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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 55 records · Page 3

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↗

On-Line Prediction of Resistant Force During Soil–Tool Interaction

For off-road vehicles such as excavators and wheel loaders, a large portion of energy is consumed to overcome the soil resistant force in the digging process. For optimal control of the digging tool, a high-fidelity model of the soil–tool interaction force is important to reduce energy consumption. Here, in this paper, an on-line soil resistant force prediction method is proposed. In this method, a hybrid model, which combines a physical model and a data-driven model, is used for the force prediction. In addition, the parameters of the hybrid model can be updated on-line based on real-time data. Comparisons with experimental data demonstrate that the proposed prediction method has an average error of around 12.7%.

42 ENGINEERING↗

Public charging infrastructure for plug-in electric vehicles: What is it worth?

A lack of charging infrastructure is an important barrier to the growth of the plug-in electric vehicle (PEV) market. Public charging infrastructure has tangible and intangible value, such as reducing range anxiety or building confidence in the future of the PEV market. Quantifying the value of public charging infrastructure can inform analysis of investment decisions and can help predict the impact of charging infrastructure on future PEV sales. Estimates of willingness to pay (WTP) based on stated preference surveys are limited by consumers' lack of familiarity with PEVs. As an alternative, we focus on quantifying the tangible value of public PEV chargers in terms of their ability to displace gasoline use for PHEVs and to enable additional electric (e-) vehicle miles for BEVs, thereby mitigating the limitations of shorter range and longer recharging time. Simulation studies provide data that can be used to quantify e-miles enabled by public chargers and the value of additional e-miles can be inferred from econometric estimates of WTP for increased vehicle range. Functions are synthesized that estimate the WTP for public charging infrastructure by plug-in hybrid and battery electric vehicles, conditional on vehicle range, annual vehicle travel, pre-existing charging infrastructure, energy prices, vehicle efficiency, and household income. A case study based on California's public charging network in 2017 indicates that, to the purchaser of a new BEV with a 100-mile range and home recharging, existing public fast chargers are worth about $1500 for intraregional travel, and fast chargers along intercity routes are valued at over $6500.

33 ADVANCED PROPULSION SYSTEMS↗

Clean Cities Coalitions: 2022 Activity Report

The U.S. Department of Energy's (DOE's) Vehicle Technologies Office (VTO) works with local Clean Cities coalitions across the country as part of its Technology Integration Program. These efforts help businesses and consumers make smarter and more informed transportation energy choices that can save energy, lower costs, provide resilience through fuel diversification, and reduce emissions. This report summarizes the success and impact of coalition activities based on data and information provided in their annual reports.

33 ADVANCED PROPULSION SYSTEMS↗

Clean Cities Coalitions 2021 Activity Report

The U.S. Department of Energy's (DOE) Office of Energy Efficiency and Renewable Energy's Vehicle Technologies Office (VTO) works with local Clean Cities coalitions across the country as part of its Technology Integration Program. These efforts help businesses and consumers make smarter and more-informed transportation energy choices that can save energy, lower costs, provide resilience through fuel diversification, and reduce air emissions. This report summarizes the success and impact of coalition activities based on data and information provided in their annual progress reports.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Multifold Insights for Power System Dynamics From Data Assimilation: Meeting Current Challenges

The world’s electric power grids have evolved over the last 120 years from a single power line to today’s large networks. The evolution will continue at an accelerated rate with extensive smart grid development worldwide. Here for example, the U.S. government has set a goal of reaching 100 percent carbon pollution-free electricity by 2035, while the Department of Energy (DOE) shared a goal to deploy 30 GW and 110 GW of offshore wind by 2030 and 2050, respectively. To meet such ambitious goals, in the years to come, a significant percentage of electricity will come from intermittent renewable sources, electric vehicles (EVs), and be supplied to a vast number of loads that will actively respond to grid conditions and incentive signals. This development is largely driven by environmental and economic factors, such as reducing carbon emissions and saving electricity cost for consumers. These energy resources lead to new uncertain behaviors and dynamics which the grid has never seen and were not considered in its design. Operating such a dynamic grid with sufficient reliability and efficiency is a monumental challenge.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Consumer-Oriented Energy Use and Range Metrics for Battery Electric Vehicles

