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At least 73 records · Page 4

High-Dimensional Data-Driven Energy Optimization for MultiModal Transit Agencies

Transportation accounts for 28% of the total energy use in the United States and as such, it is responsible for immense environmental impact, including urban air pollution and greenhouse gas emissions, and may pose a severe threat to energy security. As we encourage mode shift from personal vehicles to public transit, it is important to consider that public transit systems still require substantial amounts of energy; for example, public bus transit services in the U.S. are responsible for at least 19.7 million metric tons of CO 2 emission annually. As such it is absolutely crucial that we study the bottlenecks to energy efficiency in public transit and develop new algorithms that can help the public transit agencies, especially those that are still operating mixed fleets, which may consist of Electric vehicles (EVs), hybrids (HEVs), and internal combustion engine vehicles (ICEVs), optimize the operations by deciding which vehicles are assigned to serving which transit trips.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Electric Vehicle Charging Management in Smart Energy Communities to Increase Renewable Energy Hosting Capacity

Abnormal climates due to global warming have emerged as a big concern in the global community. To mitigate climate change and achieve sustainability, distributed energy resources (DERs), including solar and wind, have been recently deployed in power systems. As the penetration level of DERs has increased, however, it caused a multitude of issues in the power systems, such as voltage fluctuation in the distribution network limiting renewable hosting capacity. On the other hand, the electric vehicle (EV) industry is rapidly growing to facilitate the transition to a carbon-neutral community, illuminating the potential of EVs as a flexible grid asset to mitigate some of the issues and improve grid operation, if properly exploited. To explore the potential of EVs, this paper proposes an EV scheduling strategy. By using an optimal EV charging scheduling proposed, distribution system operators (DSOs) can minimize their operating costs and stably operate the system with a high level of DERs. To validate the method, a modified IEEE 33-bus system with DERs is developed. The case study shows the proposed scheduling strategizes EV charging to reduce the cost of PV curtailment. In the study, the method outperforms the renewable-only case with curtailment by 4.97% in DSO cost. It also demonstrates its potential to increase the renewable hosting capacity by harmonizing EV charging with renewables.

ADVANCED PROPULSION SYSTEMS,POWER TRANSMISSION AND↗

Vehicle-Cycle Inventory for Type C School Buses & Intra-City Transit Buses

This report documents the new inventory incorporated into the Research and Development version of Greenhouse gases, Regulated Emissions, and Energy use in Technologies (R&D GREET) 2025 model for the vehicle cycle of Type C school buses and intracity transit buses. The transportation sector contributes significantly to the United States’ energy consumption and resultant emissions (EPA, 2025a). However, public transit plays an important role in mitigating these impacts because it consumes a relatively low amount of energy per passenger (Congressional Budget Office, 2022). Public transit is widely used in the United States; more than 500,000 school buses (EPA, 2025b) and ~75,000 service buses (American Public Transportation Association, 2025) operate in the nation. These are primarily internal combustion engine vehicles (ICEVs) powered by diesel. Original equipment manufacturers (OEMs) are making efforts to electrify U.S. bus fleets by using batteries as a propulsion system to replace internal combustion engines. Electrification can reduce tailpipe emissions, such as particulate matter (with a diameter ≤10 µm [PM 10 ] and with a diameter ≤2.5 µm [PM 2.5 ]) and nitrogen oxides (Jonas et al., 2025; Martinez and Samaras, 2024; EPA, 2025b; Wayne et al., 2009). Hence, any energy and emission impact analysis of public transit must consider both conventional ICEVs and upcoming electric vehicle (EV) options for the school and transit buses that dominate this landscape. To understand the detailed environmental impact profiles of ICEV and EV school and transit buses, it is necessary to conduct a thorough analysis covering both vehicle manufacturing and vehicle use stages. The current literature lacks a detailed vehicle-cycle inventory for school and transit buses, which makes this kind of comparison difficult. To overcome this gap, we developed a comprehensive vehicle-cycle model for school and transit buses in Argonne’s R&D GREET 2025 model. The model is flexible in handling user inputs for key assumptions, such as component weights and material compositions, upstream energy sources for material processing, and vehicle operating parameters, to understand their impacts on energy use and emissions for both school and transit buses. This report is organized as follows: Section 2 provides details on the modeling approach and vehicle specifications (weights and composition of different vehicle components, and vehicle operating parameters) for both school and transit buses. Section 3 provides details on vehicle assembly, disposal, and recycling (ADR) approaches for the two buses. Section 4 includes details about their incorporation into the R&D GREET model.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Online characterization of primary and secondary emissions of particulate matter and acidic molecules from a modern fleet of city buses

