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Hunter, Chad

Publications and source records attributed to Hunter, Chad.

T3CO (Transportation Technology Total Cost of Ownership) Open Source [SWR-21-54]

T3CO (Transportation Technology Total Cost of Ownership), is open source software for modeling total cost of ownership for commercial vehicles with advanced powertrains. T3CO is a modeling framework for determining geospatially and temporally optimized total cost of ownership (TCO) for vehicle powertrain technologies. T3CO runs NREL's FASTSim™ software for a representative set of operating conditions to minimize TCO based on vehicle parameters that affect purchase and operating costs (e.g., fuel/electricity consumption, asset depreciation, opportunity costs associated with charging time) while simultaneously ensuring that firm performance constraints (e.g. zero-to-sixty time, gradeability) are satisfied. T3CO will enable the user to control which powertrain parameters are used in optimizing TCO, and these parameters will be modified by a multi-objective optimization (MOO) algorithm to identify a Pareto-optimal solution set. The optimization algorithm will be modular so that users can choose from many different MOO options or insert their own user-defined optimization tool. NREL T3CO Homepage: https://www.nrel.gov/transportation/t3co.html PyPI package: https://pypi.org/project/t3co/

Lustbader, Jason↗

Powertrain Performance and Total Cost of Ownership Analysis for Class 8 Yard Tractors and Refuse Trucks

Advanced powertrain technologies, specifically fuel cell electric powertrains, have gained attention as viable alternatives for medium- and heavy-duty (M/HD) vehicles. However, it is unclear how these alternative powertrain vehicles stack up against their diesel counterparts in terms of performance and total cost of ownership (TCO). Furthermore, there are vehicle segments within the M/HD sector that have remained unstudied for fuel cell electric applications. This analysis aims to provide a comparative scoping-level TCO and performance analysis for two heavy-duty vocation vehicles (Class 8 U.S. port-side yard tractor and Class 8 U.S.-based refuse truck) for both conventional diesel and heavy-duty fuel cell electric (HDFC) powertrains. The refuse truck analysis also considered compressed natural gas powertrains (CNG) for comparison. The analysis includes seven timeframes (2020, 2025, 2030, 2035, 2040, 2045, and 2050) for comparison. This simplified TCO analysis includes only direct costs (fuel price, glider purchase price, and operating & maintenance costs) and excludes any associated indirect cost (e.g., dwell time costs and other opportunity based costs). Representative drive cycles for each vehicle were based on on-board GPS logged data and chosen by the analysis team to represent average, non-extreme driving conditions. At the time the analysis was performed, the Inflation Reduction Act was not in effect and therefore any potential subsidies and future cost reductions enacted under the Inflation Reduction Act were not included. Based on the operational setpoints used in this analysis, HDFC powertrains for both yard tractors and refuse trucks have the potential to achieve TCO advantages over conventional diesel powertrains (and CNG for refuse truck applications) in the near- to mid-term future while meeting the necessary duty cycle performance requirements. Yard tractors and refuse trucks spend a significant amount of time operating at low speeds, with long durations of idling, and experience numerous start/stop occurrences. These operational characteristics favor fuel cell performance as fuel cells operate with higher efficiencies at lower percentages of total power output. Conversely, conventional diesel and CNG engines are most efficient at higher percentages of total power output. This helps HDFC powered yard tractors and refuse trucks realize improved fuel economy when compared to their diesel counterparts, which helps reduce total fuel costs and therefore, total TCO. The analysis demonstrates that fuel prices play a significant role in determining TCO for each vehicle and should remain an R&D focus area. Overall, under the analysis' specified conditions, HDFC yard tractors have the potential to achieve cost parity with diesel yard tractors as early as 2025. For refuse trucks, HDFC refuse trucks have the potential to achieve cost parity with diesel and CNG refuse trucks in 2030 and 2040, respectively.

33 ADVANCED PROPULSION SYSTEMS↗

Michigan Hydrogen and Fuel Cell Electric Vehicle Deployment Plan: H2 FCEV Roadmap 2022

This report describes a roadmap for hydrogen fuel cell electric vehicles in the state of Michigan. This plan provides links to relevant information to assess, plan, and initiate hydrogen and FCEV deployment to help meet the energy, economic, and environmental goals for the State of Michigan. Policies and incentives that support hydrogen and fuel cell technology will increase deployment, thus increasing production and creating jobs throughout the supply chain. As deployment increases, an economy of scale will develop and manufacturing costs will decline, positioning hydrogen and fuel cell technology to compete more effectively in a global market without incentives. Policies and incentives to purchase and support the deployment of FCEVs, FCEBs, and hydrogen refueling can be coordinated regionally to maintain this advanced clean transportation sector as a global exporter for long-term growth and economic development. Overall, the execution of this plan will maintain Michigan's role as a global showcase for regionally manufactured transportation technology while reducing NOx and CO 2 emissions and as new jobs are created for businesses and industry.