The present study was motivated by a need to expand information for consumers offered through the FuelEconomy.Gov website. To that end, a power-based modeling approach has been used to examine the effect of steady-speed driving on estimated range for model year 2020 – 2023 battery electric vehicles (BEVs). This approach allowed rapid study of a broader range of BEV models than could be accomplished through vehicle tests. Publicly accessible certification test results and other data were used to perform a regression between cycle-average tractive power requirements and the resulting electrical power. Importantly, this regression enabled estimation of electric power and energy use over a range of steady highway speeds. These analyses in turn allowed projection of vehicle range at differing speeds. The projections agree within 6% with available 65 MPH manufacturer test data. Analyses of vehicles from model years 2020 – 2023 show that the 5-cycle range and energy use values from the window stickers of new vehicles are reasonable values for steady-speed driving at 65 MPH. Range decreases by a median value of approximately 15% for each 10 MPH increase in speed. The 5-cycle energy use (in kW-Hr / 100 miles) and energy economy (in miles / kW-Hr) derived from the 5-cycle energy use are reasonable estimates for 65 MPH steady speed driving. Energy economy decreases by about 0.5 miles / kW-Hr for every 10 MPH increase in speed.

33 ADVANCED PROPULSION SYSTEMS↗

Development of a Heavy-Duty Electric Vehicle Integration and Implementation (HEVII) Tool

As demand for consumer electric vehicles (EVs) has drastically increased in recent years, manufacturers have been working to bring heavy-duty EVs to market to compete with Class 6-8 diesel-powered trucks. Many high-profile companies have committed to begin electrifying their fleet operations, but have yet to implement EVs at scale due to their limited range, long charging times, sparse charging infrastructure, and lack of data from in-use operation. Thus far, EVs have been disproportionately implemented by larger fleets with more resources. To aid fleet operators, it is imperative to develop tools to evaluate the electrification potential of heavy-duty fleets. However, commercially available tools, designed mostly for light-duty vehicles, are inadequate for making electrification recommendations tailored to a fleet of heavy-duty vehicles. The main challenge is that light-duty tools do not estimate real-time vehicle mass, a factor that has a disproportionate impact on the energy consumption of large commercial vehicles. The Heavy-Duty Electric Vehicle Integration and Implementation (HEVII) tool advances the state of the art in evaluating electrification potential and infrastructure requirements for fleets of commercial vehicles. In this work, the HEVII tool is demonstrated with non-uniformly sampled telematics data from an existing fleet to assess the suitability for electrification of each individual vehicle, determine optimal locations for charging infrastructure to support a fleet of EVs and analyze associated costs. Payload mass is predicted using sparse ground-truth data for all input drive cycles and an initial data analysis is conducted to assess the characteristics driving behaviors and energy consumption of the fleet using an adaptable vehicle model. Battery size requirements are determined by applying a novel charger placement algorithm to maximize routes that are viable for EVs and balance time delays with infrastructure development costs. This work details and demonstrates the different aspects of the HEVII tool, presenting preliminary results from an example use case.

