Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Cost reduction”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 577 records · Page 32
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Energy transduction by reversible electron bifurcation

Electron bifurcation is a biological energy conversion process that oxidizes a two-electron donor at medium potential, coupled to the reduction of a high- and a low-potential acceptor species. This process is often fully reversible (can occur close to ΔG ≈ 0), allowing the creation of strong reductants with minimal free energy cost, using compounds with higher reduction potentials. For many years, the internal workings of electron bifurcating enzymes were poorly understood, especially regarding how short-circuit reactions are prevented. Recently, a conserved energy landscape was proposed to naturally insulate against short-circuit reactions, enabling efficient and reversible electron bifurcation (the reversible EB scheme). Here, we review the physical principles that underpin the EB scheme, describe how the reversible EB scheme is distinct from previous views, and outline questions that remain open.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Electrochemical-assisted leaching of active materials from lithium ion batteries

The development of a circular economy for lithium-ion batteries (LIB) is essential to realize decarbonization and an electrified energy market. However, the current commercial operations that recover valuable constituents from LIBs require significant energy and reagents, which create toxic emissions and additional waste. We report an electrochemical-based method for leaching valuable metals from the active materials of mixed shredded LIBs. In this process, the use electrons, as green reagent, allows the use and regeneration of Fe 2+ in low concentrations as substitute for hydrogen peroxide as a reducing agent. Leaching in a membrane separated two-compartment electrochemical cell contributes to decrease the acid requirements as H+ can be generated electrochemically. With this design, leaching efficiencies over 96% for the active metals (Li, Co, Mn, and Ni) were demonstrated at pulp densities up to 240 g/L. Copper present in the active material is electrowon and recovered separately. Preliminary cost analyses demonstrate ca. 80% reduction in energy and chemical costs as compared to traditional hydrometallurgical routes.

25 ENERGY STORAGE↗
DOE OSTI2021

A Methodology for Robust Load Reduction in Wind Turbine Blades Using Flow Control Devices

Decades of wind turbine research, development and installation have demonstrated reductions in levelized cost of energy (LCOE) resulting from turbines with larger rotor diameters and increased hub heights. Further reductions in LCOE by up-scaling turbine size can be challenged by practical limitations such as the square-cube law: where the power scales with the square of the blade length and the added mass scales with the volume (the cube). Active blade load control can disrupt this trend, allowing longer blades with less mass. This paper presents the details of the development of a robust load control system to reduce blade fatigue loads. The control system, which we coined sectional lift control or SLC, uses a lift actuator model to emulate an active flow control device. The main contributions of this paper are: (1) Methodology for SLC design to reduce dynamic blade root moments in a neighborhood of the rotor angular frequency (1P). (2) Analysis and numerical evidence supporting the use of a single robust SLC for all wind speeds, without the need for scheduling on wind speed or readily available measurements such as collective pitch or generator angular speed. (3) Intuition and numerical evidence to demonstrate that the SLC and the turbine controller do not interact. (4) Evaluation of the SLC using a full suite of fatigue and turbine performance metrics.

17 WIND ENERGY↗
DOE OSTI2021

Future Cost Benefits Analysis for Electrified Vehicles from Advances Due to U.S. Department of Energy Targets

The U.S. Department of Energy’s Vehicle Technologies Office (DOE-VTO) supports research and development (R&D), as well as deployment of efficient and sustainable transportation technologies, that will improve energy efficiency and fuel economy and enable America to use less petroleum. To accelerate the creation and adoption of new technologies, DOE-VTO has developed specific targets for a wide range of powertrain technologies (e.g., engine, battery, electric machine, lightweighting, etc.). This paper quantifies the impact of VTO R&D on vehicle energy consumption and cost compared to expected historical improvements across vehicle classes, powertrains, component technologies and timeframes. We have implemented a large scale simulation process to develop and simulate tens of thousands of vehicles on U.S. standard driving cycles using Autonomie, a vehicle simulation tool developed by Argonne National Laboratory. Results demonstrate significant additional reductions in both cost and energy consumption due to the existence of VTO R&D targets compared to predicted historical trends. It is observed that, over time, the fuel consumption of different electrified vehicles is expected to decrease by 40–50% and a reduction of 45–55% for vehicle manufacturing costs owing to significant improvements through various VTO R&D targets.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

