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At least 253 records · Page 14

Human Supervision of Autonomous Vehicle Fleet Operations and Associated Passenger Communications: Preprint

Advances in automated vehicle (AV) technology and expanded operations are rapidly emerging with Automated Mobility District (AMD) deployments in global cities. NLR's AMD research addresses critical elements of human supervision of AV fleet operations and associated passenger communications for vehicles in which no driver or safety attendant is present. Although sufficiently advanced AVs no longer have direct oversight by a driver, fleet management remains staffed with operations personnel at the operations command and control (OCC) facility. This paper examines the functionality of the OCC, drawing comparisons of how automated train control and automated people mover OCCs operate. Within an AMD, the OCC manages various vehicle types, sizes, and operational modes, including on-demand and fixed route service, to facilitate a 'network of networks' for transport within a metropolitan area. The OCC serves as oversight for multiple AV fleets assisting AVs via remote operation of vehicles, communication, and dispatching personnel to resolve problems. The OCC also coordinates system operation, geographically staging vehicles, and managing weather, police, and emergency events. Informed by traffic management center (TMC) strategies using highly integrated software and communications, OCCs facilitate seamless information flows. OCC personnel remotely assist passengers and oversee multi-party operation to ensure safety and security. Although social norms mitigate large-capacity unattended vehicle operations, social interaction in multi-party automated small vehicles has little precedent. This poses a new frontier for society and requires research to effectively understand and manage. Future research will monitor OCC implementations, passenger interfaces, and deployment scaling of initial AMD systems.

33 ADVANCED PROPULSION SYSTEMS↗

Solid Sorbent Cost Sensitivity Analysis: A Framework for UNF Reprocessing Sorbent Cost Comparison

Solid sorbents have been the subject of research and development across the U.S. Department of Energy national laboratory complex for many years. They are generally accepted as a safer alternative to cryogenic distillation for noble gas capture, and they present an easier pathway in development of long-term waste forms after iodine capture. As more types of sorbents have been proposed for capture of volatile radionuclides, it has become necessary to compare them based on performance and cost criteria. This report details cost and performance information for three promising sorbents and provides a cost sensitivity analysis. The goal of this analysis is to establish a framework which can be utilized to directly compare future sorbents, with differing properties, to the sorbents discussed in this report. Direct comparison is instrumental to making informed decisions to efficiently guide research and minimize laborious detours. In all cases, sorbent capacity is a major cost driver as it influences the mass of sorbent, operational footprint, and disposal cost requirements., However, sorbent price can greatly increase the cost of a capture technology. For sorbents used in krypton capture, the purity of krypton released to storage is the highest cost driver.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

ChargeX OCPI Recommendations

The Open Charge Point Interface (OCPI) is an open protocol that enables electric vehicle (EV) charging systems to work together across networks. It supports communication and data sharing between Charge Point Operators (CPOs), who manage charging stations, and e-Mobility Service Providers (eMSPs), who provide charging services to EV drivers. OCPI facilitates functions like user authorization, remote charge point control, charging session data exchange, and billing through Charge Detail Records (CDRs). This allows EV roaming, so drivers can charge at different networks without multiple accounts. As the EV market grows due to increased adoption and technological advancements, OCPI faces higher demands. This has revealed issues with CDR format consistency, timestamp standardization across regions, transmission of EV-side error codes for troubleshooting, and support for new use cases. These challenges can affect operations and user experience, particularly as the industry starts considering Vehicle-to-Grid (V2G) systems, where EVs supply energy to the grid, and Vehicle-to-Everything (V2X) technologies for broader energy interactions. Using feedback from the ChargeX Diagnostics taskforce discussions, industry 1-on-1 meetings, technical standards, and OCPI’s evolution through versions (e.g., OCPI 2.1.1, 2.2, and 2.2.1), this report identifies these issues and suggests practical recommendations. These aim to improve interoperability, streamline operations, and prepare OCPI for future trends in the EV charging ecosystem.

