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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Accelerating Battery Simulations by Using High Performance Computing and Opportunities with Machine Learning

The US Department of Energy (DOE) estimates that the battery pack cost of $60 per kilowatt-hour while increasing the driving range to over 300 miles and vehicle charging under 15 min or less would enable mass penetration of electric vehicles in the USA by 2030. These projections are based on the currently available high-density cell chemistry combined with a system level design and optimized electrodes. Electrodes for current state-of-the-art lithium-ion cell technology are fabricated from electrode slurry comprising of active material, polymeric binder, and conductive diluent such as carbon black that are coated on metal current collectors such as copper and aluminum. Given these challenging requirements for development of electrical energy storage devices for future transportation needs, a predictive simulation capability which can accelerate design by considering performance and safety implications of different geometry, materials, and chemistry choices is required. In this chapter, we discuss our state-of-the-art three-dimensional modeling framework, providing examples on battery performance and safety simulations. We also present approaches to use machine learning in the context of large datasets that are becoming available.

Allu, Srikanth↗
NASA NTRS1982

Vehicle test report: Battronic pickup truck

An electric pickup truck was tested to characterize certain parameters and to provide baseline data that can be used for the comparison of improved batteries that may be incorporated into the vehicle at a later time. The vehicle tests were concentrated on the electrical drive subsystem; i.e., the batteries, controller, and motor. The tests included coastdowns to characterize the road load and range evaluations for both cyclic and constant speed conditions. A qualitative evaluation of the vehicle's performance was made by comparing its constant speed range performance with other vehicles.

Price, T. W.↗
DOE OSTI2026

Optimized Gear Selection to Maximize Energy Savings in Electric Traction Drives for Medium and Heavy Duty Vehicles

Multi‑gear transmission systems are commonly used in electric traction drives for medium and heavy‑duty vehicles, while most passenger‑vehicle electric drivetrains rely on a single fixed ratio to reduce cost, weight, and complexity. Using multiple gear ratios can enable downsizing of the motor and inverter while still meeting performance requirements. Additionally, appropriately chosen ratios allow the motor to operate more frequently in high‑efficiency regions, improving overall energy usage and reducing operating costs over the drive cycle. This paper presents a systematic approach for selecting optimal gear ratios for electric drive systems. A neural‑network model is first developed to represent motor losses across the full torque–speed range using data generated from finite element analysis. This model enables fast, accurate evaluation of motor efficiency under varying operating conditions. A genetic‑algorithm‑based optimization framework is then applied to identify gear ratios that maximize energy cost savings over the drive cycle, with the resulting optimal ratios stored for real‑time implementation.

Gadiyar, Nishanth [ORNL] (ORCID:0000000348267524)↗
NASA NTRS1999

TAL Performance and Mission Analysis in a CDL Capacitor Powered Direct-Drive Configuration

The goals of this research are (1) to prove the concept feasibility of a direct-drive electric propulsion system, and (2) to evaluate the performance and characteristics of a Russian TAL (Thruster with Anode Layer) operating in a long-pulse mode, powered by a capacitor-based power source developed at Space Power Institute. The TAL, designated D-55, is characterized by an external acceleration zone and is powered by a unique chemical double layer (CDL) capacitor bank with a capacitance of 4 F at a charge voltage of 400 V. Performance testing of this power supply on the TAL was conducted at NASA Lewis Research Center in Cleveland, OH. Direct thrust measurements of the TAL were obtained at CDL power levels ranging from 450 to 1750 W. The specific impulse encompassed a range from 1150 s to 2200 s, yielding thruster system efficiencies between 50 and 60%. Preliminary mission analysis of the CDL direct-drive concept and other electric propulsion options was performed for the ORACLE spacecraft in 6am/6pm and 12am/12pm, 300 km sun-synchronous orbits. The direct-drive option was competitive with the other systems by increasing available net mass between 5 and 42% and reducing two-year system wet mass between 18 and 63%. Overall, the electric propulsion power requirements for the satellite solar array were reduced between 57 and 91% depending oil the orbit evaluated The direct-drive, CDL capacitor-based concept in electric propulsion thus promises to be a highly-efficient, viable alternative for satellite operations in specific near-Earth missions.

