Leveraging electric vehicles as a resiliency solution for residential backup power during outages
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Liu, Shanshan (ORCID:0000000241737485)↗
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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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Study of advanced electric propulsion system concept using a flywheel for electric vehicles
Advanced electric propulsion system concepts with flywheels for electric vehicles are evaluated and it is predicted that advanced systems can provide considerable performance improvement over existing electric propulsion systems with little or no cost penalty. Using components specifically designed for an integrated electric propulsion system avoids the compromises that frequently lead to a loss of efficiency and to inefficient utilization of space and weight. A propulsion system using a flywheel power energy storage device can provide excellent acceleration under adverse conditions of battery degradation due either to very low temperatures or high degrees of discharge. Both electrical and mechanical means of transfer of energy to and from the flywheel appear attractive; however, development work is required to establish the safe limits of speed and energy storage for advanced flywheel designs and to achieve the optimum efficiency of energy transfer. Brushless traction motor designs using either electronic commutation schemes or dc-to-ac inverters appear to provide a practical approach to a mass producible motor, with excellent efficiency and light weight. No comparisons were made with advanced system concepts which do not incorporate a flywheel.
Younger, F. C.↗
An Integrated Traction Drive with a High Speed Surface Permanent Magnet External Rotor Motor for Electric Vehicles
This work presents the detailed design of an outer rotor motor and integrated drive for passenger electric vehicles. The motor uses non-heavy rare earth permanent magnets and operates at a top speed of 20,000rpm. In-slot ceramic heat exchangers are utilized for the cooling of the windings. The external rotor configuration of the motor leaves a significant amount of space in the stator bore, which is leveraged for the integration of the power electronics. A high speed external rotor motor creates a number of mechanical, thermal and assembly challenges and this work presents detailed thermal, mechanical and rotordynamics analysis.
ADVANCED PROPULSION SYSTEMS↗
Alternating-Current Motor Drive for Electric Vehicles
New electric drive controls speed of a polyphase as motor by varying frequency of inverter output. Closed-loop current-sensing circuit automatically adjusts frequency of voltage-controlled oscillator that controls inverter frequency, to limit starting and accelerating surges. Efficient inverter and ac motor would give electric vehicles extra miles per battery charge.
Krauthamer, S.↗
How Improved Forecasting Can Increase the Bulk Power System Value of Price-Responsive Electric Vehicle Managed Charging
Personal light-duty vehicle (LDV) electric vehicle managed charging (EVMC) can reduce power system costs by better aligning electric vehicle (EV) charging with locations and times of low energy cost or infrastructure use. The need to coordinate charging demand across thousands to millions of vehicles while preserving mobility service is a barrier to realizing the value of EVMC. Price-responsive dispatch mechanisms like time-of-use rates (TOU) and hourly real-time prices (RTP) are attractive compared to direct load control (DLC) because they only require one-way communications and local controls. However, increasing participation in price responsive mechanisms can induce costly-to-serve spikes in load and otherwise increase, rather than decrease, production costs. We quantify the ability of improved EVMC forecasting to sustain savings from price responsive mechanisms beyond the limit of 14% of LDVs actively participating observed in previous work. Perfect forecasting of price-responsive EV load makes TOU and RTP value-competitive with a low-error DLC formulation with up to 27% (within-week flexibility) to 45% or more (within-session flexibility) of LDVs participating in EVMC in an envisioned New England power system with 84% clean energy. Additional costs of implementing DLC should be no more than tens of dollars per vehicle-year if DLC is to be value-competitive with accurately forecast price-responsive EVMC for double-digit percentage shares of LDVs participating.
29 ENERGY PLANNING, POLICY, AND ECONOMY↗
State-of-the-art assessment of electric vehicles and hybrid vehicles
The Electric and Hybrid Vehicle Research, Development, and Demonstration Act of 1976 (PL 94-413) requires that data be developed to characterize the state of the art of vehicles powered by an electric motor and those propelled by a combination of an electric motor and an internal combustion engine or other power sources. Data obtained from controlled tests of a representative number of sample vehicles, from information supplied by manufacturers or contained in the literature, and from surveys of fleet operators of individual owners of electric vehicles is discussed. The results of track and dynamometer tests conducted by NASA on 22 electric, 2 hybrid, and 5 conventional vehicles, as well as on 5 spark-ignition-engine-powered vehicles, the conventional counterparts of 5 of the vehicles, are presented.