32 - ENERGY CONSERVATION, CONSUMPTION, AND UTILIZA↗

Regional climate change: consensus, discrepancies, and ways forward

Climate change has emerged across many regions. Some observed regional climate changes, such as amplified Arctic warming and land-sea warming contrasts have been predicted by climate models. However, many other observed regional changes, such as changes in tropical sea surface temperature and monsoon rainfall are not well simulated by climate model ensembles even when taking into account natural internal variability and structural uncertainties in the response of models to anthropogenic radiative forcing. This suggests climate model predictions may not fully reflect what our future will look like. The discrepancies between models and observations are not well understood due to several real and apparent puzzles and limitations such as the “signal-to-noise paradox” and real-world record-shattering extremes falling outside of the possible range predicted by models. Addressing these discrepancies, puzzles and limitations is essential, because understanding and reliably predicting regional climate change is necessary in order to communicate effectively about the underlying drivers of change, provide reliable information to stakeholders, enable societies to adapt, and increase resilience and reduce vulnerability. The challenges of achieving this are greater in the Global South, especially because of the lack of observational data over long time periods and a lack of scientific focus on Global South climate change. To address discrepancies between observations and models, it is important to prioritize resources for understanding regional climate predictions and analyzing where and why models and observations disagree via testing hypotheses of drivers of biases using observations and models. Gaps in understanding can be discovered and filled by exploiting new tools, such as artificial intelligence/machine learning, high-resolution models, new modeling experiments in the model hierarchy, better quantification of forcing, and new observations. Conscious efforts are needed toward creating opportunities that allow regional experts, particularly those from the Global South, to take the lead in regional climate research. This includes co-learning in technical aspects of analyzing simulations and in the physics and dynamics of regional climate change. Finally, improved methods of regional climate communication are needed, which account for the underlying uncertainties, in order to provide reliable and actionable information to stakeholders and the media.

54 ENVIRONMENTAL SCIENCES↗

Direct Acceleration of an Electron Beam with a Radially Polarized Long-Wave Infrared Laser

Direct laser acceleration with radially polarized lasers is an intriguing variant of laser-based particle acceleration that has the potential of offering GeV/cm-level energy while avoiding the instabilities and complex beam dynamics associated with plasma wakefield accelerators. A major limiting factor is the difficulty of generating high-power radially polarized beams. In this paper, we propose the use of CO2-based long-wave infrared (LWIR) lasers as a driver for direct laser acceleration, as the polarization insensitivity of the gain medium allows a radially polarized beam to be amplified. Additionally, the larger waist sizes, Rayleigh lengths, and pulse lengths associated with the long wavelength could improve the injection efficiency of the electron beam. By comparing acceleration simulations using a near-infrared laser and an LWIR laser, we show that the injection efficiency is indeed improved by up to an order of magnitude with the longer wavelength. Furthermore, we show that even sub-TW peak powers with an LWIR laser can provide MeV-level energy gains. Thus, radially polarized LWIR lasers show significant promise as a driver of a direct laser-driven demonstration accelerator.

43 PARTICLE ACCELERATORS↗

What the Flicker is going on here? Temporal Light Modulation in Automotive Lighting

Temporal light modulation (TLM), colloquially known as “flicker,” is once again an issue in almost all lighting applications, due to widespread adoption of LED and OLED sources and their driving electronics. A subset of LED/OLED lighting systems delivers problematic TLM, often in specific types of residential, commercial, outdoor, and vehicular lighting. Dashboard displays, touchscreens, marker lights, taillights, daytime running lights, interior lighting, etc. frequently use PWM circuits to achieve different luminances for different times of day and user visual adaptation levels. The resulting TLM waveforms and viewing conditions can result in distraction and disorientation, nausea, cognitive effects, and serious health consequences in some populations, occurring with or without the driver, passenger, or pedestrian consciously “seeing” the flicker. There are three visual responses to TLM: direct flicker, the stroboscopic effect, and phantom array effect (also called the “beads effect”). Metrics for the first two have limitations in both calculation and application. The phantom array effect has no established visibility measure at all, and this is the effect most associated with vehicular flicker because of the widespread use of PWM. Conventional wisdom from the recent past, especially concerning acceptable driver frequency ranges, needs to be reconsidered and replaced with improved guidelines to protect health and comfort. Four principal TLM waveform characteristics affect TLM visibility: frequency, modulation depth, duty cycle, and waveshape. This paper proposes much higher frequency operation if PWM control cannot be avoided; but it may be possible to modify the four principal waveform characteristics together in order to achieve reduced TLM visibility and improved health and comfort.

