid Engagement

As the transportation industry continues to become electrified, introduction of additional digital devices within associated actions such as recharging bring additional potential for cybersecurity attacks. Devices that are designed, implemented, and operated with cybersecurity as a crucial consideration exacerbate these concerns by failing to provide strict boundaries on access to and use of the equipment. Emerging use cases such as Vehicle to Grid (V2G) charging may expand the potential physical effects of a cybersecurity attack by providing indirect access to electrical components of a building microgrid or portions of the larger power grid. This paper serves as an overview of findings and recommendations based on cybersecurity testing performed at a V2G implementation site operated by a member of the Memorandum of Understanding (MOU) to Establish the Vehicle-to-Everything (V2X) Collaboration [1]. The Department of Energy Office of Cybersecurity, Energy Security, and Emergency Response is a signatory of the MOU, and has funded this research paper and associated body of work regarding V2X cybersecurity. Sandia has a large background of previous research focused on Electric Vehicle (EV) cybersecurity, such as reference [2], which includes an overall survey of EV infrastructure cybersecurity and recommendations based on those findings. This report seeks to expand knowledge of EV cybersecurity status and needs by focusing on a specific implementation of V2G charging, and providing recommendations based on the relevant findings. This report serves as a publicly available, sanitized description of applied vulnerability testing on an operational V2G implementation. A more in-depth technical version of the report is provided to the MOU partner, but not available at the time of writing due to inclusion of proprietary information. V2G charging comes with many research problems that must be solved before the technology can securely implemented in sites with unrestricted public access or where cybersecurity attacks could have increased consequences, such as government offices. V2G charging requires many stakeholders such as end users, host sites, equipment vendors, and integrators, which all rely on operational safety and security as well as security and trustworthiness of any associated financial transactions.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2021

A Review of Existing and Emerging Methods for Lithium Detection and Characterization in Li-Ion and Li-Metal Batteries

Whether attempting to eliminate parasitic Li metal plating on graphite (and other Li-ion anodes) or enabling stable, uniform Li metal formation in ‘anode-free’ Li battery configurations, the detection and characterization (morphology, microstructure, chemistry) of Li that cannot be reversibly cycled is essential to understand the behavior and degradation of rechargeable batteries. In this review, various approaches used to detect and characterize the formation of Li in batteries are discussed. Each technique has its unique set of advantages and limitations, and works towards solving only part of the full puzzle of battery degradation. Going forward, multimodal characterization holds the most promise towards addressing two pressing concerns in the implementation of the next generation of batteries in the transportation sector (viz. reducing recharging times and increasing the available capacity per recharge without sacrificing cycle life). Such characterizations involve combining several techniques (experimental- and/or modeling-based) in order to exploit their respective advantages and allow a more comprehensive view of cell degradation and the role of Li metal formation in it. Additionally, it is also discussed which individual techniques, or combinations thereof, can be implemented in real-world battery management systems on-board electric vehicles for early detection of potential battery degradation that would lead to failure.

25 ENERGY STORAGE↗
DOE OSTI2021

Quantification of heterogeneous, irreversible lithium plating in extreme fast charging of lithium-ion batteries

Realization of extreme fast charging (XFC, ≤15 minutes) of lithium-ion batteries is imperative for the widespread adoption of electric vehicles. However, dramatic capacity fading is associated with XFC, limiting its implementation. To quantitatively elucidate the effects of irreversible lithium plating and other degradation mechanisms on the cell capacity, it is important to understand the links between lithium plating and cell degradation at both the local and global (over the full cell) scales. Here, we study the nature of local lithium plating after hundreds of XFC cycles (charging C-rates ranging from 4C to 9C) in industrially-relevant pouch cells using spatially resolved X-ray diffraction. Our results reveal a spatial correlation at the mm scale between irreversible lithium plating on the anode, inactive lithiated graphite phases, and local state-of-charge of the cathode. In regions of plated lithium, additional lithium is locally and irreversibly trapped as lithiated graphite, contributing to the loss of lithium inventory (LLI) and to a local loss of active anode material. The total LLI in the cell from irreversibly plated lithium is linearly correlated to the capacity loss in the batteries after XFC cycling, with a non-zero offset originating from other parasitic side reactions. Finally, at the global (cell) scale, LLI drives the capacity fade, rather than electrode degradation. We anticipate that the understanding of lithium plating and other degradation mechanisms during XFC gained in this work will help lead to new approaches towards designing high-rate batteries in which irreversible lithium plating is minimized.