ADVANCED PROPULSION SYSTEMS↗

Parametric Vehicle Choice Modeling: ParaChoice

Assess the evolving integration potential of light-duty (LDV) and heavy-duty vehicle (HDV) technologies, fuels, and infrastructure and their contributions to lowering emissions and petroleum consumption. Leverage existing LDV and build HDV ParaChoice capability to conduct parametric analyses that explore the trade-space for key factors that influence consumer choice and technology, fuel and infrastructure development. ParaChoice provides the unique capability to examine tipping points and tradeoffs, and can help quantify the effects of and mitigate uncertainty introduced by data sources and assumptions.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Estimating the electric vehicle charging demand of multi-unit dwelling residents in the United States

Abstract Early battery electric vehicle (EV) adopters can access home chargers for reliable charging. As the EV market grows, residents of multi-unit dwellings (MUDs) may face barriers in owning EVs and charging them without garage or parking availability. To investigate the mechanisms that can bridge existing disparities in home charging and station deployment, we characterized the travel behavior of MUD residents and estimated their EV residential charging demand. This study classifies the travel patterns of MUD residents by fusing trip diary data from the National Household Travel Survey and housing features from the American Housing Survey. A hierarchical agglomerative clustering method was used to cluster apartment complex residents’ travel profiles, considering attributes such as dwell time, daily vehicle miles traveled (VMT), income, and their residences’ US census division. We propose a charging decision model to determine the charging station placement demand in MUDs and the charging energy volume expected to be consumed, assuming that MUD drivers universally operate EVs in urban communities. Numerical experiments were conducted to gain insight into the charging demand of MUD residents in the US. We found that charging availability is indispensable for households that set out to meet 80% state of charge by the end of the day. When maintaining a 20% comfortable state of charge the entire day, the higher the VMT are, the greater the share of charging demand and the greater the energy use in MUD chargers. The upper-income group requires a greater share of MUD charging and greater daily kWh charged because of more VMT.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

The electric vehicles-solar photovoltaics Nexus: Driving cross-sectoral adoption of sustainable technologies

Residential and transportation energy consumption account for more than one-half of the overall energy consumption in the United States. Adoption of electric vehicles (EVs) can play a key role in decarbonizing the transportation sector, while the adoption of renewable energy sources (e.g., solar photovoltaics [PVs]) could bring similar benefits to the residential energy sector and in turn support transport electrification. Although the market shares for both EVs and PVs continue to grow, both of these emerging technologies are deployed rather disjointly, without considering the existence of potential similarities among users who own (or aspire to own) these technologies. This might be due to lack of understanding of the behavioral interdependence in consumer preferences toward these technologies. To fill this gap in knowledge, this study utilizes data from the 2018 WholeTraveler Transportation Behavior Study to develop an integrated model system that explores interactive EV and PV adoption behaviors. A structural equation model is employed that incorporates direct effects as well as error correlations among the adoption behaviors for EVs and PVs. Model results indicate that the adoption behavior for both these technologies is indeed interconnected and significantly influenced by attitudes, values, and personality traits. Findings from this research suggest that incentives (e.g., subsidies) that drive bundled adoption of EV-PV systems could accelerate the adoption of both of these sustainable technologies. In conclusion, this study highlights the need to consider transport and building energy-efficient technology adoption behavior in a single integrated structure.

14 SOLAR ENERGY↗

Is the Adoption of Electric Vehicles (EVs) and Solar Photovoltaics (PVs) Interdependent or Independent? An Integrated EVs-PVs Modeling Framework

Transportation and residential energy consumption account for more than one-half of the overall energy consumption in the United States. Adoption of electric vehicles (EVs) can play a key role in decarbonizing the transportation sector, while the adoption of renewable energy sources (e.g., solar photovoltaics or PVs) could bring similar benefits to the residential energy sector and in turn support transport electrification. Although the market share for both EVs and PVs continue to grow, both these emerging technologies are deployed rather disjoint without considering the existence of potential similarities among users who own (or aspire to own) EVs and PVs. This might be due to lack of understanding of the behavioral interdependence in consumer preferences towards these technologies. To fill this gap in knowledge, this study utilizes data from the 2018 WholeTraveler Transportation Behavior Study to develop an integrated model system that explores EV and PV adoption behaviors. A structural equations model (SEM) is employed that incorporates direct effects as well as error correlations among the adoption behaviors for EVs and PVs. Model results indicate that the adoption behavior for both these technologies is indeed interconnected and significantly influenced by attitudes, values and personality traits. Findings from this research suggest that incentives (e.g., subsidies) that drive 'bundled' adoption of EVs and PVs could accelerate the adoption of both these sustainable technologies. The results highlights the need to consider transport and building energy efficient technology adoption behavior in a single integrated structure.