flicker, TLM, temporal light modulation, automotiv↗

The IDEA detector concept for FCC-ee

A detector concept, named IDEA, optimized for the physics and running conditions at the FCC-ee is presented. After discussing the expected running conditions and the main physics drivers, a detailed description of the individual sub-detectors is given. These include: a very light tracking system with a powerful vertex detector inside a large drift chamber surrounded by a silicon wrapper, a high resolution dual readout crystal electromagnetic calorimeter, an HTS based superconducting solenoid, a dual readout fiber calorimeter and three layers of muon chambers embedded in the magnet flux return yoke. Some examples of the expected detector performance, based on fast and full simulation, are also given.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Data from: Coupled machine learning-ecosystem ensemble models substantially improve predictions of nitrous oxide (N 2 O) fluxes from US croplands

Nitrous oxide (N₂O) is a potent and persistent greenhouse gas, with rising atmospheric concentrations driven in part by inefficient use of synthetic nitrogen (N) fertilizers in agriculture. Predicting soil N₂O emissions is challenging due to high spatial and temporal variability arising from complex soil biogeochemical processes. Process-based ecosystem models and standalone machine learning (ML) approaches without extensive site-specific calibration often miss high emission episodes. Here, we show how an Ensemble Modeling System (EMS) based on outputs from an ensemble of ecosystem models coupled to an ensemble of ML models can improve predictions and understanding of N2O fluxes from US cropland. Trained and validated on approximately 12,000 N2O chamber measurements at 17 U.S. Midwest sites (six crops, 35 management practices), the EMS accurately predicted daily fluxes of N2O at both training (R² = 0.84, RMSE = 16.4 g N ha⁻¹ d⁻¹) and held-out testing sites (R² = 0.84, RMSE = 6.2 g N ha⁻¹ d⁻¹). Analyses identified six dominant N₂O drivers: soil organic carbon (SOC), NH₄⁺, NO₃⁻, water-filled pore space (WFPS), soil temperature, and biomass production. Wet, warm soils produced large N₂O peaks only with sufficient SOC and mineral N; in low-SOC soils, fluxes remained low. Incorporating these drivers into process-based models might significantly improve their predictive capacity. The EMS demonstrates a strong potential to predict N₂O fluxes at unseen sites, enabling more reliable regional inventories, improved gap-filling where measurements are sparse, and enhanced understanding of mechanisms to advance targeted mitigation strategies in food, feed, and bioenergy crops.

agricultural sciences↗

Disentangling atmospheric, hydrological, and coupling uncertainties in compound flood modeling within a coupled Earth system model

Compound riverine and coastal flooding is usually driven by complex interactions among meteorological, hydrological, and ocean extremes. However, existing efforts to model this phenomenon often do not integrate hydrological processes across atmosphere–land–river–ocean systems, leading to substantial uncertainties that have not been fully examined. To bridge this gap, we leverage the new capabilities of the Energy Exascale Earth System Model (E3SM) that enable a multi-component framework that integrates coastally refined atmospheric, terrestrial, and oceanic components. We evaluate compound uncertainties arising from two-way land–river–ocean coupling in E3SM and track the cascading meteorological and hydrological uncertainties through ensemble simulations over the Delaware River basin and estuary during Hurricane Irene (2011). Our findings highlight the importance of two-way river–ocean coupling to compound flood modeling and demonstrate E3SM's capability in capturing compound flood extent near the coast, with a hit rate over 0.75. Our study shows the growing uncertainties that transition from atmospheric forcings to flood distribution and severity. Furthermore, an analysis based on artificial neural networks is used to assess the roles of hydrological drivers, such as infiltration and soil moisture, in the generation of compound flooding. The response of compound floods to tropical cyclones (TCs) is found to be susceptible to these often overlooked drivers. For instance, the flooded area could increase more than 2-fold (∼2.4) if Hurricane Irene were preceded by an extreme antecedent soil moisture condition (AMC). The results not only support the use of a multi-component framework for interactive flooding processes, but also underscore the necessity of broader definitions of compound flooding that encompass the simultaneous occurrence of intense precipitation, storm surge, and high AMC during TCs.