25 ENERGY STORAGE↗
DOE OSTI2022

Caldera_Grid

Caldera Grid is part of Caldera software platform, a suite of collective, open-source tools that was developed to improve the state of the art in modeling the impacts of Electric Vehicle (EV) charging on the grid. Caldera Grid is a co-simulation framework implemented using Hierarchical Engine for Large scale Infrastructure Co-Simulation (HELICS). The framework facilitates the co-simulation of EV charging and Smart Charge Management (SCM) strategies in Caldera Infrastructure Charge Model (ICM) with distribution level grid models in OpenDSS. Vehicle energy needs and charge session requirements generated using Caldera Charge Decision Module (CDM) are fed in as input to Caldera Grid. The EV charging models in Caldera ICM simulates both the uncontrolled charging loads as well as loads modified by the SCM strategies to develop distributed load profiles for each grid node hosting an Electric Vehicle Supply Equipment (EVSE) – also known as chargers. These loads were simulated in OpenDSS alongside existing distribution feeder loads. Each of these models are co-simulated in a HELICS federate. The HELICS co-simulation framework facilitates communication and synchronization between the federates. By co-simulating EV loads and distribution feeder loads, Caldera Grid can assess the potential grid impacts of EV charging on distribution feeders under various grid conditions. A control strategy federate is implemented with an interface where control strategies based on feedback from EV charging status and grid conditions can be developed and implemented. The platform can also support multiple control strategies in a single co-simulation.

Sundarrajan, ManojKumar Cebol↗
DOE OSTI2024

Value-based Insights from the Implementation of Hierarchical Control for Energy Savings and Demand Response in Residential Premises

As the adoption of distributed energy resources and electric vehicles at residential customer premises increases exponentially, behind-the-meter assets can be utilized to achieve energy cost reduction and demand response through coordination and control strategies. A hierarchical control architecture from the utility headend to residential premises is implemented to attain these objectives. This paper extracts the values from the development, implementation, and deployment of that control hierarchy. The development of the control philosophy is built upon the existing advanced metering infrastructure, communication protocols, and industry-compatible application programming interfaces. Results are presented visually with analytical insights by utilizing the data from hardware-in-the-loop testing and simulation analysis out of the collected data from the field.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Timeouts Best Practices

This study investigates common timeouts encountered in the electric vehicle (EV) charging communications process. Many different timeouts are defined within the EV charging communications protocols. These timeouts can either be a fixed value or a defined range of values. In both cases, the timeout defines the duration of time for which one or both parties in the communications session are expected to wait for some action or process to complete before terminating the charge attempt. These timeout-based terminations are intended to prevent the charging process from becoming stuck indefinitely in any particular step. These terminations also enable a retry of the terminated charging session to begin. However, misaligned timeout values can have a significant negative impact on the user experience. Premature termination of charging sessions due to inappropriate timeout settings can lead to charging failures, causing inconvenience, wasted time, and frustration for users. These disruptions can degrade the overall user experience, making it essential to carefully manage and align timeout values with the relevant actions and processes to ensure reliable and satisfactory EV charging sessions. The core objective of this study is to boost reliability and enhance user experience by conducting a thorough review of timeout-based issues in EV charging and delivering a set of recommendations to modify these existing timeouts. These recommendations are informed by feedback gathered from multiple EV charging partners. This document is intended to inform electric vehicle supply equipment (EVSE) and EV manufacturers, EV charging infrastructure developers, and policymakers responsible for designing and implementing EV charging protocols and systems.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