Hrbud, Ivana↗
DOE OSTI2020

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.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRS2010

Inductive Non-Contact Position Sensor

Optical hardware has been developed to measure the depth of defects in the Space Shuttle Orbiter's windows. In this hardware, a mirror is translated such that its position corresponds to the defect's depth, so the depth measurement problem is transferred to a mirror-position measurement problem. This is preferable because the mirror is internal to the optical system and thus accessible. Based on requirements supplied by the window inspectors, the depth of the defects needs to be measured over a range of 200 microns with a resolution of about 100 nm and an accuracy of about 400 nm. These same requirements then apply to measuring the position of the mirror, and in addition, since this is a scanning system, a response time of about 10 ms is needed. A market search was conducted and no sensor that met these requirements that also fit into the available housing volume (less than one cubic inch) was found, so a novel sensor configuration was constructed to meet the requirements. This new sensor generates a nearly linearly varying magnetic field over a small region of space, which can easily be sampled, resulting in a voltage proportional to position. Experiments were done with a range of inductor values, drive voltages, drive frequencies, and inductor shapes. A rough mathematical model was developed for the device that, in most aspects, describes how it operates and what electrical parameters should be chosen for best performance. The final configuration met all the requirements, yielding a small rugged sensor that was easy to use and had nanometer resolution over more than the 200-micron range required. The inductive position sensor is a compact device (potentially as small as 2 cubic centimeters), which offers nanometer-position resolution over a demonstrated range of nearly 1 mm. One of its advantages is the simplicity of its electrical design. Also, the sensor resolution is nearly uniform across its operational range, which is in contrast to eddy current and capacitive sensors whose sensitivity is dependent upon position.

Youngquist, Robert↗
DOE OSTI2020

Highly Integrated WBG Power Module for Next Generation Plug-In Vehicles

Current inverter technologies used in electric vehicles (EVs) are bulky, heavy, and expensive. The performance of the inverter is also limited by the traditional Si-based semiconductor and packaging technology. These constraints are responsible for extra weight and volume in the vehicle that reduces the driving range along with usable space within the vehicle. Moreover, operating temperature restrictions, and boundaries on the inverter location within the vehicle drastically reduces the inverter performance. Thus an improved inverter design is required for next generation electric vehicles. The objective of this project was to research, develop and demonstrate a highly integrated WBG power module targeting the next generation of plugin hybrid electric vehicles (PHEVs). This power module needed to be functionally and mechanically optimized for General Motors (GM) traction inverter architecture. General Motors was the prime contractor, led the project, and oversaw the design, build, and test of the integrated power module. Virginia Polytechnic Institute and State University (VT) performed modeling and simulation tasks as well as power module design support. Monolith Semiconductor, Inc provided SiC dies and consulted on devices for the inverter. Oak Ridge National Laboratory (ORNL) performed power module technology evaluations, design evaluations of interconnect options, and performed material analysis and cross-sectioning of die activities.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2026

How the Availability and Cost of Water Could Influence the Future Buildout of the Electric Grid in the U.S.

The power sector is the largest water withdrawer in the U.S., and water availability can drive both its investment and operating decisions. Given a range of uncertain trends in the power sector, it's important to consider how water demands might evolve from both generation and load change and how the cost and availability of water might impact water source decisions. Doing so requires a detailed consideration of technology-specific water needs, water availability characterization, and scenario exploration. This presentation describes capabilities to do so in unprecedented detail and some preliminary findings about how water constraints could influence power sector expansion.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Optimized System for On-Route Fast Charging of Battery-Electric Shuttle Buses

Electrifying cars, buses, and trucks is an attractive means of reducing energy use and emissions because it involves more efficient drivetrain components and minimal restructuring of the transportation network. Transit buses, driving fixed routes, help minimize driver range anxiety by properly sizing energy storage systems. A major challenge to fully electrifying transit buses is providing the amount of energy they consume in a day of driving. To enable a full day of operation without charging, batteries need to be large, which could be expensive and heavy. This work utilizes real-world transit bus data used in a battery-electric drivetrain model to co-optimize charger locations, charger power levels, and vehicle battery sizes.