The potential impact of transitioning from conventional fossil fuel to a non-fossil-fuel vehicle fleet was investigated by measuring primary emissions via extractive sampling of bus plumes and assessing secondary mass formation using the Gothenburg Potential Aerosol Mass (Go:PAM) reactor from 76 in-use transit buses. Online chemical characterization of gaseous and particulate emissions from these buses was conducted using chemical ionization mass spectrometry (CIMS) with acetate as the reagent ion, coupled with the Filter Inlet for Gases and AEROsols (FIGAERO). Acetate reagent ion chemistry selectively ionizes acidic compounds, including organic and inorganic acids, as well as nitrated and sulfated organics. A significant reduction (48 %–98 %) in fresh particle emissions was observed in buses utilizing compressed natural gas (CNG), biodiesels like rapeseed methyl ester (RME) and hydrotreated vegetable oil (HVO), and hybrid-electric HVO (HVO HEV ) compared to diesel (DSL). However, secondary particle formation from photooxidation of emissions was substantial across all the fuel types. The median ratio of particle mass emission factors of aged to fresh emissions increased in the following order: DSL buses at 4.0, HVO buses at 6.7, HVO HEV buses at 10.5, RME buses at 10.8, and CNG buses at 84. Of the compounds that can be identified by CIMS, fresh gaseous emissions from all Euro V/EEV (Enhanced Environmentally friendly Vehicle) buses, regardless of fuel type, were dominated by nitrogen-containing compounds such as nitrous acid (HONO), nitric acid (HNO 3 ), and isocyanic acid (HNCO), alongside small monoacids (C 1 –C 3 ). Notably, the emission of nitrogen-containing compounds was lower in Euro VI buses equipped with more advanced emission control technologies. Secondary gaseous organic acids correlated strongly with gaseous HNO 3 signals (R 2 =0.85–0.99) in Go:PAM, but their moderate to weak correlations with post-photooxidation secondary particle mass suggest that they are not reliable tracers of secondary organic aerosol formation from bus exhaust. Our study highlights that non-regulated compounds and secondary pollutant formation, not currently addressed in legislation, are crucial considerations in the evaluation of environmental impacts of future fuel and engine technology shifts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Spatially Resolved Domicile Charging Demands for Light-, Medium-, and Heavy-Duty Electric Vehicles in Virginia

The use of plug-in electric vehicles (PEVs) and resulting grid impacts are likely to grow rapidly, and evaluation of optimal smart charge management and grid integration strategies is warranted now. Evaluating distribution grid impacts requires fine-grained models of PEV operations to estimate charging loads across diverse vehicles at high spatial resolution. We propose such a model and consider a high-electrification scenario in Richmond and Newport News, Virginia. Our framework considers four categories of vehicle that are amenable to early aggressive electrification: light-duty passenger vehicles (LDV), trucks and vans with a focus on delivery or other local operations, school buses, and transit buses. These vehicles have a relatively consistent domicile, reducing the need for public charging infrastructure rollout to electrify. We apply a recent LDV model and propose new models for each vocation of medium- and heavy-duty vehicle, leveraging telematics data. We demonstrate our framework in Virginia and find energy demands in the region may total 15 GWh day, with most consumed by LDV. However, considering power demand at high spatial resolution reveals a different trend: LDVs have relatively small peak loads at specific sites (peak site demand around 800 kW) compared to average and high demand medium- and heavy-duty vehicle charging sites (peak site demand around 6,000 kW at a transit bus depot, 1,500 kW at a local freight hub, and 1,000 kW at a school). Our framework yields insights on the relative impacts of each vocation and enables future work to tailor grid integration strategies to each vehicle category.

33 ADVANCED PROPULSION SYSTEMS↗

Joint optimization of electric bus charging infrastructure, vehicle scheduling, and charging management

High upfront costs of vehicles and charging infrastructure as well as the lack of knowledge related to infrastructure planning and electric bus system operation are major obstacles to the implementation of battery electric buses (BEBs). To tackle the obstacles and promote BEB adoption, a comprehensive optimization framework was developed to address the combined charging infrastructure planning, vehicle scheduling, and charging management problem for BEB systems, with the goal to minimize the total cost of ownership. The problem was formulated as a mixed-integer non-linear problem. A genetic algorithm-based approach was then proposed to solve the problem. Last, three alternative scenarios based on a sub-transit network in Salt Lake City, Utah, were analyzed and compared with the optimal scenario results in the numerical experiments. Our comparison results demonstrate the effectiveness of the proposed model and solution algorithm in determining a cost-efficient planning strategy for BEB systems.