ADVANCED PROPULSION SYSTEMS,ENERGY PLANNING, POLIC↗

Automated vehicle microscopic energy consumption study (AV-Micro): Data collection and model development

While the Adaptive Cruise Control (ACC) system in automated vehicles (AVs) is expected to impact transportation energy significantly, existing AV energy consumption models only directly adopt those developed with Human-driven Vehicle (HV) data without even slight adaptation or calibration to accommodate unique AV energy consumption features. This study will investigate how accurately HV data-based models can predict the energy consumption of AVs. Empirical trajectory data and corresponding instantaneous energy consumption rates from both AVs and HVs were collected. We adopted two classical HV data-based models to fit these data. The calibration results indicated that these models yield around 20 30% prediction errors for AVs. To further improve the prediction accuracy, this study designed an AV-Micro model by incorporating components of multiple classic energy consumption models that better capture ACC energy consumption features, including piecewise driving behavior. With this, the AV-Micro model achieves lower than 10% prediction errors. The AV-Micro model’s high consistency across different test runs was verified with statistical significance tests, demonstrating its adaptability in different driving profiles. To confirm the discrepancies between the energy consumption features of AVs and HVs, more statistical significance tests were conducted to show that the AV-Micro model cannot be directly applied to HV data. The findings by calibrated AV-Micro models revealed that AVs consume approximately 80.5–146.4 J more energy than HVs for each meter traveled. Furthermore, the frequency analysis of energy consumption indicates that there is still some room for AVs to improve energy efficiency, particularly given their larger amplitude high-frequency fluctuations.

33 ADVANCED PROPULSION SYSTEMS↗

Sourcing, Refining and Recycling of Rare-Earth Magnets

Permanent magnets today are used in a wide range of transportation, industrial, residential/commercial, consumer electronics, defense, domestic, data storage, wind energy, and medical markets and applications. There are five classes of commercial permanent magnet materials; however, magnets based on Nd-Fe-B account for over 60% of the global magnet production by value. They typically contain around 31 wt.% of rare earth elements (REEs), principally, Nd and Pr, plus Dy for higher-temperature performance. Nd-Fe-B magnets are forecast to grow throughout this decade, largely driven by the growth in electric vehicles of all types. However, several studies forecast a shortfall of the primary REEs from mined resources. In this paper, the sourcing, processing, and recycling of REEs are discussed. Additionally, presented are the advantages and disadvantages of the major recovery and recycling technologies for REEs.

36 MATERIALS SCIENCE↗

Vehicle Residual Value Analysis by Powertrain Type and Impacts on Total Cost of Ownership

Vehicle depreciation is a key factor in determining the total cost of vehicle ownership and consumer purchase behavior. This report examines how light-duty-vehicle residual values have evolved over time for conventional and advanced vehicle technologies, accounting for important factors such as market segment, size class, and country of assembly. Advancements in electric vehicle technology have led to plug-in vehicles exhibiting depreciation curves similar to those of conventional vehicles. This report compares two methods for determining depreciation trends (snapshot method and time-series method) in order to identify potential impacts on calculating vehicle total cost of ownership given differing data availability.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Vehicle Residual Value Analysis by Powertrain Type and Impacts on Total Cost of Ownership

Vehicle depreciation is a key factor in determining the total cost of vehicle ownership and consumer purchase behavior. This report examines how light-duty-vehicle residual values have evolved over time for conventional and advanced vehicle technologies, accounting for important factors such as market segment, size class, and country of assembly. Although plug-in vehicles have historically depreciated faster than conventional vehicles, advancements in electric vehicle technology have led to plug-in vehicles exhibiting depreciation curves similar to those of conventional vehicles. This report compares two methods for determining depreciation trends (snapshot method and time-series method) in order to identify potential impacts on calculating vehicle total cost of ownership given differing data availability.