08 HYDROGEN↗

Analysis of Benefits Associated With Projects and Technologies Supported by the Clean Transportation Program

The California Energy Commission's Clean Transportation Program (CTP) supports a wide range of alternative, low-carbon fuel and vehicle projects. This report improves upon the 2014 Alternative and Renewable Fuel and Vehicle Technology Program (ARFVTP) Benefits Report(the former name of the Clean Transportation Program), which focused on two components of benefit calculation: expected benefits and market transformation benefits. The "expected benefits" are defined as benefits that accrue because of the direct displacement of petroleum-based fuels or vehicle technologies. The "market transformation benefits" accrue because of CTP funding shifting the underlying market dynamics and accelerating the adoption of alternative fuel vehicles. This report documents the updated methods used in the benefits analysis in 2014 and applies them for this 2021 Clean Transportation Program Benefits Report. The project team used data collected from CTP projects funded from 2009 to the third quarter of 2021 to estimate the benefits between 2021 and 2030. CTP projects valued at $\$898.3 million$ were assessed (out of $\$1.04 billion$ funded) to estimate expected benefits of 249 million gallons per year petroleum reduction and 2.79 million metric tons per year of carbon dioxide equivalent greenhouse gas (GHG) reduction in 2030. Market transformation benefits are additive to the expected benefits and were estimated with high and low ranges for the 315 relevant projects evaluated. The market transformation benefits' GHG reductions are estimated as 2.2 million to 6.2 million metric tons of carbon dioxide equivalent per year and the petroleum reductions as 145.3 million to 671.5 million gasoline gallon equivalents per year in 2030. Combining both benefit types, the CTP projects can make significant progress toward meeting California's long-term GHG and petroleum fuel use reduction goals.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Big Box Retail Grocery Store and Electric Vehicle Station Load Profiles

This dataset includes yearlong, one-minute resolution time series profiles for the big box retail grocery stores stores simulated in Phoenix, Houston, Denver, and Minneapolis, as well as electric vehicle charging time series profiles for the various ports, charging levels, and station utilizations produced for the study "Impact of electric vehicle charging on the power demand of retail buildings", published in 2021 (https://doi.org/10.1016/j.adapen.2021.100062). Please cite as: Gilleran, M., Bonnema, E., Woods, J. et al. Impact of electric vehicle charging on the power demand of retail buildings. Advances in Applied Energy 4, (2021). https://doi.org/10.1016/j.adapen.2021.100062

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Energy sector portfolio analysis with uncertainty

Governments are dealing with the challenge of how to efficiently invest in research and development portfolios related to energy technologies. Research and development investment decisions in the energy space are especially difficult due to numerous risks and uncertainties, and due to the complexity of energy's interactions with the broad economy. Historically, much of the U.S. Department of Energy's in-depth research and development analyses focused on assessing the impact of a research and development activity in isolation from other available opportunities and did not substantially consider risk and uncertainty. Endeavoring to combine integrated energy-economy modeling with uncertainty analysis and technology-specific research and development activities, the U.S. Department of Energy commissioned the development of the Stochastic Energy Deployment System to support and improve public energy research and development decision-making. The Stochastic Energy Deployment System draws from expert-elicited probability distributions for research and development-driven improvements in technology cost and performance, and it uses Monte Carlo simulations to evaluate the likelihood of outcomes within a system dynamics energy-economy model. The framework estimates the uncertain benefits and costs of various research and development portfolios and provides insight into the probability of meeting national technology goals, while accounting for interactions with the larger economy and for interactions among research and development investments spanning many energy sectors.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Spatial and Temporal Analysis of the Total Cost of Ownership for Class 8 Tractors and Class 4 Parcel Delivery Trucks

The medium- and heavy-duty transportation sector is experiencing rapid changes in powertrain technology innovation, with recent announcements of battery electric and fuel cell electric trucks being offered. The economics of these alternative powertrain vehicles are uncertain and difficult to compare directly. This analysis seeks to provide a rigorous, techno-economic analysis of all of these alternative powertrain vehicles within the same analytic framework. Specifically, this report evaluates the total cost of ownership (TCO) of six different truck powertrain technologies (diesel, diesel hybrid electric, plug-in hybrid electric, compressed natural gas, battery electric, and fuel cell electric) for three different truck vocations (Class 8 long haul [750-mile range and 500-mile range], Class 8 short haul [300-mile range], and Class 4 parcel delivery [120-mile range]), for three different time frames (2018, 2025, and Ultimate).