33 ADVANCED PROPULSION SYSTEMS↗

Blueprinting Electrified Transit System Implementation

To achieve a more affordable and reliable transportation system, we need to smartly upgrade our power systems and install a large number of charging stations, but conventional planning methods are not up to the task. By applying advanced simulation and optimization tools, we can design a smarter, more cost-effective electric transportation network. The initial focus was on public transit systems, demonstrating how this approach can deliver broader economic, reliability, and air quality benefits nationwide.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Evolving Architectures and Considerations to address Distributed Energy Resources and Non-Wired Alternatives

The electric grid is in the beginning stage of a transformation, driven by a combination of shutdowns of coal-fired plants, commissioning of new natural-gas plants, and tremendous growth in energy supply from renewables such as wind, and solar. As utilities navigate this transformation, their progress is supported by advances in Operational Technologies (OT), and Informational Technologies (IT), such as automation, smart inverters, cloud computing, mobile computing, machine learning, big data analytics, which have the potential to enable advanced capabilities more efficiently and at a lower cost. This white paper focuses on the architectural considerations that will allow the industry to transition in a planned manner. It introduces and formalizes two architectural constructs –the data bus and the control bus. The data bus is responsible for carrying all non-operational models and information necessary to drive utility decisions. In contrast, the control bus is responsible for carrying all operational data and control actions taken at the local level, centralized level, or other levels in-between. The paper reviews those architectural considerations, their requirements and how they will evolve. This paper intends to provide a context for vendors, utilities, and their service providers to review and understand the changes that are coming and get ready for them.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Feasibility and Qualitative Risk Assessment of Fuel Cell Electric Bus Use for Emergency Backup Power for Airport Applications

Airports rely on robust backup power systems to maintain critical operations during emergencies. This paper investigates the feasibility of using hydrogen fuel cell electric buses (FCEBs) as emergency backup power sources, focusing on their technical specifications, operational challenges, and associated risks. Using Portland International Airport as a case study, the analysis evaluates the power output and hydrogen consumption of New Flyer’s 40’ Xcelsior Charge fuel cell buses, to provide power for key airport systems. Additionally, the paper explores the design and layout of how FCEBs can be connected to airport facilities, and addresses safety considerations, hydrogen supply logistics, and electrical compatibility. While FCEBs present significant advantages in terms of sustainability and resilience, their implementation requires careful planning, infrastructure investment, and adherence to safety standards. This research provides actionable insights for airport stakeholders seeking to transition to hydrogen-based backup power system.

08 HYDROGEN↗

Mitigating Voltage Instability in the Saudi Grid for a Decarbonized, Fully Solar Power System

Lately, solar photovoltaic (PV) has received significant interest due to its economic and environmental benefits. As the integration of renewable energy sources (RES) increases into existing power grids, challenges such as the decrease in short circuit ratio (SCR) are introduced. Here, this paper investigates a case study of the Saudi power grid, examining the voltage stability as the grid transitions from traditional power generation to 100% penetration of solar PV gradually. Moreover, the paper explores the relationship between the increase in solar penetration and the potential effects on the short circuit MVA (SCMVA), which could significantly impact the overall SCR of the system. To meet the North American Electric Reliability Corporation (NERC) recommendation of maintaining SCR at a particular level, synchronous condensers (SC)s were integrated into the grid. The effectiveness of utilizing SCs to maintain the system voltage at optimal levels in a fully solar grid is also considered. In addition, this paper covers the weak grid analysis via utilizing the Newton-Raphson load flow method, along with PV and QV curve analyses. The purpose behind that is to determine weak bus locations in need of voltage improvements, and to meet the amount of reactive power to be injected. Finally, the amount of power being delivered by SCs will be added progressively in three scenarios to show the enhancements on SCR more precisely.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Multi-modal Energy-optimal Trip Scheduling in Real-time (METS-R) for Transportation Hubs (Final Report)