ADVANCED PROPULSION SYSTEMS↗
NASA NTRS1987

Near fields in the vicinity of pulsed electron beams in space

Most measurements of the radio frequency emissions from artificial electron beams in space have been made in close proximity to the beam. This paper presents theory and results for the near-field radiation associated with the operation of a pulsed electron beam, taking into account the effects of the ionospheric plasma. The beam is modeled as an infinite train of square-wave pulses and the radiation is obtained by adding coherently the radiation from each individual electron in the idealized helical trajectory assumed by the beam as it traverses the magnetized plasma. The mathematical solution is obtained by taking the Fourier transform in space and time of Maxwell's equations and the driving modulated beam current, and then taking the inverse transform of the resulting electric field. Typical electric field strengths are presented for a range of modulation frequencies extending from below the ion cyclotron to the electron cyclotron frequency.

Harker, K. J.↗
DOE OSTI2020

The prospective impacts of 2019 state energy policies on the U.S. electricity system

Over the past several years state energy policies have been evolving rapidly, and are more frequently including higher targets, including 100% clean energy targets. This study assesses the aggregate impacts of state clean energy standards and emissions policies on national electricity generation, power sector carbon dioxide (CO 2 ) emissions, and electricity prices and system costs. To do so, we apply the Regional Energy Deployment System (ReEDS) model, which is a detailed electric sector capacity expansion model, to evaluate scenarios with and without state policies and using a range of renewable energy technology cost projections. Across the scenarios analyzed, we find that the state policies drive 1.9%–10.7% of total nationwide clean energy and reduce cumulative power sector CO 2 emissions by 2.6%–5.4% over the 2020–2050 study period. This incremental generation is predominantly, but not exclusively, from renewable energy technologies. In most cases, the state policies result in increases to electricity prices and electricity system costs, and policy costs are sensitive to the future cost of clean energy technologies. Across all scenarios, the levelized cost of incremental policy-driven clean energy generation is estimated to be $17–38/MWh and the average cost of CO 2 abatement from the state-level policies is estimated to be $29–74/metric ton.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Experimental driving performance evaluation of battery-powered medium and heavy duty all-electric vehicles

As the push to reduce air pollutants and carbon dioxide for global warming continues, there is increasing interest in the development and deployment of battery electric vehicles for heavy-duty applications as one of the critical and challenging steps of a broader effort to fully electrify the transportation sector. This study evaluated and quantified the energy consumption rates and energy regeneration rates for three heavy-duty battery electric vehicles (a step van, a yard tractor, and a class 8 truck) using driving cycle tests with a heavy-duty vehicle chassis dynamometer. Information in this area is currently very limited, and yet it is critical to understanding how effective heavy-duty battery electric vehicles will be for a wide range of applications as the electrification of the heavy-duty vehicle market continues to expand. Energy consumption rates ranged from 0.37 and 2.71 kWh/km for most vehicle/cycle combinations. On a diesel liter energy-equivalent basis, the heavy-duty vehicles had approximately 3 to 6 times better energy consumption rates compared to comparable diesel vehicles, with weight normalized energy consumption rates also comparing favorably to the current and future greenhouse gas/fuel economy standards for equivalent diesel vehicles. Based on battery capacities ranging from 80 to 215 kWh, the vehicle ranges varied from 38.18 km to 171.2 km, with ranges of 115.9 km to 171.2 km for most types of driving and lower ranges of 38.18 to 42.20 km for sustained grade cycles. Overall, the advantage of improved energy consumption rates coupled with improvements that can be expected for battery technology and vehicle range, provide promise for expanded use of heavy-duty vehicles going into the future.

