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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.

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At least 91 records · Page 5

Automated Vehicle Multi-Object Tracking at Scale with CAN

Millions of vehicles are on the road with RADAR sensors in use for adaptive cruise control (ACC), and RADAR sen- sors are not tracking all of the objects in the field of view. This work shows a work-in-progress tool to improve track- ing from RADAR and controller area network (CAN) which should be vitally useful for safety of transportation systems and automated vehicle development. The CAN data provides object detections, but there is a lingering data association problem. The contribution of this work in progress is the solution to the data association problem by posing the data association as a minimum cost network flow problem, and doing it at low cost with an eye toward scalable CPS research.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Aviation Mission Profile Performance Evaluation in a High Specific Power Surface Permanent Magnet Machine with Additively Manufactured Coils and Integrated Heat Pipes

The purpose of this paper is to accurately evaluate the performance and overall efficiency of an electrical machine driving a propeller (as a part of a hybrid or electric propulsion system) during the flight mission profile using electromagnetic-thermal simulations. The study focuses on a 250 kW, 5000 rpm, 1.25 kHz, 36/30 slot/pole surface permanent magnet (SPM) machine with additively manufactured (AM) hollow conductors and integrated heat pipes (HP). The machine drive parameters (frequency, and current) are tuned to maximize the efficiency for a given flight cycle, while providing the highest specific power (SP) during takeoff. Afterward using Multiphysics simulations, the transient thermal behavior of the machine is studied and temperature profile for different parts of the machine is extracted. Finally, steady-state temperatures during cruising are estimated and overall efficiency is re-evaluated.

additive manufacturing↗

Next-Cycle Optimal Dilute Combustion Control via Online Learning of Cycle-to-Cycle Variability Using Kernel Density Estimators

Dilute combustion using exhaust gas recirculation (EGR) presents a cost-effective method for increasing the efficiency of spark-ignition (SI) engines. However, the maximum amount of EGR that can be used at a given condition is limited by a rapid increment of cycle-to-cycle variability (CCV). This study describes a methodology to design a model-based stochastic optimal controller to adjust the cycle-to-cycle fuel injection quantity in order to reduce CCV and further extend the dilute limit. Given the complexity and chaotic nature of combustion events, the controller was enhanced with online learning in order to identify the statistical properties of combustion efficiency, which are needed to generate predictions for next-cycle events. This study showed that a kernel density estimator (KDE) can be used to learn the combustion properties in real time and can be incorporated into the feedback policy in order to calculate the optimal control command. Experimental results suggested that the dilute limit can be extended from 18.5% to 21% EGR fraction at an operating condition relevant for highway cruising. Additionally, the proposed controller can achieve a large CCV reduction with less fuel enrichment compared to previous methods, overall contributing to an increase in 0.2% indicated fuel conversion efficiency.

33 ADVANCED PROPULSION SYSTEMS↗

Modifying Network Guided Vehicle for Repeatable EcoCAR ACC Energy Testing

The newest iteration of the Department of Energy (DOE) Advanced Vehicle Technology Competitions is the EcoCAR Mobility Challenge. In this paper, ANL and HORIBA MIRA collaborate to propose and pilot a test method that enables controlled, repeatable track-based energy consumption testing of semi-autonomous features. The testing was performed at MIRA’s proving ground facility in Nuneaton, UK, using their Network Guided Vehicle (NGV) connectivity and automation test platform. The NGV served as a repeatable lead vehicle following prescribed drive traces around two different track circuits while the host vehicle under test, a Honda Civic with full speed range Adaptive Cruise Control, followed behind. Over the course of a two day test, multiple iterations of certification and custom EPA drive traces were performed on track, demonstrating the viability of a two vehicle energy test. Results were analyzed to assess NGV lead vehicle performance in following the prescribed cycle using SAE J2951 standard calculations in an effort to quantify how repeatably and accurately the lead vehicle followed the trace. Host vehicle energy consumption was assessed using both vehicle CAN bus monitoring and an on-board fuel flow meter.