This report summarizes the work performed under the award number EE0008524. The project develops the Multi-modal Energy-optimal Trip Scheduling in Real-time (METS-R) platform as the next-generation transportation solution based on autonomous electric vehicles (AEV) serving passenger trips from and to urban transportation hubs, to substantially reduce transportation energy consumption. Extensive data collection and analyses were first conducted to understand the demand patterns and energy consumption of hub-based on-road trips. Then, a data-driven framework that consists of an analytical module and a simulation module was proposed. For the analytical module, five planning + operation tools were developed to support the planning and energy-efficient operations of urban AEV services: the charging station planning that robotically allocates charging supplies based on the stationary charging demand distribution; the transit planning and demand adaptive scheduling model that efficiently generates\ candidate transit routes from hubs to other places and dynamically adjusts the transit time table to fit the current demand; the online energy-efficient routing that learns the energy-optimal paths from observations of link-level energy consumption in real-time; the hub-based ridesharing that matches trip requests together with account for the uncertainty of future trip demand and vehicle supply; and finally, the integrated demand prediction and anomaly detection pipeline that leverages the flight/train time table and support other planning/operation tools. To demonstrate the performance of these tools, a scalable high-performance agent-based simulator was built. We divided the urban space into multiple service zones where each zone was considered as an agent for passenger generation and vehicle charging. Two types of AEV agents were coded to model two types of mobility services: AEV taxi and AEV transit. For the AEV taxi, the team implemented the functions of pickup/drop-off passengers, energy-efficient routing, ridesharing, fleet rebalancing, and recharging. For the AEV bus, the team implemented the functions of demand-adaptive route scheduling, passenger boarding, and recharging. A high-performance computing framework was introduced to receive various profiling information (such as link energy updates, vehicle speed) from the simulator instances and communicate the operational commands back to the instances. The numerical experiments show that each of the proposed operational algorithms can reduce energy consumption and improve system efficiency. Furthermore, there exists the need to collectively consider multiple planning + operational strategies as multiple strategies can influence each other in terms of performance impacts. Recommendations for future work related to AEV planning and simulation are discussed.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Optical Properties of Thin Film Molecular Mixtures

Thin films composed of molecular mixtures of metal and dielectric are being considered for use as solar selective coatings for a variety of space power applications. By controlling the degree of molecular mixing, the solar selective coatings can be tailored to have the combined properties of high solar absorptance, alpha, and low infrared emittance, epsilon. On orbit, these combined properties would simultaneously maximize the amount of solar energy captured by the coating and minimize the amount of thermal energy radiated. Mini-satellites equipped with solar collectors coated with these cermet coatings may utilize the captured heat energy to power a heat engine to generate electricity, or to power a thermal bus that directs heat to remote regions of the spacecraft. Early work in this area identified the theoretical boundary conditions needed to operate a Carnot cycle in space, including the need for a solar concentrator, a solar selective coating at the heat inlet of the engine, and a radiator. A solar concentrator that can concentrate sunlight by a factor of 100 is ideal. At lower values, the temperature of the solar absorbing surface becomes too low for efficient heat engine operation, and at higher values, cavity type heat receivers become attractive. In designing the solar selective coating, the wavelength region yielding high solar absorptance must be separated from the wavelength region yielding low infrared emittance by establishing a sharp transition in optical properties. In particular, a sharp transition in reflectance is desired in the infrared to achieve the desired optical performance. For a heat engine operating at 450C, a sharp transition at 1.8 micrometers is desired. The radiator completes the heat flow through the Carnot cycle. Additional work has been done supporting the use of molecular mixtures for terrestrial applications. Sputter deposition provides a means to apply coatings to the tubes that carry a working fluid at the focus of trough-style collectors. Sputtering offers considerable flexibility in coating conditions, including a wide variety of metal and dielectric targets. Coating designs range from simple two or three layer coatings to complex coatings that are purposely graded to be metal-rich at their base and oxide-rich at their surface in order to yield the desired solar selective properties. In these cermet coatings, molecular islands of metal are thought to be embedded in a three dimensional matrix of dielectric. Recent work has identified the use of custom made ion beam sputter deposition targets to produce coatings containing molecular mixtures of metal and dielectric. The targets are cylindrical and the surface consists of a gradually changing composition of metal and dielectric. Rotating the cylinder under the beam during ion beam sputter deposition yields a coating that is a molecular mixture of metal and dielectric, with the composition changing through the thickness of the coating. The optical properties of these coatings are not only dependent on their thickness and chemical composition, but are also dependent on the extent of the through thickness gradient established during deposition. This paper presents a summary of the optical properties of several thin film molecular mixtures designed as solar selective coatings. Optical performance is first identified as a function of wavelength, from the ultraviolet to the visible and infrared. Coating composition, thickness, and gradient from metal to dielectric also play an important role. Additional work for future activities is also identified.