33 ADVANCED PROPULSION SYSTEMS↗
NASA NTRSDate not supplied

Recent Progress in Extreme Environment Durable SiC JFET-R Integrated Circuit Technology

This work updates recent progress made by NASA Glenn Research Center on further advancement of its uniquely durable silicon carbide junction field effect transistor and resistor (SiC JFET-R) integrated circuit (IC) technology since HiTEC 2021. Key fabrication process improvements compared to earlier NASA Glenn IC prototype runs have been ascertained via extensive “back end of line” (BEOL) processing experiments conducted on practice wafers over the past two years. The resulting changes to the BEOL process flow employed in the fabrication of “Generation 12” SiC JFET-R wafers are described. The NASA Glenn SiC JFET-R IC prototype “Generation 12” chipset design realizes significantly higher complexity digital and analog integrated ICs aimed at flexibly implementing a broad variety of mission-enabling extreme-environment electronics demonstrations. SPICE simulations have verified circuit designs ranging from simple amplification of analog sensor signals up through long-duration Venus lander operations and microprocessor-based of electric motor drive.

Silicon Carbide↗
NASA NTRSDate not supplied

Recent Progress in Extreme Environment Durable SiC JFET-R Integrated Circuit Technology

This work updates recent progress made by NASA Glenn Research Center on further advancement of its uniquely durable silicon carbide junction field effect transistor and resistor (SiC JFET-R) integrated circuit (IC) technology since HiTEC 2021. Key fabrication process improvements compared to earlier NASA Glenn IC prototype runs have been ascertained via extensive “back end of line” (BEOL) processing experiments conducted on practice wafers over the past two years. The resulting changes to the BEOL process flow employed in the fabrication of “Generation 12” SiC JFET-R wafers are described. The NASA Glenn SiC JFET-R IC prototype “Generation 12” chipset design realizes significantly higher complexity digital and analog integrated ICs aimed at flexibly implementing a broad variety of mission-enabling extreme-environment electronics demonstrations. SPICE simulations have verified circuit designs ranging from simple amplification of analog sensor signals up through long-duration Venus lander operations and microprocessor-based of electric motor drive.

Silicon Carbide↗
NASA NTRS2023

Recent Progress in Extreme Environment Durable SiC JFET-R Integrated Circuit Technology

This work updates recent progress made by NASA Glenn Research Center on further advancement of its uniquely durable silicon carbide junction field effect transistor and resistor (SiC JFET-R) integrated circuit (IC) technology since HiTEC 2021. Key fabrication process improvements compared to earlier NASA Glenn IC prototype runs have been ascertained via extensive “back end of line” (BEOL) processing experiments conducted on practice wafers over the past two years. The resulting changes to the BEOL process flow employed in the fabrication of “Generation 12” SiC JFET-R wafers are described. The NASA Glenn SiC JFET-R IC prototype “Generation 12” chipset design realizes significantly higher complexity digital and analog integrated ICs aimed at flexibly implementing a broad variety of mission-enabling extreme-environment electronics demonstrations. SPICE simulations have verified circuit designs ranging from simple amplification of analog sensor signals up through long-duration Venus lander operations and microprocessor-based of electric motor drive.

Silicon Carbide↗
DOE OSTI2022

Projecting Recent Advancements in Battery Technology to Next–Generation Electric Vehicles

Electric vehicles (EVs) have seen rapid growth in adoption over the last several years. Advancements to increase battery life and performance, policy shifts, and high charging rate are expected to further accelerate the development of next generation of EVs. Battery improvements continue to emerge, enabling increased driving range, total distance driven over the life of vehicles, and ability to charge at high rates. Herein, an analysis framework to provide insights into inclusive design metrics, such as specific energy of batteries, energy consumption of vehicles, and charging power infrastructure development, is developed. Various cell-level fast charge protocols to realistic battery designs to understand the infrastructure needs associated with achieving range replacement of 32.25 km min -1 (20 mi min -1 ) are also scaled. Additionally, by calculating scaled power and peak to average power ratio, it is found that there needs to be more distinct alignment between the research efforts focused at the cell level and what is being developed for EV charging infrastructure needs. Finally, impact of high direct current voltage architecture in next-generation EVs is discussed. The findings in this work provide an insight into recent advancements in battery technology to next-generation EVs.