08 HYDROGEN↗

Maximizing Solar and Transportation Synergies

This report considers the technological and market pathways that will enable better use of photovoltaic (PV) electricity as fuel for future transportation demand. Most of the pathways identified will require collaborative research and development (R&D) efforts to improve the capabilities of multiple technologies, including PV, energy storage, vehicles, electrolyzers, electrofuels, and infrastructure. For plug-in electric vehicles (PEVs), technologies that enable wide-scale managed and coordinated charging are among the highest priorities for continued research, development, and deployment in the near term. Furthermore, managed and coordinated charging capabilities are foundational for future vehicle-to-grid (V2G) functionality in the long term. For hydrogen fuel cell electric vehicles (FCEVs), the use of PV electricity for electrolysis provides an opportunity to increase PV deployment. For rail, air, and maritime transportation, the feasibility of increased PV use varies in the near term; opportunities for synergies with solar include the electrification of rail, increased reliability from airport microgrids, and switching from heavy fuel oil to clean maritime electrofuels made from PV-based hydrogen. Over the longer term, battery swap stations for electric airplanes and the co-location of solar with hydrogen fueling stations at shipping ports may enable greater synergies between PV and transportation.

14 SOLAR ENERGY↗

Vehicle Technologies and Hydrogen and Fuel Cell Technologies Research and Development Programs Benefits Assessment Report for 2020

The U.S. Department of Energy’s Vehicle Technologies and Hydrogen and Fuel Cell Technologies Offices (VTO and HFTO) support research and development of efficient and sustainable transportation technologies that will improve energy efficiency, minimize emissions, and enable America to use less petroleum. VTO and HFTO regularly revisit and update relevant research and development goals and areas of emphasis in response to the latest technological advancements and in alignment with current national priorities. As such, analyses of expected benefits resulting from VTO and HFTO investments and anticipated goal achievements are updated periodically and will be again for 2021 in the context of the latest national-level transportation decarbonization goals. The analysis in the present report is based on technical progress goals established in VTO and HFTO in the years immediately prior to and including 2020, and it summarizes the estimated energy and emissions benefits corresponding to achievement of those goals. The goals span research activities on batteries, electric drive technologies (EDT), combustion, lightweight materials, fuel cells, and hydrogen storage. The evaluation includes detailed analyses into the benefits of technology improvements on the U.S. light-duty (LD) vehicle fleet and separately on the U.S. medium- and heavy-duty (MDHD) vehicle fleet. This report summarizes the outcomes from each of these analyses both independently and in combination.

08 HYDROGEN↗

Impact of electric vehicle charging on the power demand of retail buildings

As electric vehicle penetration increases, charging is expected to have a significant impact on the grid. Electric vehicle charging stations will greatly affect a building site's power demand, especially with the onset of fast charging with power levels as high as 350 kW per charger. Here, we assess how electric vehicle charging stations would impact a retail big box grocery store, exploring numerous station sizes, charging power levels, and utilization factors in various climate zones and seasons. We measure the effect of charging by assessing changes in monthly peak power demand, electricity usage, and annual electricity bill, computed using three distinct rate structures. We find that an electric vehicle station has the potential to dwarf a big box building's power demand if behind the same meter, increasing monthly peak power demand at the site by over 250%. Cold-climate areas paired with rate structures incorporating high demand charges are most susceptible for significant changes to the annual electricity bill, with increases as high as 88%.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Comprehensive Total Cost of Ownership Quantification for Vehicles with Different Size Classes and Powertrains