Jaworske, Donald A.↗

Optical Properties of Thin Film Molecular Mixtures

Thin films composed of molecular mixtures of metal and dielectric are being considered for use as solar selective coatings for a variety of space power applications. By controlling the degree of molecular mixing, the solar selective coatings can be tailored to have the combined properties of high solar absorptance, , and low infrared emittance, . On orbit, these combined properties would simultaneously maximize the amount of solar energy captured by the coating and minimize the amount of thermal energy radiated. Mini-satellites equipped with solar collectors coated with these cermet coatings may utilize the captured heat energy to power a heat engine to generate electricity, or to power a thermal bus that directs heat to remote regions of the spacecraft. Early work in this area identified the theoretical boundary conditions needed to operate a Carnot cycle in space, including the need for a solar concentrator, a solar selective coating at the heat inlet of the engine, and a radiator.1 A solar concentrator that can concentrate sunlight by a factor of 100 is ideal. At lower values, the temperature of the solar absorbing surface becomes too low for efficient heat engine operation, and at higher values, cavity type heat receivers become attractive. In designing the solar selective coating, the wavelength region yielding high solar absorptance must be separated from the wavelength region yielding low infrared emittance by establishing a sharp transition in optical properties. In particular, a sharp transition in reflectance is desired in the infrared to achieve the desired optical performance. For a heat engine operating at 450 C, a sharp transition at 1.8 micrometers is desired.2 The radiator completes the heat flow through the Carnot cycle.

Jaworske, Donald A.↗

Building Blocks of Electric Vehicle Deployment: A Guide for Developing Countries

Countries can use electric transportation to help fulfill numerous goals, including greenhouse gas (GHG) emissions targets, local air quality goals, mobility objectives, energy security, and transportation resiliency. Vehicle electrification is a promising pathway to achieving clean energy transitions in the transport sector at scale. As vehicles electrify, the traditionally siloed electricity and transport sectors increasingly converge to create technical, institutional, and economic opportunities and challenges. To navigate this transition effectively, we propose the following foundational pillars or “building blocks” that undergird effective electric vehicle (EV) deployment. Jurisdictions with experience and mature EV markets offer useful lessons learned that may enable developing countries to leapfrog over common roadblocks. Nonetheless, developing countries face distinct challenges collectively, and individually, from developed countries that require careful consideration. From our work around the world, the U.S. Agency for International Development (USAID) and National Renewable Energy Laboratory (NREL) have witnessed interest growing in EVs for a variety of reasons. Lao People’s Democratic Republic (PDR), for example, looks toward EVs as a way to use their surplus of hydropower to displace expensive oil. Thailand and Pakistan seek economic development opportunities in EV manufacturing. Cities including Mexico City, Surat, India, and Kingston, Jamaica see the potential of bus electrification to improve local air quality and reduce traffic congestion. Many USAID partner countries in Southeast Asia are trying to understand how to reach ambitious EV deployment targets and implement EV and transportation plans. This pursuit is prompting questions about EV supply equipment (EVSE) standards, tariff design, and business models that affirm the importance of the building blocks outlined in this report.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Manufacturing Supply Chain Development for Modular Solar-Thermochemical Conversion Platform - CRADA 387 (Final Report)

Modular chemical process intensification (MCPI) is an emerging field where chemical processing is performed using small-scale modular equipment instead of conventional large centralized chemical plants. Conventional chemical plants benefit from economies of scale that encourage scale-up to ever larger plants. A goal of MCPI is to develop technology that intensifies processing so that equipment can be dramatically smaller and integrated into modular systems. Scale-up occurs by adding more modules in parallel rather than making the equipment larger. A key concept is that equipment and modules can ultimately be cheaper by leveraging economies of mass production, analogous to the automotive industry, in manufacturing the equipment. This project made significant progress toward this outcome by meeting the RAPID institute metric to reduce equipment cost by 20% for each doubling in manufacturing volume. The MCPI application was thermochemical technology that is being commercialized by STARS Technology Corporation, one of the CRADA partners. The technology converts solar and renewable power to chemical energy to produce renewable hydrogen, fuels, and chemicals. The benefit to the public is reduction in greenhouse gases that are contributing to climate change. The project transitioned the steam methane reforming (SMR) reactor from conventional fabrication methods to additive manufacturing (AM) direct metal laser sintering (DMLS) process. This is projected to reduce the cost of making a reactor by 58% when producing 100 reactors per year. Innovations in the DMLS process produced a patented design that reduces reactor weight by 60%. Reductions in material costs and processing time extend the DMLS advantage to higher production volumes. The new design promises to be 38% cheaper than the conventional processes at 1000 units per year. The resulting 87% reduction in the steam methane reforming (SMR) module cost in scaling from current costs meets the RAPID metric. The project was successful in producing and testing the first ever additively manufactured SMR reactors. A reactor achieved over 82% efficiency in converting electric power to chemical energy, which is a world record for an inductively heated SMR. The project has contributed to the design and assembly of a first demonstration plant that is headed to a hydrogen bus filling station in Thousand Palms, CA.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Development of a DC Distribution Testbed for High-Power EV Charging