ACC↗

Mutually promoting or constraining? Disentangling the superimposed effect of velocity and illuminance on fish motion in low-velocity flows with a novel metric

Global climate change, species invasion, and human activities such as the construction of hydraulic facilities are contributing to the worldwide degradation of fish stocks. As a pivotal environmental factor that affects fish migration and population distribution, low-velocity flow has not drawn enough attention despite its extensive presence in various ecoregions. Herein, to understand the behavioural profiles of fish in low-velocity flow, we examined the motility and swimming performance of two representative cyprinids, grass carp (GC, Ctenopharyngodon idella) and silver carp (SC, Hypophthalmichthys molitrix), under the combined effect of different flow velocities and illuminance ranges. The two species were exposed to two flow velocities (0.15 and 0.25 m/s) and three illuminance ranges (100.0 – 0.9 lx, 300.0 – 2.5 lx, and 700.0 – 4.9 lx). A novel behavioural metric, composed of light preference, cruising swimming speed, rheotaxis index (RI), swimming stability (SS), and the probability of moving forwards/backwards over a certain distance (PM f -0.1 and PM b -0.1), was developed to depict the motion strategy of fish fully. By investigating the individual distribution of the fish in light gradient, we confirmed the scototaxis of GC and found the oscillating light preference in SC that changed from 84.4 – 10.2 lx to 6.0 – 2.1 lx and disappeared with increasing illuminance. At the given velocities, the RI and SS increased in both species with a faster flow, and SC was more forward-prone and stable than GC. Despite its fluctuating light preference, the higher illuminances heightened the RI and SS in SC; while in GC, higher illuminances inhibited the SS and had no impact on the RI. The results of PM f -0.1 and PM b -0.1 indicated that a higher flow velocity could facilitate temporary upstream swimming in both species, while illuminance could promote the same effect in SC only. Finally, our study proposed possible moving manoeuvres in fine-scale spatio-temporal scenarios such as attraction flow and untraditional passages and provides valuable insights into fish community dynamics, laying the groundwork for alleviating the threat from invasive species and for future fish population recovery.

59 BASIC BIOLOGICAL SCIENCES↗

Dedicated short range communications used as fail-safe in autonomous navigation

Here in this paper, we have analyzed scenarios for leader-follower vehicle convoys that have the potential to be unsafe, hazardous, or even fatal in order to provide insight on dangerous driving conditions for autonomous vehicle platoons. These scenarios were created in a simulation software called Prescan, and are made to reflect the behavior of the vehicle dynamics and sensor characteristics of a real-world vehicle convoy that is currently being tested at the American Center for Mobility (ACM) and sponsored by the Department of Energy (DOE), National Renewable Energy Laboratory (NREL), the U.S. Army Combat Capabilities Development Command - Ground Vehicle Systems Center (U.S. Army CC-DEVCOM) and the Michigan Department of Transportation (MDOT). The follower vehicle in this study is tested under multiple scenarios, equipped with a Dedicated Short Range vehicle-to-vehicle communication system (DSRC), a radar-based adaptive cruise control system (ACC) and a precision global positioning system (GPS).

42 ENGINEERING↗

Genomic surveillance reveals multiple introductions of SARS-CoV-2 into Northern California

The coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has spread globally, with >365,000 cases in California as of 17 July 2020. We investigated the genomic epidemiology of SARS-CoV-2 in Northern California from late January to mid-March 2020, using samples from 36 patients spanning nine counties and the Grand Princess cruise ship. Phylogenetic analyses revealed the cryptic introduction of at least seven different SARS-CoV-2 lineages into California, including epidemic WA1 strains associated with Washington state, with lack of a predominant lineage and limited transmission among communities. Lineages associated with outbreak clusters in two counties were defined by a single base substitution in the viral genome. These findings support contact tracing, social distancing, and travel restrictions to contain the spread of SARS-CoV-2 in California and other states.