Innovative rail transport of a supersized land-based wind turbine blade

Wind turbine blade logistic providers are being challenged with escalating costs and routing complexities as one-piece blade approach lengths of 75 m in various regions of the U.S. land-based market. New lower cost solutions are needed to enable further reductions in the levelized cost of energy (LCOE) and continued market expansion. In this paper, a novel method of using existing U.S. rail infrastructure to deploy 100-m, one-piece blades to U.S. land-based wind sites is numerically investigated. The study removes the constraint that blades must be kept rigid during transport, and it allows bending to keep blades within a clearance profile while navigating horizontal and vertical curvatures. Novel system optimization and blade design processes consider blade structural constraints and rail logistic constraints in parallel to develop a highly flexible, rail-transportable blade. Results indicate maximum deployment potential in the Interior region of the United States and limited deployment potential in other regions. The study concludes that innovative rail transportation solutions combined with advanced rotor technologies can provide a feasible alternative to segmentation and support continued LCOE reductions in the U.S. land-based wind energy market.

17 WIND ENERGY↗
DOE OSTI2025

EM-Enhanced HyPOR Loop for Fast Fusion Cycles

Vacuum pumps are the heart of a fusion energy facility – fusion power cannot be generated without them. Nevertheless, the vacuum technology needed to operate a viable fuel cycle for a compact fusion power plant does not exist. Commercial vacuum technology offers the best solution to this challenge, but a pump oil recycling and detritiation system is necessary. Conventional oil detritiation processes have only been developed to deal with legacy waste and are too slow and destructive to the oil. Further, post hoc detritiation strategies are intrinsically inefficient. Our approach is to rethink the challenge holistically by designing the pumping fluid and tritium extraction system in an integrated manner to achieve an innovative solution. By selecting an oil for the specific task of pumping tritium and then designing our catalytic system to selectively target the tritium-bearing functional groups, an effective detritiation system (hydrocarbon pump oil recycling, HyPOR, loop) for fusion power plants can be obtained. The project demonstrated a HyPOR loop process that can selectively remove heavier hydrogen isotopes from pump oil, reaching the target of 99.5 % removal, with an uptake of less than 0.01% of tritium throughput, while also purifying the oil of radiation-induced damage. The recycled oil retained its pumping characteristics over 7 recycles and gamma irradiation over 30 MGy. By meeting these targets, the project enable a reduction in pump operational costs from $\$$14.5M/year to $\$$103k/year (>140× reduction), reducing pump electric power consumption from 2.8 MW to 0.25 MW (>10× reduction), and reducing in-process tritium inventory from 2.03 kg to 0.48 kg (>4× reduction).

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Scaling kinetic Monte-Carlo simulations of grain growth with combined convolutional and graph neural networks

Graph neural networks (GNN) have emerged as a promising machine learning method for microstructure simulations such as grain growth. However, accurate modeling of realistic grain boundary networks requires large simulation cells, which GNN has difficulty scaling up to. To alleviate the computational costs and memory footprint of GNN, we suggest a hybrid architecture combining a convolutional neural network (CNN) based bijective autoencoder to compress the spatial dimensions, and a GNN that evolves the microstructure in the latent space of reduced spatial sizes. Our results demonstrate that the new design significantly reduces computational costs with using fewer message passing layer (from 12 down to 3) compared with GNN alone. The reduction in computational cost becomes more pronounced as the spatial size increases, indicating strong computational scalability. For the largest mesh evaluated (160 3 ), our method reduces memory usage and runtime in inference by 117× and 115×, respectively, compared with GNN-only baseline. More importantly, it shows higher accuracy and stronger spatiotemporal capability than the GNN-only baseline, especially in long-term testing. Such combination of scalability and accuracy is essential for simulating realistic material microstructures over extended time scales. The improvements can be attributed to the bijective autoencoder’s ability to compress information losslessly from spatial domain into a high dimensional feature space, thereby producing more expressive latent features for the GNN to learn from, while also contributing its own spatiotemporal modeling capability. Training data are generated from stochastic grain growth simulations, providing realistic variability for learning robust microstructure evolution. Comprehensive system validation confirms that the model is accurate, robust, and scalable.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Fatigue performance of the Deeply Embedded Ring Anchor

Existing anchor solutions are limited in their applicability to the floating offshore wind industry, which demands prolonged load endurance in extreme weather conditions and varied seabed soils. This limitation restricts project feasibility and increases costs. In order to address these challenges, the Deeply Embedded Ring Anchor (DERA) is proposed to achieve substantial reductions in anchor costs through efficiency enhancements. Ensuring the long-term safety and reliability of the DERA, especially considering a minimum operational period of 25 years, necessitates a comprehensive understanding of fatigue damage. Induced by repetitive loading below material yield strength, fatigue poses a significant threat to structures exposed to waves and currents. Anchors, vital for station keeping, are susceptible to fatigue damage, particularly in the padeye area. This paper conducts a fatigue analysis, focusing on factors such as the wall thickness of the ring anchor, inner stiffeners, and stiffener thickness, to evaluate the performance of DERA in this context. The results showed that the stiffener significantly affects the elongation of the total life of the anchor. In conclusion, this paper focuses on advancing innovations like DERA, enabling the efficient utilization of offshore wind resources, and addressing safety concerns through meticulous fatigue analysis.