This paper explores the design and implementation of a power hardware-in-the-loop (P-HIL) setup for DC distribution infrastructure integrated with high-power charging (HPC) of electric vehicles (EVs), DC loads, and sources. The utilization of DC distribution holds significant potential for enhancing the operation of a HPC station architecture. However, there are challenges establishing a DC charging hub including interoperability, commoditization, distributed energy resource integration, stability, DC protection, and lack of common system level controllers. To address these challenges, a testing setup is required that accommodates commercial off-the-shelf (COTS) products to evaluate different use cases at rated power and voltage levels. The developed P-HIL setup features a dedicated DC charging hub, DC-coupled chargers, DC loads/sources, DC protection, and a communication architecture. The integrated P-HIL system provides a versatile testing environment to address technology and interoperability gaps and implements a smart energy management system (SEMS). This platform enables comprehensive and robust testing of COTS devices, charger prototypes, SEMS controllers and protection schemes, which together will accelerate transition to EVs at scale. The setup is tested for various use-cases at full-scale, integrating 950 V DC bus voltage, 660 kW grid-tied inverter, 150 kW COTS charger, and 100 kW energy storage system within an open-source SEMS platform.

ADVANCED PROPULSION SYSTEMS,POWER TRANSMISSION AND↗

The 10 kW power electronics for hydrogen arcjets

A combination of emerging mission considerations such as 'launch on schedule', resource limitations, and the development of higher power spacecraft busses has resulted in renewed interest in high power hydrogen arcjet systems with specific impulses greater than 1000 s for Earth-space orbit transfer and maneuver applications. Solar electric propulsion systems with about 10 kW of power appear to offer payload benefits at acceptable trip times. This work outlines the design and development of 10 kW hydrogen arcjet power electronics and results of arcjet integration testing. The power electronics incorporated a full bridge switching topology similar to that employed in state of the art 5 kW power electronics, and the output filter included an output current averaging inductor with an integral pulse generation winding for arcjet ignition. Phase shifted, pulse width modulation with current mode control was used to regulate the current delivered to arcjet, and a low inductance power stage minimized switching transients. Hybrid power Metal Oxide Semiconductor Field Effect Transistors were used to minimize conduction losses. Switching losses were minimized using a fast response, optically isolated, totem-pole gate drive circuit. The input bus voltage for the unit was 150 V, with a maximum output voltage of 225 V. The switching frequency of 20 kHz was a compromise between mass savings and higher efficiency. Power conversion efficiencies in excess of 0.94 were demonstrated, along with steady state load current regulation of 1 percent. The power electronics were successfully integrated with a 10 kW laboratory hydrogen arcjet, and reliable, nondestructive starts and transitions to steady state operation were demonstrated. The estimated specific mass for a flight packaged unit was 2 kg/kW.

Hamley, John A.↗

Online energy consumption forecast for battery electric buses using a learning-free algebraic method

Accurately predicting the energy consumption plays a vital role in battery electric buses (BEBs) route planning and deployment. Based on the algebraic derivative estimation, we present a novel method to forecast the energy consumption in real time. In contrast to the mainstream machine-learning-based methods, the proposed method does not require access to the historical energy consumption data. It eliminates the time-consuming and computationally expensive offline training. Consequently, its prediction performance is not constrained by the quantity and quality of the training data. Moreover, the method can swiftly adapt to new situations not included in the previous driving cycles, which makes it especially suitable for emerging transport modes, e.g., on-demand transit services. In addition, its online execution only involves algebraic calculations, yielding superior calculation efficiency. Using real-world data, we comprehensively compare the performance of the proposed learning-free algebraic method with multiple representative machine-learning-based methods. Finally, the advantages and limitations of the proposed method are discussed in detail.

33 ADVANCED PROPULSION SYSTEMS↗