59 BASIC BIOLOGICAL SCIENCES↗

WiP Abstract: Edge-Based Privacy of Naturalistic Driving Data Collection

Collecting large driving datasets is important for data-driven transportation research and studied in naturalistic driving [3]. Due to the standard implementation of a Controller Area Network (CAN) bus for a vehicle’s inter-module communication, many off-the-shelf devices can easily transform a vehicle into a rich data collection utility [2]. Vehicles with Adaptive Cruise Control (ACC) are an example of a feature resulting in emergent traffic behavior when scaled [4]. While these utilities were designed with particular data use cases, data may be publicly shared to benefit other researchers through online tools like CyVerse [1]. However, such data should only be shared when any private information is removed. This private information may exist as a set of GPS coordinates, since the start and end points of a trip may designate a driver’s place of residence or work. When considering larger continuously-collected data sets with a focus on naturalistic driving, many drivers are needed to make data collection feasible. Removal of private information becomes much more of a challenge since every driver may uniquely define their geographic privacy. This project aims to build upon the foundation of libpanda [2] by adding features of edge-based data privacy enforcement. In it’s current form, libpanda uses a GPS in conjunction with a CAN interface to record data. Libpanda feature s a set of startup and shutdown scripts to perform automatic data collection and upload. With additional support hardware on a Raspberry Pi, the Pi can maintain power on vehicle shutdown to automatically upload data before shutdown.

Bunting, Matt↗

CFD-Enhanced Calibration of a Multihole Probe for Small Uncrewed Aircraft Systems

A robust calibration method with a 9-hole probe (9HP) for inertial wind vector measurements from a small uncrewed aircraft system (sUAS) is presented. Calibration accuracy is improved by using computational fluid dynamics (CFD) to estimate corrections, such as those for test section blockage, that are generally applied in wind tunnel testing. A method for estimating experimental bias is presented to account for flow variations over the pressure taps as the 9HP is repositioned in the test section. Installation effects from flow over the airframe and upwash produced by the wings are estimated from CFD simulations of the entire airframe at the expected cruise speed. An initial CFD analysis has demonstrated a quantifiable linear relationship between the measured and actual angle of attack as measured from the relative wind frame. In conclusion, the objective of these additional steps is to increase the accuracy of 9HP calibration.

54 ENVIRONMENTAL SCIENCES↗

Revenue-Maximizing Shared Parking and Electric Vehicle Charging Management in Multi-Unit Dwellings

In urban areas, searching for parking and electric vehicle (EV) charging can result in cruising, congestion, and environmental externalities. Recognizing the business opportunity of offering private parking and charging infrastructure access within multi-unit dwellings (MUDs) during daytime, we model a shared parking and EV charging management system. We maximize the revenue of MUD charging hubs in mixed land use, catering to public demand. Our approach accounts for the objectives of the two stakeholders involved: a demand model is fitted on the choices of EV charging users, and the supply model optimizes the allocation of parking and charging requests in an MUD parking lot. A binary integer linear programming model for the allocation of parking and charging spaces with a rolling horizon is integrated with matching rules that handle both parking and charging requests. In our numerical experiments in a neighborhood of Chicago, Illinois, we estimate the performance of the MUD parking and charging system with metrics that include revenue, number of matchings, and utilization rates. At any given time, MUDs with lower prices attract more charging requests, particularly those of longer duration, resulting in higher revenue and greater charging utilization. Dynamic pricing facilitates a more equitable distribution of requests; as MUD parking lots reach capacity and their fees increase, other MUDs become more competitive, attracting additional requests. Comparing our method against first-come-first-served and optimal-solution benchmarks, we demonstrate our model’s effectiveness in dynamically managing mixed parking and charging demand in MUD charging hubs.

electric vehicle, multi-unit dwelling, charging in↗

Development of in-use engine speed/torque heat maps across multiple heavy-duty commercial vehicle vocations