17 WIND ENERGY↗
DOE OSTI2026

Towaoc Housing Solar Initiative

The Towaoc Housing Solar initiative was implemented to install net-metered solar generation systems on twenty-three Tribal buildings in Towoac, CO on the Ute Mountain Ute Reservation. The project was funded 80% by Department of Energy and 20% by the Ute Mountain Ute Tribe. The project and grant are authorized by Ute Mountain Ute Tribal Council Resolution 2020-116. The systems were designed to cumulatively generate 160 direct current (DC) kilowatts on average, translating to 222,585 kilowatt hours per year. The average cost for the generation was calculated at $\$$3.34/watt with a return on investment period anticipated at 22 years for a simple payback of all costs, 11 years for the Tribe’s investment at 50% cost-share. The systems should last for 30 years. The primary goals of the project for the Tribe were identified as the reduction of electricity costs for the twenty three Tribal buildings of the Housing Authority (comprising 22 rental homes and a small apartment building with 11 units) and the reduction of carbon pollution through the transition of energy sources used in the buildings.

14 SOLAR ENERGY↗
DOE OSTI2022

Energy-effective and low-cost carbon capture from point-sources enabled by water-lean solvents

Aqueous amines, as the most mature carbon capture technology, are subject to high energy and cost penalties due to the large water content in their formulations. Emerging technologies are in demand to enable a transition to a low-carbon global economy. However, rigorous process modeling and techno-economic analyses are limited for emerging carbon capture technologies. Here, four CO 2 -Binding Organic Liquids (CO 2 BOLs), all water-lean solvents were presented as promising options towards energy-effective and low-cost carbon capture from point sources. Rigorous solvent property and process models were developed in Aspen Plus for a coal-fired power plant with CO 2 BOL-based carbon capture unit. Techno-economic analyses were conducted in 2018 US pricing basis. The results suggest that water-lean formulations can minimize water condensation and vaporization, leading to a 36% energy saving compared with aqueous amines. Indeed, these CO 2 BOLs can capture up to 97–99% CO 2 from coal fired plant. The estimated carbon capture cost is about $40/tonne CO 2 at 90–97% carbon capture rate, about 12–23% less expensive than the conventional aqueous amine technology. The comparison between these CO 2 BOLs showed that in addition to vapor liquid equilibrium and kinetics (key properties for aqueous solvents), viscosity, volatility, and hydrophobicity, also have strong impacts on the performance of water-lean solvents. The methods presented in this work can be used to evaluate other emerging carbon capture technologies, while the results linking costs and performance of carbon capture solvents with their properties. Additionally, this work identifies research directions and targets for further reductions in total costs of capture from either cost or energy perspectives for these leading water-lean solvents.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Machine learning reduces soft costs for residential solar photovoltaics

Further deployment of rooftop solar photovoltaics (PV) hinges on the reduction of soft (non-hardware) costs—now larger and more resistant to reductions than hardware costs. The largest portion of these soft costs is the expenses solar companies incur to acquire new customers. In this study, we demonstrate the value of a shift from significance-based methodologies to prediction-oriented models to better identify PV adopters and reduce soft costs. We employ machine learning to predict PV adopters and non-adopters, and compare its prediction performance with logistic regression, the dominant significance-based method in technology adoption studies. Our results show that machine learning substantially enhances adoption prediction performance: The true positive rate of predicting adopters increased from 66 to 87%, and the true negative rate of predicting non-adopters increased from 75 to 88%. We attribute the enhanced performance to complex variable interactions and nonlinear effects incorporated by machine learning. With more accurate predictions, machine learning is able to reduce customer acquisition costs by 15% ($0.07/Watt) and identify new market opportunities for solar companies to expand and diversify their customer bases. Our research methods and findings provide broader implications for the adoption of similar clean energy technologies and related policy challenges such as market growth and energy inequality.