20 mi/min↗
DOE OSTI2020

Feasibility of Operating a Heavy-Duty Battery Electric Truck Fleet for Drayage Applications

Vehicle fleet electrification is regarded as one major pathway toward achieving energy independence and reducing air pollution and greenhouse gas emissions. Compared to light-duty and medium-duty vehicles, electrification of heavy-duty vehicles, especially Class 8 trucks, is more challenging owing to the battery size required to attain the driving range necessary for their operating goals. As drayage trucks generally have a limited daily mileage, return to a home base every night, and spend a large amount of time creeping and idling, drayage operation has been the first targeted application for Class 8 electric trucks. The feasibility of operating battery electric drayage trucks at the individual vehicle level has recently been demonstrated. However, questions remain as to whether these trucks are capable of meeting the needs of typical drayage operation at the fleet level. Here we present a feasibility analysis of operating an electric truck fleet based on real-world operation data of a diesel drayage operator in Southern California. Second-by-second activity data collected from 20 trucks in the fleet were used to estimate the corresponding electric energy consumption and the state of charge of the battery using a microscopic electric energy consumption model. An algorithm for generating tours of drayage activity from the collected data was developed and implemented. Multiple scenarios with different battery charging and truck scheduling assumptions were analyzed. The results show that 85% of the tours could be served by electric trucks if there is opportunity for charging at the home base during the time gap between consecutive tours.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2023

Energy Optimization of Light and Heavy-Duty Vehicle Cohorts of Mixed Connectivity, Automation and Propulsion System Capabilities via Meshed V2V-V2I and Expanded Data Sharing (Final Scientific and Technical Report)

Vehicle connectivity and automated driving technologies individually have the potential to decrease energy consumption and/or increase safety on light, medium or heavy duty vehicles to varying degrees depending on the traffic infrastructure and specific driving scenarios. Due to advances in sensing, perception and computing power, research and development emphasis in the mobility sector has shifted away from connectivity. Prior research has shown that driving automation with the absence of connectivity can in certain circumstances increase energy consumption. The effectiveness of synergizing connectivity and driving automation technologies is the focus of this work, specifically applied to vehicle cohorts of mixed composition, light and heavy duty, and powertrains ranging from all electric to conventional internal combustion engine. The project team is led by Michigan Technological University (MTU) and partnered with AVL Mobility Technologies Inc. (AVL), Borg Warner (BW), Traffic Technology Services (TTS), American Center for Mobility (ACM) and Navistar (NAV). The main thrusts for the team are to develop a micro-traffic simulation environment with specific VD&PT system attributes and CAV capabilities, 2) field a vehicle test fleet of mixed classification, propulsion and CAV capacity, 3) develop artificial intelligence (AI) and machine learning (ML) based multi-agent optimization methods for various traffic infrastructures, 4) integrate the virtual environment and the optimization methods then deploy the system as a CAV hardware in the loop (HiL) for the vehicle test fleet and 5) conduct closed track and public road testing to validate simulation and demonstrated energy and mobility improvements at multiple scales. For a cohort of mixed vehicles, the team will demonstrate a reduction of energy consumption of 10-50% at intersection, arterial roadway and limited access highway scenarios through connectivity and automation in simulation and at a closed test track. The energy reduction objectives of the project are summarized in Table 1, indicating the infrastructure and over what distances are relevant considered. Single scenario energy reductions are not relevant and thus, the research team took the approach to vary parameters associated with the infrastructure, vehicle cohort composition and dynamic behavior to generate energy consumption distributions for both unconnected and connected scenarios.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