Source record↗
Learning electric vehicle driver range anxiety with an initial state of charge-oriented gradient boosting approach
This manuscript focuses on the modeling of electric vehicle (EV) driver’s range anxiety, a fear that a vehicle does not have sufficient range, or state of charge (SOC) of the battery pack, to reach its destination and would strand its occupants. Despite numerous research studies on the modeling of charging behaviors, modeling efforts to understand at what battery percentages do EV drivers charge their vehicles, and what are the associated contributing factors, are rather limited. To this end, an ensemble learning model based on gradient boosting is developed. The model sequentially fits new predictors to new residuals of the previous prediction and, then, minimizes the loss when adding the latest prediction. A total of 18 features are defined and extracted from the multisource data, which cover information on driver, vehicles, stations, traffic conditions, as well as spatial-temporal context information of the charging events. The analyzed dataset includes 4.5-year’s charging event log data from 3,096 users and 468 public charging stations in Kansas City Missouri, and the macroscopic travel demand model maintained by the metropolitan planning organization. Here, the result shows the proposed model achieved a satisfactory result with a R square value of 0.54 and root mean square error of 0.14, both better than multiple linear regression model and random forest model. To reduce range anxiety, it is suggested that the priorities of deploying new charging facilities should be given to the areas with higher daily traffic prediction, with more conservative EV users or that are further from residential areas.
33 ADVANCED PROPULSION SYSTEMS↗
Electric Vehicle Basics (French Translation)
Electric vehicles (EVs) use electricity as their primary fuel or to improve the efficiency of conventional vehicle designs. EVs include all-electric vehicles, also referred to as battery electric vehicles (BEVs), and plug-in hybrid electric vehicles (PHEVs). In colloquial references, these vehicles are called electric cars, or simply EVs, even though some of these vehicles still use liquid fuels in conjunction with electricity. EVs are known for providing instant torque and a quiet driver experience. Other types of electric-drive vehicles not covered here include hybrid electric vehicles, which are powered by a conventional engine and an electric motor that uses energy stored in a battery that is charged by regenerative braking, not by plugging in, and fuel cell electric vehicles, which use a propulsion system similar to electric vehicles, where energy stored as hydrogen is converted to electricity by the fuel cell. This is the French translation of NREL/FS-5400-87125.
ADVANCED PROPULSION SYSTEMS,DIRECT ENERGY CONVERSI↗
Integrated Optimization of Powertrain Energy Management and Vehicle Motion Control for Autonomous Hybrid Electric Vehicles
Hybrid Electric Vehicles (HEVs) and autonomous vehicles have been widely studied recently for on-road transportation. In the study of autonomous HEVs, the control of the vehicle's external dynamics and powertrain dynamics are often treated separately. Optimizing these two problems together can significantly improve fuel economy. In this paper, an autonomous HEV following a leader is considered. First, the augmented model to integrate the abovementioned dynamics is presented. Second, the optimization problem is defined to find the optimum fuel consumption of the follower in pursuit of a leader in a drive cycle. A customized control strategy based on Approximate Dynamic Programming (ADP) is then explored in which the optimal cost-to-go at each time step is approximated using neural networks. Also, the accuracy of the optimization solution is enhanced by applying the concept of the reachable sets. At last, three case studies show that the examined integrated control strategy outperforms the one with the separated optimization method by an additional 7.4%, 4.6%, and 11.8% improvement in fuel consumption, respectively.
33 ADVANCED PROPULSION SYSTEMS↗
Highly Resolved Projections of Passenger Electric Vehicle Charging Loads for the Contiguous United States: Results From and Methods Behind Bottom-Up Simulations of County-Specific Household Electric Vehicle Charging Load (Hourly 8760) Profiles Projected Through 2050 for Differentiated Household and Vehicle Types
This report documents enhancements made to the TEMPO (Transportation Energy & Mobility Pathway Options TM ) model to project spatially, demographically, and temporally resolved national-scale EV charging load profiles and describes three scenarios and corresponding datasets created for the NREL demand-side grid (dsgrid) project in support of bulk power systems modeling. In brief, TEMPO was enhanced to disaggregate national and annual energy demand projections into household and county-level projections of passenger electric vehicle (EV) hourly charging load profiles (8760 profiles), accounting for consumer, travel, and temperature variations that impact EV energy demand. In alignment with NREL's forward-looking grid modeling, three scenarios for EV adoption covering 2020-2050 were created-- Annual Energy Outlook (AEO) Reference Case, Electrification Futures Study (EFS) High Electrification, and All EV Sales by 2035 --and associated datasets have been included in the dsgrid platform for public use.
29 ENERGY PLANNING, POLICY, AND ECONOMY↗
Study of Electric Vehicle Range Loss Associated with Replacement Tires
The FuelEconomy.Gov website has become a trusted source for consumers to find information pertaining to fuel economy and fuel-efficient vehicles. As electric vehicles are an increasingly important part of the light-duty fleet in the U.S., there is a need to expand the website content that is targeted to electric vehicle (EV) owners. This report addresses a concern about which several anecdotal reports have come to the attention of the website support staff. Specifically, some EV owners have observed a sudden, noticeable decrease in their all-electric range when they replace the tires that came with their vehicle when it was new. This change has reportedly led some owners to take their vehicles to the dealership service department out of concern that something had gone wrong with the vehicle.