In order to accurately compare the costs of two vehicles, the total cost of ownership (TCO) should consist of all costs related to both purchasing and operating the vehicle. This TCO analysis builds on previous work to provide a comprehensive perspective of all relevant vehicle costs of ownership. In this report, we present what we believe to be the most comprehensive explicit financial analysis of the costs that will be incurred by a vehicle owner. This study considers vehicle cost and depreciation, financing, fuel costs, insurance costs, maintenance and repair costs, taxes and fees, and other operational costs to formulate a holistic total cost of ownership and operation of multiple different vehicles. For each of these cost parameters that together constitute a comprehensive TCO, extensive literature review and data analysis were performed to find representative values in order to build a holistic TCO for vehicles of all size classes. The light- and heavy-duty vehicles selected for analysis in this report are representative of those that are on the road today and expected to be available in the future. Important additive analyses in this study include systematic analysis of vehicle depreciation, in-depth examination of insurance premium costs, comprehensive maintenance and repair estimates, analysis of all relevant taxes and fees, and considerations of specific costs applicable to commercial vehicles. We find that cars depreciate faster than light trucks and that older plug-in electric vehicles have a greater depreciation rate than newer electric vehicles. Light-duty vehicle (LDV) insurance costs show comparable costs for different powertrains, and lower costs for larger size classes. Medium- and heavy-duty vehicle (MHDV) insurance costs vary significantly by vocation. Electric and electrified powertrains have lower maintenance and repair costs than internal combustion engine (ICE) powertrains for all vehicle sizes, relative to vehicle price. MHDV maintenance and repair costs depend heavily on vocation and duty cycle. LDV taxes and fees are comparable across powertrain types and size classes, though marginally higher registration fees exist for alternative fuel vehicles. MHDV fees depend on the vocation, weight rating, and state. Many electric tractor trailers would be affected by additional battery weight, reducing the available payload capacity, and this cost can be substantial. Electric vehicle charging for commercial vehicles can be time-consuming; labor rates can cause this cost to dominate TCO. With improved knowledge of each of the cost components, we calculate a lifetime TCO for comparison across vehicles of different types and attributes. For a simulated small sport utility vehicle in 2025, modeled using Autonomie, the hybrid electric vehicle (HEV) has the lowest cost, followed by the conventional ICE vehicle. For MHDV, TCO can be drastically different depending on the vocation. Long-haul vehicles typically have the lowest per-mile costs. Excluding labor costs, the class 4 delivery has a comparable TCO to the day cab. Vocational trucks, refuse trucks, and transit buses have a high per-mile cost of ownership due to maintenance and insurance. For all of these vehicles, the cost of operating the vehicle is heavily weighted by the labor of the driver, followed by the fuel costs. While the HEV begins as the lowest cost powertrain for passenger vehicles, fuel cells are forecast to reach cost parity by 2030 when hydrogen prices reach $\$ 5$/kg while battery electric vehicles (BEV) reach cost parity by 2035 at a battery cost of $\$ 98$ per usable kWh of capacity, with these two technologies being the lowest cost in 2050. For the class 8 day cab tractor, the HEV and ICE vehicle begin as the lowest cost powertrains, and the 250-mile BEV reduces in cost from the most expensive to the least expensive by 2030.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Methods for R&D Portfolio Analysis and Evaluation (Workshop Report)

The Workshop on Methods for R&D Portfolio Analysis and Evaluation convened on 17–18 July 2019 at the National Renewable Energy Laboratory in Golden, Colorado, and examined strengths and weaknesses of the various methodologies applicable to R&D portfolio modeling, analysis, and decision support, given pragmatic constraints such as data availability, uncertainties in estimating the impact of R&D spending, and practical operational overheads. Participants employed their deep expertise in approaches such as stochastic optimization, real options, Monte-Carlo analysis, Bayesian networks, decision theory, complex systems analysis, deep uncertainty, and technology-evolution modeling to critique the initial example models developed by the project’s core team and to conduct thought experiments grounded in real-life technology models, progress data, expert elicitation, and portfolio information. This engagement of participants’ methodological expertise with the practical requirements of real-life portfolio decision support yielded ideas for improved approaches, alternative methodological hypotheses, and hybridization of methodologies that are well-grounded theoretically, computationally sound, and realistically executable given data availability and other practical constraints.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Methods for R&D Portfolio Analysis and Evaluation (Workshop Report)

The Workshop on Methods for R&D Portfolio Analysis and Evaluation convened on 17-18 July 2019 at the National Renewable Energy Laboratory in Golden, Colorado, and examined strengths and weaknesses of the various methodologies applicable to R&D portfolio modeling, analysis, and decision support, given pragmatic constraints such as data availability, uncertainties in estimating the impact of R&D spending, and practical operational overheads. Participants employed their deep expertise in approaches such as stochastic optimization, real options, Monte-Carlo analysis, Bayesian networks, decision theory, complex systems analysis, deep uncertainty, and technology-evolution modeling to critique the initial example models developed by the project’s core team and to conduct thought experiments grounded in real-life technology models, progress data, expert elicitation, and portfolio information. This engagement of participants’ methodological expertise with the practical requirements of real-life portfolio decision support yielded ideas for improved approaches, alternative methodological hypotheses, and hybridization of methodologies that are well-grounded theoretically, computationally sound, and realistically executable given data availability and other practical constraints.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