The U.S. Department of Energy (DOE) established the SuperTruck program with the goal of achieving brake thermal efficiency (BTE) greater than or equal to 55% as demonstrated in an operational heavy-duty (HD) diesel engine at a 65-miles-per-hour (mph) cruise point. Beyond the line-haul application, HD engines operate in a wide range of speed and torque conditions that are unlikely to yield the same efficiency under real-world operation. Thereby, the in-use engine heat maps described in this paper are a valuable tool to illustrate whether the engine-efficiency “sweet spot” matches the most frequent operating conditions. In this study, NREL developed engine heat maps to quantify the important operating points for various vocations using our Fleet DNA database of commercial fleet vehicle operations data. These heat maps clearly show that high-frequency operating points vary significantly according to vehicle vocation, while only a few of them match the sweet spot. Beyond the illustration, engine in-use heat maps can also be leveraged to build up reduced-order engine-efficiency models, needed by many rapid powertrain simulations. As case studies, nine reduced-order models – including line-haul truck, transfer truck, transit bus, transit bus with compressed natural gas (CNG) engine, drayage, refuse pickup, local delivery, utility truck, and school bus with CNG engine – using a trust-region reflective algorithm to fit the on-road data extracted based on the engine in-use heat maps.

33 ADVANCED PROPULSION SYSTEMS↗

Practical low-temperature gasoline combustion for very high efficiency off-road, medium- and heavy-duty engines

Low-temperature gasoline combustion (LTGC) with additive-mixing fuel injection (AMFI) is a new combustion strategy that has been demonstrated to deliver 9%–25% better brake thermal efficiency than similar-sized market-leading diesel engines over the operating map. Moreover, the LTGC-AMFI engine shows near-zero smoke, and NOx emissions are 4–100 times lower than those of a diesel, sufficiently low that no aftertreatment, or only passive NOx aftertreatment, would be sufficient (diesel exhaust fluid is not required). LTGC-AMFI combustion is based on kinetically controlled compression ignition of a dilute charge with a variable amount of low-to-moderate fuel stratification. Fast combustion control is provided by adding minute amounts of an ignition-enhancing additive into the fuel each engine cycle to control its reactivity. This strategy was used to operate a medium-duty (MD) LTGC-AMFI engine at loads from idle to 16.3 bar BMEP and speeds from 600 to 2400 rpm with regular E10 gasoline, which covers nearly the entire operating map of a typical MD engine. Turbine-out temperatures were sufficient for an oxidation catalyst to control hydrocarbon and CO emissions. Autonomie simulations over the GEM ARB Transient and the GEM 55 mph Cruise driving cycles for class-6 trucks using this technology showed fuel economies of 8.1 and 11.4 mpg-gasoline-equivalent, respectively, corresponding to 18.6% and 13.4% improvements over a similar-size diesel engine. Engine-out NOx emissions were 0.024 and 0.01 g/bhp-h, respectively, well below current U.S. emission standards. These results show that switching from diesel to LTGC-AMFI engines would greatly reduce greenhouse gas (GHG) emissions for off-road, MD and HD applications, which will continue to rely on combustion engines because electrification is not practical in the foreseeable future. Finally, with their reduced fuel consumption, the lower cost of gasoline compared to diesel fuel, and much lower aftertreatment costs, LTGC-AMFI engines also offer a significantly lower total cost of ownership.

33 ADVANCED PROPULSION SYSTEMS↗

WholeTraveler Anonymized Data Phase 1

Phase 1 of the WholeTraveler Study data collection consisted of an online-only survey. This survey captured data on three categories of observable variation in the population relevant to transportation decisions. First, the survey collected traditional demographic data such as age, gender, income, and education level. Second, it collected data across personality, psychological, and preference categories. This included: 1. The "Big Five" inventory personality traits: openness to new experience, conscientiousness, extroversion, agreeableness, and neuroticism; 2. Risk and time preferences; and 3. Environmental preferences. Third, the survey collected data on historical behavior patterns including: 1. Adoption of (as well as interest in) new technologies or innovations (e.g., smartphones, PEVs, solar panels, adaptive cruise control [ACC]); 2. Car ownership history and current car ownership status; 3. Recent mode use across different time scales (e.g., previous week, previous month, previous year); and 4. Timing of major life events such as starting a family as well as overall lifecycle trajectory patterns. Data from Phase 1 and Phase 2 are linked by a unique respondent identifier. Anonymized versions of the Phase 1 and Phase 2 data are both available on Livewire.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