14 SOLAR ENERGY↗
DOE OSTI2023

Spectral-partitioned Kohn-Sham density functional theory

Here we introduce a general, variational scheme for systematic approximation of a given Kohn-Sham free-energy functional by partitioning the density matrix into distinct spectral domains, each of which may be spanned by an independent diagonal representation without requirement of mutual orthogonality. It is shown that by generalizing the entropic contribution to the free energy to allow for independent representations in each spectral domain, the free energy becomes an upper bound to the exact (unpartitioned) Kohn-Sham free energy, attaining this limit as the representations approach Kohn-Sham eigenfunctions. A numerical procedure is devised for calculation of the generalized entropy associated with spectral partitioning of the density matrix. The result is a powerful framework for Kohn-Sham calculations of systems whose occupied subspaces span multiple energy regimes. As a case in point, we apply the proposed framework to warm- and hot-dense matter described by finite-temperature density functional theory, where at high energies the density matrix is represented by that of the free-electron gas, while at low energies it is variationally optimized. We derive expressions for the spectral-partitioned Kohn-Sham Hamiltonian, atomic forces, and macroscopic stresses within the projector-augmented wave (PAW) and the norm-conserving pseudopotential methods. It is demonstrated that at high temperatures, spectral partitioning facilitates accurate calculations at dramatically reduced computational cost. Moreover, as temperature is increased, fewer exact Kohn-Sham states are required for a given accuracy, leading to further reductions in computational cost. Finally, it is shown that standard multiprojector expansions of electronic orbitals within atomic spheres in the PAW method lack sufficient completeness at high temperatures. Spectral partitioning provides a systematic solution for this fundamental problem.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Improving Economics of Generation 3 CSP System Components Through Fabrication and Application of High Temperature Nickel-Based Alloys

To improve the efficiency and lower the cost of Concentrating Solar Power (CSP) plants, new Generation 3 ‘Gen 3’ CSP concepts using novel salts, solids, or gas heattransfer media envisaged to integrated with a supercritical CO 2 (sCO 2 ) power block at temperatures >715ºC are being investigated. Regardless of the specific pathway, critical components including receivers, piping, and heat-exchangers (HXs) will require the use of heat-resistant nickel-based alloys. Furthermore, the use of age-hardenable alloys, such as INCONEL® alloy 740H® (alloy 740H) may be needed to reduce capital cost. The unique challenges presented by CSP plants to material manufacture, such as small diameter thin-walled tubing in receivers, large diameter thin wall piping, and thin sheet and tubes for HXs can add to the cost to produce such alloys when compared to traditional wrought and cast processing. The goal of this project was to facilitate a reduction of plant cost by developing alternate manufacturing routes and quantifying the performance and economic benefits for alloy 740H in comparison to other candidate nickel-based alloys through fabrication trials, high-temperature mechanical property studies, and interactions with technology developers and codes and standards.

14 SOLAR ENERGY↗
DOE OSTI2024

Demonstration of a Continuous Motion Direct Air Capture System

Global Thermostat (GT) has developed a process that addresses the primary technical challenges associated with direct air capture (DAC): the ability to process enormous volumetric flowrates of air and provide the energy for regeneration at acceptable cost. However, at current, there is opportunity for improvement in overall capture costs and especially in capital costs. While GT has advanced its base technology to TRL levels supporting commercial deployments, its research strategy includes alternative technology embodiments that enable substantial reductions in the cost per tonne of CO 2 removed. The objective of this project is to advance the most promising of these embodiments, where a DAC plant is operated in a continuous fashion rather than a discrete stepwise fashion (GT’s commercial scale technology approach). The Continuous Motion Direct Air Capture (cDAC) System’s advantages over the GT baseline stepwise DAC platform have been proposed primarily as a reduction in the complexity required for starting and stopping a movement system, relaxing requirements for other components designed for a rapid switching application, and a flattening of the sharp instantaneous fluid flowrates into steady-state mass & energy flows to enable smoother operation and easier heat integration. These advantages can lead to shorter cycle times, greater plant reliability, and lower capital expense. The primary objective of this project is the design, construction, commissioning, and operation of a field-test unit (FTU) at a scale in the range of ~200 tons CO 2 per year. Data generated from the operation campaign would then be used in a prescreening techno-economic analysis (TEA) and life cycle analysis (LCA), allowing this process to be compared to other carbon capture technologies.

