Engineering topics

Bennett, Jesse

Publications and source records attributed to Bennett, Jesse.

5 records

DOE OSTI2024

Analyzing School Bus Electrification in Richmond, Virginia

School buses are an essential component of the transportation infrastructure, serving as a lifeline for students across the globe. However, the widespread use of diesel school buses has raised concerns about the health impact on millions of students exposed to harmful emissions daily. Recognizing this issue, school districts worldwide are urgently seeking cleaner energy alternatives. Electric school buses emerge as an environmentally friendly and sustainable option, fostering a healthier environment for both students and communities. However, school bus electrification faces the challenges of high upfront cost, cumbersome charging management, and constraints from power grids. To help school bus operators address those challenges, this study presents a data-driven analysis for school bus electrification. This study considered a real-world school bus system in Richmond, VA, and developed a mathematical programming model to analyze the system design, charging strategies, and charging load profiles for the electrification scenario. The study evaluated different charging strategies based on model outcomes, aiming to optimize efficiency and effectiveness. Ultimately, this research generated electric school bus charging demand profiles under various scenarios, shedding light on the feasibility and implications of transitioning to electric-powered school buses.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2024

Slide Decks for EV@S Stakeholder Meeting at INL September 2024

These slides were used at the Electric Vehicles at Scale National Lab Consortium, Stakeholder Meeting hosted at INL in September 2024. The slides are now requested to be made available publicly for reference. All slides review projects that are already in the public domain and their information is intended for public release. They are not from sensitive topics or areas with any restrictions. A few projects are overviewed in detail and some slides were just an aid to the breakout sessions that were conducted with stakeholders and lab staff.

25 ENERGY STORAGE↗

DOE OSTI2024

Assessment of Alternative Fueling Infrastructure in the United States

NHTSA uses the Corporate Average Fuel Economy (CAFE) Model to analyze potential CAFE standards and their impact on emissions and vehicle fleet composition. The CAFE model analyzes the application of potential technologies to the current automotive industry vehicle fleet to determine the feasibility of future CAFE standards and the associated costs and benefits of the standards. A significant portion of the engineering input development is related to the effectiveness (energy consumption reduction) of each fuel-saving technology and the combination of several fuel-saving technologies, including AFVs. The purpose of this report is to deepen NHTSA's understanding of alternative fueling infrastructure and its potential impact on the adoption of alternative fuel vehicles (AFVs) so that AFVs can be more accurately and comprehensively incorporated into the CAFE Model. This report analyzes the current state of alternative fueling infrastructure in the United States and its relationship to the light-, medium-, and heavy-duty AFV markets; explores the costs associated with alternative fueling infrastructure; investigates trends driving the deployment of alternative fueling infrastructure; explores how the adoption of various vehicle and fuel technologies may look in the future; and analyzes the evolution of alternative fueling corridors.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2024

Survey and Gap Prioritization of U.S. Electric Vehicle Charge Management Deployments

The goal of this study was to survey and characterize the scope of current technical and programmatic knowledge pertaining to EV charge management technologies and practices in the US and relevant international jurisdictions. This characterization of existing field demonstrations and knowledge derived were used to determine gaps in the SCM demonstration landscape. Addressing these gaps through research and demonstration could increase confidence in the U.S. that load management and EV charge control could achieve overarching societal benefits. A survey of charge management deployments and input from stakeholders was completed to determine the state-of-the-art of smart charge management (SCM) where SCM is defined as controlling the amount of power exchanged between chargers and EVs to meet customers' charging needs while also responding to external power demand or pricing signals to provide load management, resilience, or other benefits to the customer and electric grid. The survey was the basis of the gap analysis in this report and determines which areas are well understood, with high confidence, and which areas need further investigation. Existing examples of EV charge management are characterized here to determine aspects that are ready for widespread deployment and have been demonstrated in the field. These include demonstration studies, pilots, programs, and EV-specific tariffs. In all, 110 examples of charge management were characterized. The data sources were public literature and utility filings as well as targeted interviews. In addition, 43 interviews with stakeholders were conducted with a consistent set of questions used in each interview. This study prioritized gaps in demonstrated SCM capabilities based on 1) Urgency of the particular use-case to offset traditional grid assets, 2) Impact, extensibility, and scaling of results across the entire spectrum of 3000+ utility service territories including projected technical and market potential for a given grid service, and 3) Value of federal funding in addressing the gap, including potential to leverage and/or add scope to existing field demonstrations funded by other non-federal funding mechanisms.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2023

Data-driven method for electric vehicle charging demand analysis: Case study in Virginia

Electric vehicle (EV) adoption in the U.S. will be accelerated by the historic $7.5 billion public investments in EV charging infrastructure. Careful analysis of EV charging demands plays a vital role in understanding the energy requirements, power grid impact, and smart charging management opportunities of EVs. To this end, this paper develops a data-driven trip-chaining-based modeling framework including five steps: Trip data acquisition and preprocessing, EV adoption modeling, travel itinerary synthesis, EV charging demand simulation and EV load profile generation. The developed analysis framework was demonstrated using real-world data for one region in Virginia, U.S. The results show that the proposed modeling framework can work effectively. For the study region in 2040, the predicted number of plug-in EVs is 470,114, resulting in a weekly charging demand of 38,078,127 kWh (55% home, 9% work, and 36% public) in September and 45,920,358 kWh (61% home, 9% work, and 30% public) in February.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