33 ADVANCED PROPULSION SYSTEMS↗

CalCharge CRADA000008852 Master Agreement Amendment 1, Battery Consortium – Proprietary Activities

Lawrence Berkeley National Laboratory (LBNL) is partnering with the California Clean Energy Fund to launch CalCharge, an energy storage innovation accelerator, comprised of emerging and established California companies and related organizations developing battery technologies for the electric/hybrid vehicle transportation, the electric grid and consumer electronics markets. The vision of CalCharge is to accelerate the pace of technology innovation, business growth, and cluster development. Calcharge programs will deliver technology acceleration and technical expertise to the energy storage industry, as well as policy and market development support to strengthen the regional economy. LBNL shall collaborate with CalCharge members on the analysis and testing of battery and energy storage technologies. LBNL’s work will include analysis and testing of external design, examination of materials and components either separately or as a whole, and providing data and observations resulting from each collaboration. LBNL shall maintain and provide access to LBNL specialized facilities for research activities performed by or for CalCharge members. In addition, LBNL will provide expertise for short-term consultation, interpretation of testing data, or to clarify technical obstacles if requested by a Member. Over this time frame, Calcharge partnered with several start-ups to provide analytical resources. Those companies include Halotechnics, ZAF Energy Systems, Volkswagen Group of America, Toyota Motor Corporation, and Ensor Inc.

25 ENERGY STORAGE↗

A review of privacy in energy applications

As the distribution system continues to experience an increase in distributed energy resource (DER) and electric vehicle (EV) penetration, so does the need for new solutions that can help grid operators manage and leverage their capabilities. This will undoubtedly lead to new operational schemes and business opportunities that will transform the traditional consumer into a prosumer who will be more actively engaged in grid operations. Although the field is still under active development, many of the potential use cases presented in literature or industry are built upon edge computing, two-way communications, and other innovative computational constructs to attain their goals. However, at their core, many use cases assume a great level of data access to aid with the decision-making process, an assumption that may need to be revised to ensure fair and equitable operational processes are maintained. This may be particularly true as edge resources are predicted to participate in retail-side, many-to-many, or peer-to-peer markets and thus may lead to financial impacts if data access considerations are ignored. The need to revise data access mechanisms can be further justified by the introduction of new participants into the operational process, who do not have the same level of trust, nor the incentives to focus on energy delivery as their primary objective. At the same time, more consumers are becoming aware of their own data, and the potential impacts of its abuse. To help solution developers better understand these risks, this report has been developed to offer an initial introduction to the topic of privacy. This is achieved by 1) Highlighting the need for privacy-aware solutions; 2) Encouraging system designers to be inquisitive about the status quo; 3) Documenting the existing threat space; 4) Presenting and evaluating tools that may be helpful towards enabling better privacy postures; and 5) Making recommendations to encourage the adoption of better practices. From a technical perspective, the report focuses on evaluating two potential techniques by applying them to the Transactive Energy Space. Based on the obtained results, it can be established that differential privacy (DP) methods may have limited applicability when highly correlated, time-series data records need to be protected. However, DP may be a powerful tool when it is used to aggregate and analyze mid-size and large-size data sets in a more traditional statistical environment. The second tool under evaluation is threshold cryptography, which can guarantee complete secrecy (and thus privacy) but requires the establishment of key management procedures and dedicated communication channels for key coordination. Therefore, due to its increased computational overhead, the use of threshold cryptography must be weighted using a cost/benefit analysis on a per-application basis.

24 POWER TRANSMISSION AND DISTRIBUTION↗