42 ENGINEERING↗
DOE OSTI2025

Develop an efficient and cost-effective novel anaerobic digestion system producing high purity of methane from diverse waste biomass

This project focuses on developing an advanced, intensified anaerobic digestion system aimed at transforming the treatment and conversion of organic wastes into valuable products, specifically renewable natural gas. The motivation for this research stems from the limitations of conventional anaerobic digestion technologies, which often face challenges such as long retention times, high operational costs, and incomplete organic material degradation. The new technology called Intensified Versatile Anaerobic Digestion (IVAD), is developed to address these challenges by incorporating innovative reactors and processes that enhance the overall efficiency and output of anaerobic digestion. The significance of this project lies in its potential to revolutionize waste management practices and waste biomass utilization. The IVAD system integrates a hyperthermophilic anaerobic acidification reactor, a hydrothermal treatment (HTT) unit, and both thermophilic and mesophilic methanogenic reactors. This combination enables a higher rate of organic breakdown and energy recovery, resulting in faster processing times, reduced reactor sizes, and lower operational costs compared to traditional systems. Key data include an increase in methane productivity to 1.18 m 3 /m 3 /day, a significant improvement compared to the baseline technology’s 0.64 m 3 /m 3 /day. Additionally, the IVAD system achieves a 45% reduction in levelized cost of energy (LCOE), down to $\$$10.04/MMBTU, and an energy return on investment (EROI) of 3.19, representing an 87% increase over baseline levels. Technical and economic analyses highlight that the IVAD system significantly reduces hydraulic retention time (HRT) and solid retention time (SRT). The HRT for the HTT reactor can be reduced from 1 hour to 0.5 hours, while decoupling SRT from HRT in the anaerobic acidification reactor (AAR) allows for further reductions. These design optimizations lead to smaller reactor volumes, cutting down equipment and construction costs. Despite these advancements, energy consumption remains comparable to conventional methods due to a novel heat recovery strategy, enhancing overall process productivity. The system also achieves in-situ CO 2 removal and ammonia stripping features, resulting in biogas with a methane purity level of 75%, and produces high-quality nitrogen fertilizer as an additional by-product. Public benefits of the IVAD system are substantial, contributing to sustainable waste management and renewable energy production. By providing a scalable solution that can be adopted by dairy farms and similar agricultural operations, the IVAD system helps reduce waste, produce renewable natural gas (RNG) suitable for transportation fuel, and generate fertilizer, supporting a circular economy. This project plays a role in achieving broader environmental objectives by mitigating greenhouse gas emissions and promoting energy independence. Additionally, it offers a pathway for farmers to lower operational costs while adopting practices that are both environmentally sustainable and economically advantageous.

03 NATURAL GAS↗
DOE OSTI2020

Novel Membrane and Electrodeposition-Based Separation and Recovery of Rare Earth Elements from Coal Combustion Residues (Final Report)

This project developed a hydrometallurgical-based technology to extract and concentrate rare earth elements (REEs) from a representative group of coal combustion residuals (CCRs) from major coal sources in the United States. The approach for REE recovery comprises two general components: (1) Leaching of REEs from CCRs and (2) Separation of REEs from other major ions in the CCR leachate. The leaching step entails acid leaching with nitric or hydrochloric acid, and in some cases, pretreatment of CCRs with alkaline roasting prior to acid leaching. The follow-up REE recovery steps involve a series of membrane-based methods to separate and concentrate rare earth ions from other major ions in acid leachates of CCRs. These methods include liquid emulsion membranes, supported liquid membranes and electrodeposition with carbon nanotube electrochemical filters. The advantage of these separation approaches (relative to conventional approaches such as solvent extraction) is a reduction in the usage of solvents and other costly chemicals and a reduction of hazardous waste products that are challenges in conventional REE separation methods. In the testing of our process, we selected a representative set of CCR samples from our collection and performed a suite of characterization measurements (total REE content and major mineralogy). The major results of this work demonstrated that heated acid leaching could efficiently extract REEs from PRB-based coal fly ashes while the Appalachian and Illinois Basin CCRs required alkaline roasting with NaOH prior to acid leaching at room temperature. The supported liquid membrane (SLM) configuration and electrochemical deposition (ED) system yielded the most promising methods of REE recovery from the acid leachates of fly ash. Our most concentrated product to date comprised 1 wt.% (dry basis) REEs produced from an Appalachian-based fly ash leached and purified by SLM. The SLM separation process was more selective for heavy REEs over the light REEs. When SLM was combined with ED, preliminary results demonstrated that a final product of >2 wt.% REEs was possible.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2020

Algae/Wood Blends Hydrothermal Liquefaction and Upgrading: 2019 State of Technology

The fiscal year (FY) 2019 State of Technology (SOT) Assessment for a microalgae and woody biomass blend feedstock hydrothermal liquefaction (HTL) and biocrude upgrading system has been completed and reported here. This study is a preliminary economic analysis for this system. Inputs from the 2019 NREL open pond algae cultivation model provided microalgae seasonal flowrates and dewatered algae feedstock price. These inputs have been coupled with modeled experimental data from PNNL for algae/wood blends processed via HTL to assess the cost impacts. The TEA results demonstrated a 28% reduction in the conversion cost only from $1.22/gge in 2018 to $0.88/gge in 2019.