Feng, Dongyu [Pacific Northwest National Laborator↗

High power pulse systems for surface processing

A high-power pulsed surface processing system includes insulated-gate bipolar transistors (IGBT) to replicate desirable pulse structures with high precision, at low cost, and with high reliability within a single system. The pulsed surface processing system includes a power supply, an anode and a cathode, a dual gate driver supplying power to one or more IGBT gates, and one or more capacitor banks. Pulse formation software controls the timing and duration of electrical pulses to the electrodes. A freewheeling diode protects the system from an abrupt reduction of current in the circuit. The high-power pulsed surface processing system may be used to control versatile and complex pulse structures while with precise control of instantaneous pulse powers, pulse timing, and process control. The inclusion of dual gate drivers also offers the ability for multiple pulsers to be created and “slaved” together for a wide variety of custom processes.

Tian, Hui↗

Operational Experience and Development of a Reliability Model for the ATR Demineralizer System (Slides)

The Advanced Test Reactor (ATR) is a light water reactor with aluminum clad driver fuel. Strict limits are implemented on pH, conductivity, and filterable solids to assure the performance of the driver fuel limit corrosion of the primary coolant system (PCS) pressure boundary components. A bypass demineralizer system is used to maintain PCS coolant within allowable bands for each of the aforementioned variables. Unlike many other reactors, the ATR does not have a filtration system. As such, failure of ion exchange resin in the bypass demineralizer can defeat the purpose of the system and result in high filterable solids in the PCS. Power operations with high filterable solids is prohibited by a technical safety requirement. This paper discusses recent failures of the ATR bypass demineralizer system. The testing and analysis done to deduce the cause of the failures is covered, as well as short term mitigative steps that were taken. To prevent the likelihood of future issues, historical data from the ATR and industry is used to develop a reliability model of the ATR bypass demineralizer system. Evidence of radiolytic decomposition of ion exchange resin was found in the cause investigation. As such, special attention is given to ion exchange resin failure due to high radiation environments. The reliability model is used to develop the ATR testing and maintenance program. Specifically, limits on resin service life are discussed.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗

Enhanced Lighting Signals for Safety and Efficiency - Experiments with Addressable LEDs

For enhanced roadway safety, clear and immediate visual cues are essential for preventing accidents between drivers and pedestrians. At intersections, however, the line of sight to other roadway users may be obstructed by vehicles and infrastructure. Additionally, adverse conditions, including low visibility, poor weather, or inadequate lighting can increase the potential for collisions. Distracted drivers and pedestrians can further exacerbate the risk of accidents, particularly when using a smartphone, rather than focusing on roadway surroundings. These issues demonstrate the need for infrastructure upgrades that enhance visibility and awareness at crosswalks. A potential solution is through enhanced lighting signals integrated into the roadway infrastructure. One such example is the use of addressable LEDs, individually controllable lights that can change color and brightness instantaneously through programmable microcontrollers. They can be installed and integrated into crosswalks to maintain visibility in conditions where pedestrians may be difficult to see, while also offering peripheral cues to pedestrians who may be distracted by their phones or other objects rather than the road. Such a system (as one example) that is integrated into a traffic intersection digital twin that tracks all roadway users accurately, has the potential to enhance visibility of vulnerable road users, and thus enhance safety. This paper examines the potential implementation and feasibility of this technology, as well as the safety benefits it could provide. Laboratory experiments with addressable LEDs reveal the capabilities and challenges of this technology for roadway infrastructure safety. These findings could pave the way for more integrated lighting in infrastructure for vehicles and pedestrians at intersections, merge and diverge locations, and other areas where complex interactions present safety hazards. Such lighting solutions, enabled by modern computation and communications, could enhance safety and efficiency in our transportation system and improve overall mobility.

24 POWER TRANSMISSION AND DISTRIBUTION↗

A Study of Financial Impacts of Pooled Rideshare Based on Assignment Strategies

This study explores the potential profitability of a pooled rideshare service in a simulation-based case study of two US metropolitan regions in the context of two fleet assignment strategies. A new method of obtaining more accurate fares is created to address scalability and accuracy assumptions relevant to pooling choice. Cases for private rideshare fleets, public mobility on demand offerings, and autonomous fleets are explored and analyzed. Two regions of differing types are explored to illustrate the impacts of geo-spatial demand density of profitability, with one region capturing a large urban and suburban environment and the second a less dense more compact small city. Results indicate that the cost of human drivers is prohibitively expensive, and regulation of driver pay extends the issue of financial viability. Despite these shortcomings, a more efficient rideshare assignment strategy is shown to increase profitability by as much as 60%. The smaller, more dense region was illustrated to experience a greater increase in profitability than the larger region when pooling was improved.