Improving the Freight Productivity of a Heavy-Duty, Battery Electric Truck by Intelligent Energy Management

This project aimed to enhance the range and reduce the operating costs of battery electric Class 8 trucks traveling over 250 miles daily. This was achieved through the development and implementation of an intelligent-Energy Management System (i-EMS) that leverages vehicle and operations data, physics-aware machine learning algorithms, and vehicle-to-cloud (V2C) connectivity. The project hypothesized that advanced machine learning algorithms and real-time data analytics could significantly improve the energy efficiency and range of these trucks. Key objectives included developing a physics-aware machine learning algorithm, implementing an i-EMS with V2C connectivity and physics-aware spatial data analytics (PSDA), and validating the system’s effectiveness with fleet partners HEB Companies and Murphy Logistics. Extensive data collection from vehicle operations, including vehicle characteristics, road conditions, and payload, was conducted. A machine learning algorithm was developed to predict energy consumption and enable proactive decision-making. The i-EMS was implemented on two Volvo VNR BEVs, with operators receiving charging and routing recommendations. Charging stations were installed at depot locations in Texas and Minnesota, with an additional on-route charger in Minnesota. Significant findings included a 14% range improvement for Murphy Logistics on a highway-driving eco-route and a 22% range improvement for HEB Companies on a city-driving eco-route. The i-EMS utilized rule-based methods and physics-based algorithms to predict and reduce energy consumption, with real-time monitoring and analysis through V2C connectivity enabling proactive decision-making. The project demonstrated the feasibility and economic viability of battery electric Class 8 trucks for long-haul operations, showcasing the potential of physics-aware machine learning in optimizing energy management. The successful implementation of the i-EMS in real-world scenarios validates its practical application and effectiveness, paving the way for the widespread adoption of battery electric vehicles in the freight transportation industry.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Joint optimization of electric bus charging infrastructure, vehicle scheduling, and charging management

High upfront costs of vehicles and charging infrastructure as well as the lack of knowledge related to infrastructure planning and electric bus system operation are major obstacles to the implementation of battery electric buses (BEBs). To tackle the obstacles and promote BEB adoption, a comprehensive optimization framework was developed to address the combined charging infrastructure planning, vehicle scheduling, and charging management problem for BEB systems, with the goal to minimize the total cost of ownership. The problem was formulated as a mixed-integer non-linear problem. A genetic algorithm-based approach was then proposed to solve the problem. Last, three alternative scenarios based on a sub-transit network in Salt Lake City, Utah, were analyzed and compared with the optimal scenario results in the numerical experiments. Our comparison results demonstrate the effectiveness of the proposed model and solution algorithm in determining a cost-efficient planning strategy for BEB systems.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

Intelligent, grid-friendly, modular extreme fast charging system with solid-state DC protection

The development of electric vehicle (EV) charging infrastructure is crucial for the widespread adoption of electric transportation. However, implementing such infrastructure is a complex task that requires consideration of factors such as space limitations, adherence to industry standards, grid capacity, and other technical and policy issues. This project seeks to create a framework for the efficient design of compact medium voltage (MV) extreme fast charging (XFC) stations for EVs. The station design involves the use of a solid-state transformer (SST) that connects to the MV distribution network, delivering power to a shared DC bus. This innovative approach eliminates the need for a step-down transformer to provide low-voltage service by connecting directly to the MV distribution network. Eliminating the low-frequency transformer not only reduces the system footprint and losses but also eliminates inrush currents during grid black-start. Additionally, placing power electronics directly on the distribution system allows for high-bandwidth filtering and power factor correction. The inclusion of a shared DC bus enables multiple charging dispensers and DC storage/generation units to connect, forming a DC microgrid. This setup facilitates power sharing with minimal conversion stages. The project showcases a DC distribution network protected by intelligent solid-state (SS) DC circuit breakers (DCCB) capable of isolating the smallest section of the faulted circuit much faster than existing mechanical solutions.

24 POWER TRANSMISSION AND DISTRIBUTION↗