09 BIOMASS FUELS↗
DOE OSTI2022

Port of New York and New Jersey Drayage Electrification Analysis

The National Renewable Energy Laboratory (NREL) evaluated the potential for drayage electrification in the Port of New York and New Jersey (PoNYNJ), with a focus on operators: Harbor Freight Transport (HF), Safeway Trucking (SWT), and International Motor Freight Inc (IMF). This report summarizes the data collection and electrification evaluation of all three drayage operators, includes detailed operational data, and identifies the performance requirements for battery electric tractors (BETs) and corresponding infrastructure operated within the context of PoNYNJ drayage operation. This report also details a methodology to evaluate opportunities, strategies, and challenges associated with future expansions of BETs in meeting PANYNJ emissions goals. The Port Authority has established a goal of achieving Net Zero carbon emissions by 2050 across all facilities, including from tenant and stakeholder sources such as drayage trucks. NREL used real-world performance data collected on the three PoNYNJ drayage operations, along with modeling and analysis tools to compare BET to diesel trucks. From March to July 2021, NREL collected 1Hz vehicle and engine data from 46 drayage trucks at the three operators totaling nearly 121,000 miles of operation, providing enough information to assess vehicle operations for electrification potential. A Future Automotive Systems Technology Simulator (FASTSim) electric truck powertrain model was validated using PoNYNJ data and scenarios were run to evaluate drayage truck electrification requirements over the real-world cycles. The first scenario examined BET viability with minimal changes to existing operations. This assumes the trucks charge when stopped for two hours or longer, have a functional battery size of 375 kWh, and can charge at 270 kilowatts (kW) average which are the specification of the commercially available Freightliner eCascadia. The second scenario looked at what operational, charging infrastructure, and BET technology changes would be needed to fully electrify. Finally, detailed analysis was run on charging rate structure to understand operational costs to the fleets. The studied drayage trucks averaged 5.1 MPG, spent roughly 9% of their energy at idle, and drove an average of 140 miles per day with a maximum daily distance of 573 miles. The FASTSim model results indicate a comparable BET would use 417 kWh of energy per day on average accounting for cargo weight, which is close to the full usable capacity of the eCascadia currently available on the market. Based on the daily average operating data, partial fleet electrification is possible with current technology. However, some specific days of operation would require over 1,600 kWh of energy due to longer distances traveled by the trucks and more intense operation. Trucks used for long distance and intense operation cannot be readily electrified with current technology without operational changes. Full adoption of BETs could reduce CO 2 emissions from these fleets by roughly 75% today, eliminating 76 metric tons of CO 2 (MTCO 2 ) per vehicle each year, which equates to 24,100 MTCO 2 per year for all three operators. Commercially available direct current fast chargers (DCFC) have charge rates up to 350 kW. Based on the average daily modeled energy use for each operator, current industrial rate structures, and the assumption of 350 kW peak charging, full drayage electrification would increase electricity consumption. In addition, peak demand usage would increase with unmanaged charging along with cost of electricity having a direct impact on cost per mile for electric vehicles. The resulting cost per mile for BETs along with comparable cost per mile for conventional diesel trucks are also examined at $\$$4.00 per gallon of diesel. It will be important for PANYNJ and the drayage operators within the PoNYNJ to consider these load impacts to their existing electrical infrastructure and devise operational strategies that avoid coincident charging of vehicles to mitigate demand charges. Despite these electricity cost increases, savings from reductions in diesel consumption will help offset the costs of this increased electricity consumption. However, prices of both electricity and diesel are subject to change based on various factors meaning the realized savings will vary over time. This shows BETs could be cost-competitive on an energy cost per mile basis for all scenarios while diesel is above $\$$3.00/gal. Further, if diesel prices dropped to the 15-year low of $2.33/gal, it would still be cost competitive to operate the EVs with electricity costs of 16.3 ¢/kWh or less.

33 ADVANCED PROPULSION SYSTEMS↗