Paul, Joseph↗

V1G Frequency Regulation: Algorithm Development, Validation & Analysis at Scale

Researchers at Argonne National Laboratory developed and validated a high-fidelity digital twin of a smart charging (V1G) ecosystem to model the participation of up to 1,000 unique electric vehicles (EVs) in the PJM frequency regulation market. Utilizing a discrete-event framework, the simulation models complex interactions, from dynamic grid signals (updated every 2 seconds) to individual EV charging dynamics. The simulation incorporates multiple EV models created from real-world lab test data. Researchers tested multiple control algorithms to balance the dual objectives of maximizing aggregator’s revenue and driver charging needs. Results demonstrate that aggregated EVs function as a controllable, highly effective grid resource, achieving high PJM Performance Scores (80–90%). Additionally, an optimized, market-aware bidding strategy was identified as key to profitability. The platform was shown to provide drivers with an average charging discount of nearly 50%. The algorithm was further validated in the lab using production EVs and charging stations to compare simulation results with real-world performance.

Manne, Nithin↗

Evaluating the impacts of Variable Message Signs on Airport Curbside Performance Using Microsimulation

Curbs play a vital role in facilitating vehicle access and egress for individuals at airports. Inefficiently allocating this resource hinders airport accessibility and productivity, resulting in congestion, longer travel times, and increased pollution. As airport demand fluctuates throughout the day and grows over time, airports face intensified curbside pressure. Yet, curb management research is significantly less robust at airports than in urban areas. Given the unbalanced nature of airport demand—riders tend to arrive simultaneously at specific entrances at certain hours—Variable Message Sign (VMS) arises as a cost-effective technology to divert vehicles from congested to underutilized curbs. Still, VMS implementation faces a significant challenge. Historically, airports have managed VMS heuristically and by intuition rather than an evidence-based approach. This research investigates the impacts of implementing VMS on curb performance at airports. By considering different driver compliance rates (DCR), we aim to determine when the sign should be turned on and off to diverge traffic to avoid undesired externalities while enhancing curb performance. Using a validated agent-based microsimulation model, VISSIM, we analyzed the Seattle-Tacoma (SeaTac) Airport as a case study. We modeled sixteen VMS management scenarios and a baseline where the message sign is not displayed, diverging vehicles between the departures and arrivals access levels at four different moments (early morning, morning, afternoon, and late night). We quantified the effects of VMS using seven metrics, including curb productivity index (CPI), curb accessibility (CA), queue length, queue duration, delay, vehicle counts, and emissions. The results of each scenario were compared against the baseline using absolute and relative changes and Repeated Measures ANOVA. Overall, VMS improved curb performance and traffic conditions at the airport, reducing emissions by 14.8% to 8.9%. Moreover, significant reductions in queue length (1,150 ft to 100 ft) and duration (15 to 144 minutes) were observed in the sending link under all VMS policies. However, impacts on the receiving link varied based on congestion, with significant increases in queue duration (9.8 to 24 min) when congested but no substantial changes in free flow. Notably, diverging vehicles to congested links resulted in non-significant results, and activating late and deactivating late VMS affected curb productivity (-5.8% to -61.4%), curb accessibility (-16.5% to -25.8%), cumulative counts (-33.4% to -59.4%), and vehicle delay (95.98% to 594.3%). Activating VMS before congestion begins in the sending link and deactivating before a queue forms in the receiving link yield the most significant improvements: 8.1% to 10.1% in CPI, 9.4% to9.6% in CA, -29.3% to -77.9% in total delay, -11.6% to -13.9% in total emissions, and 101% to 103% in cumulative counts. As the analysis was made with a wide range of time periods, access levels, driver compliance rates, and scenarios, we believe our findings can provide valuable insights into how airports should manage VMS. Our work introduces a novel approach to the scientific airport literature, as some of our metrics were previously unexplored. Additionally, we propose a methodology that other airports can adopt to maximize their curb performance.