33 ADVANCED PROPULSION SYSTEMS↗
Development and Demonstration of a Class 6 Range-Extended Electric Vehicle for Commercial Pickup and Delivery Operation: Preprint
Range-extended hybrids are an attractive option for medium- and heavy-duty commercial vehicle fleets because they offer the efficiency of an electrified powertrain with the driving range of a conventional diesel powertrain. The vehicle essentially operates as if it was purely electric for most trips, while ensuring that all commercial routes can be completed in any weather conditions or geographic terrain. Fuel use and point-source emissions can be significantly reduced, and in some cases eliminated, as many shorter routes can be fully electrified with this architecture. Under a U.S. Department of Energy (DOE)-funded project for Medium- and Heavy-Duty Vehicle Powertrain Electrification, Cummins has developed a plug-in hybrid electric Class 6 truck with a range-extending engine designed for pickup and delivery application. The National Renewable Energy Laboratory (NREL) assisted by developing representative workday drive cycles for Class 6 operation and an adapted cycle to enable vehicle track testing. A novel, automated driving system was utilized by Southwest Research Institute (SwRI) to improve the repeatability of the track testing conducted to quantify vehicle energy consumption. Cummins used a drivetrain model to design the hybrid control system for increased fuel savings. The control system functionality and fuel savings objective of 50% or more were confirmed by track testing described in this paper.
ADVANCED PROPULSION SYSTEMS↗
Well-to-wheels greenhouse gas and air pollutant emissions from battery electric vehicles in China
Electric vehicles (EVs) play a crucial role in addressing climate change and urban air quality concerns. China has emerged as the global largest EV market with 1.2 million EVs sold in 2018. This study established a novel life cycle energy use and emission inventory collecting up-to-date data including the electricity generation mix, emission controls in the power and industrial sectors, and the energy use in the fuel transport to estimate the well-to-wheels (WTW) greenhouse gas (GHG), and air pollutant emissions for battery electric vehicles (BEVs) and gasoline passenger vehicles in China. The results show that an average BEV has 35% lower WTW GHG emissions than an average gasoline car. BEVs reduce volatile organic compounds (VOCs) and nitrogen oxides (NOX) emissions by 98% and 34%, respectively, but have comparable or slightly higher primary fine particulate matter (PM2.5) and sulfur dioxide (SO2) emissions. Compact and small-size vehicles generally have lower GHG and air pollutant emissions than mid- and large-size vehicles. Class A vehicles contribute the most in the absolute amount of GHG and air pollutant emissions and therefore have the biggest potential for emission reduction. Our results suggest that global policymakers should continue to promote the transition to clean power sources, emission control, and fuel economy regulations, which are critical to enhancing emission mitigation benefits of BEVs. We also suggest EV development strategies should be formulated targeting vehicle class with the biggest emission mitigation potentials.
Air pollutant emissions↗
Hybrid Turbine Electric Vehicle
Hybrid electric power trains may revolutionize today's ground passenger vehicles by significantly improving fuel economy and decreasing emissions. The NASA Lewis Research Center is working with industry, universities, and Government to develop and demonstrate a hybrid electric vehicle. Our partners include Bowling Green State University, the Cleveland Regional Transit Authority, Lincoln Electric Motor Division, the State of Ohio's Department of Development, and Teledyne Ryan Aeronautical. The vehicle will be a heavy class urban transit bus offering double the fuel economy of today's buses and emissions that are reduced to 1/10th of the Environmental Protection Agency's standards. At the heart of the vehicle's drive train is a natural-gas-fueled engine. Initially, a small automotive engine will be tested as a baseline. This will be followed by the introduction of an advanced gas turbine developed from an aircraft jet engine. The engine turns a high-speed generator, producing electricity. Power from both the generator and an onboard energy storage system is then provided to a variable-speed electric motor attached to the rear drive axle. An intelligent power-control system determines the most efficient operation of the engine and energy storage system.
Viterna, Larry A.↗
Distributed Control of Charging for Electric Vehicle Fleets Under Dynamic Transformer Ratings
Not provided.
Automation & Control Systems↗
EVI-X Electric Vehicle Infrastructure Toolbox
The Electric Vehicle Infrastructure Toolbox offers resources for estimating charging infrastructure needs and associated electrical demands based on user-defined electric vehicle adoption scenarios. For more information and additional resources, see the full EVI-X modeling suite of electric vehicle charging infrastructure analysis tools.
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
Electric Vehicles for Fleets
Electric vehicles can fulfill many daily driving needs, making them a great solution for fleets. They offer several benefits and can fill roles in light-duty, medium-/heavy-duty (MD/HD), and even off-road applications. The unique fleet environment presents considerations beyond those that consumers must address before going electric. For example, fleet managers must understand the impacts of charging multiple vehicles while maintaining fleet operations. Larger MD/HD vehicles bring additional factors to consider.
charging↗