Gutierrez, Jorge D.↗

Tracking seasonal variability in plant traits from spaceborne PRISMA and NEON AOP across forest types and ecoregions

Plant traits serve as critical indicators of how plants adapt to environmental changes and influence ecosystem functions. While airborne hyperspectral remote sensing effectively maps plant traits through detailed reflectance properties, it is limited by cost and scale, making large-scale and temporal studies challenging. The recently launched spaceborne hyperspectral imager, PRecursore IperSpettrale della Missione Applicativa (PRISMA), offers frequent, large scale and high-fidelity observations on a spatial resolution of 30 m and a revisit time of around 29 days, making it suitable for large-scale seasonal trait mapping. However, their potential remains largely unexplored. This study developed a multi-stage framework by leveraging the PRISMA spaceborne hyperspectral data and National Ecological Observatory Network (NEON) Airborne Observation Platform (AOP) hyperspectral data to investigate the seasonal dynamics of four key plant traits — chlorophyll content, carotenoid content, equivalent water thickness, and nitrogen content — across eleven NEON sites representing diverse forest types and ecoregions in the contiguous U.S. Our results demonstrated that PRISMA hyperspectral data can reliably track seasonal variability in plant traits, achieving overall R 2 values ranging from 0.78 to 0.88 and normalized root mean square error (NRMSE) values ranging from 5.4% to 8.4% for the four traits. Seasonal patterns revealed bell-shaped trajectories for chlorophyll and carotenoids, while equivalent water thickness decreased steadily across most sites, driven by structural changes during leaf maturation and senescence. Nitrogen content exhibited less pronounced seasonal variation but followed expected nutrient resorption patterns. Analysis of environmental drivers showed that seasonal variability is primarily controlled by solar radiation and day length in northern sites, vapor pressure in semi-arid regions, and temperature in mid-southeastern sites. Spatial variability, meanwhile, was primarily driven by soil properties, particularly during the peak growing season. However, the influence of soil variables slightly declines toward the end of the season at several sites, as climatic factors become more prominent. This study highlights the capability of PRISMA, and potentially other similar spaceborne hyperspectral data for large-scale, time-series plant trait mapping and provides valuable insights into the interactions between plant traits and environmental factors. In conclusion, these findings contribute to advancing our understanding of plant functional ecology and improving predictions of ecosystem responses to environmental changes.

Environmental drivers↗

Novel adaptive immune systems in pristine Antarctic soils

Antarctic environments are dominated by microorganisms, which are vulnerable to viral infection. Although several studies have investigated the phylogenetic repertoire of bacteria and viruses in these poly-extreme environments with freezing temperatures, high ultra violet irradiation levels, low moisture availability and hyper-oligotrophy, the evolutionary mechanisms governing microbial immunity remain poorly understood. Using genome-resolved metagenomics, we test the hypothesis that Antarctic poly-extreme high-latitude microbiomes harbour diverse adaptive immune systems. Our analysis reveals the prevalence of prophages in bacterial genomes (Bacteroidota and Verrucomicrobiota), suggesting the significance of lysogenic infection strategies in Antarctic soils. Furthermore, we demonstrate the presence of diverse CRISPR-Cas arrays, including Class 1 arrays (Types I-B, I-C, and I-E), alongside systems exhibiting novel gene architecture among their effector cas genes. Notably, a Class 2 system featuring type V variants lacks CRISPR arrays, encodes Cas1 and Cas2 adaptation module genes. Phylogenetic analysis of Cas12 effector proteins hints at divergent evolutionary histories compared to classified type V effectors and indicates that TnpB is likely the ancestor of Cas12 nucleases. Our findings suggest substantial novelty in Antarctic cas sequences, likely driven by strong selective pressures. These results underscore the role of viral infection as a key evolutionary driver shaping polar microbiomes.

59 BASIC BIOLOGICAL SCIENCES↗

Integration Methods for High-Density Integrated Electric Drives (Final Technical Report)

The project goal was to research, design and fabricate high-power-density, high-performance SiC power electronic modules for motor drive inverters in electric vehicles (EVs) to enable the subsequent motor drive to achieve a power density of 100 kW/l. EVs use electric motors instead of internal combustion engines as the prime mover, and their core components are semiconductor-based power electronic modules. Efficient power electronic modules play a vital role in power conversion systems. The performance of power modules directly affects the energy efficiency and overall performance of electric vehicles. Therefore, it is particularly important to develop power modules with high power density and high electrical performance that will perform reliably under EV environmental conditions. To achieve these goals, advanced electronic packaging technologies are required. This report describes a 5-year effort to integrate key aspects surrounding the basic power devices into the module itself to increase power density. These include sensing and sensing readout circuits, gate driver circuits, and two-sided cooling solutions.

33 ADVANCED PROPULSION SYSTEMS↗