FleetREDI: Mail Delivery Class 6 Propane Trucks

Capturing real-world data is critical to reducing the barriers to technology advancement for commercial vehicles. FleetREDI’s insights provide detailed duty cycle information and highlight unique aspects of the given dataset. Each insight delivers a quick look at the collected data by summarizing the operation and identifying key findings of the initial analysis. This FleetREDI insight explores propane and diesel Class 6 mail delivery trucks. Propane-powered commercial vehicles can achieve the same duty cycles and match the power, acceleration, and cruising speeds of conventionally fueled vehicles while producing significantly less emissions of tailpipe oxides of nitrogen (NOx). The primary goal of the project was to demonstrate alternative fuel vehicles in a mail transport application and evaluate the viability of propane as a cost-effective alternative to conventional diesel trucks. ![FleetREDI clean delivery trucks](FleetREDI-clean-delivery.jpg)

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

FleetREDI: Mail Delivery Class 6 Propane Trucks

Capturing real-world data is critical to reducing the barriers to technology advancement for commercial vehicles. FleetREDI’s insights provide detailed duty cycle information and highlight unique aspects of the given dataset. Each insight delivers a quick look at the collected data by summarizing the operation and identifying key findings of the initial analysis. This FleetREDI insight explores propane and diesel Class 6 mail delivery trucks. Propane-powered commercial vehicles can achieve the same duty cycles and match the power, acceleration, and cruising speeds of conventionally fueled vehicles while producing significantly less emissions of tailpipe oxides of nitrogen (NOx). The primary goal of the project was to demonstrate alternative fuel vehicles in a mail transport application and evaluate the viability of propane as a cost-effective alternative to conventional diesel trucks. ![FleetREDI clean delivery trucks](FleetREDI-clean-delivery.jpg)

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

FleetREDI: Mail Delivery Class 6 Propane Trucks

Capturing real-world data is critical to reducing the barriers to technology advancement for commercial vehicles. FleetREDI’s insights provide detailed duty cycle information and highlight unique aspects of the given dataset. Each insight delivers a quick look at the collected data by summarizing the operation and identifying key findings of the initial analysis. This FleetREDI insight explores propane and diesel Class 6 mail delivery trucks. Propane-powered commercial vehicles can achieve the same duty cycles and match the power, acceleration, and cruising speeds of conventionally fueled vehicles while producing significantly less emissions of tailpipe oxides of nitrogen (NOx). The primary goal of the project was to demonstrate alternative fuel vehicles in a mail transport application and evaluate the viability of propane as a cost-effective alternative to conventional diesel trucks. ![FleetREDI clean delivery trucks](FleetREDI-clean-delivery.jpg)

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

FleetREDI: Mail Delivery Class 6 Propane Trucks

Capturing real-world data is critical to reducing the barriers to technology advancement for commercial vehicles. FleetREDI’s insights provide detailed duty cycle information and highlight unique aspects of the given dataset. Each insight delivers a quick look at the collected data by summarizing the operation and identifying key findings of the initial analysis. This FleetREDI insight explores propane and diesel Class 6 mail delivery trucks. Propane-powered commercial vehicles can achieve the same duty cycles and match the power, acceleration, and cruising speeds of conventionally fueled vehicles while producing significantly less emissions of tailpipe oxides of nitrogen (NOx). The primary goal of the project was to demonstrate alternative fuel vehicles in a mail transport application and evaluate the viability of propane as a cost-effective alternative to conventional diesel trucks. ![FleetREDI clean delivery trucks](FleetREDI-clean-delivery.jpg)

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

FleetREDI: Mail Delivery Class 6 Propane Trucks

Capturing real-world data is critical to reducing the barriers to technology advancement for commercial vehicles. FleetREDI’s insights provide detailed duty cycle information and highlight unique aspects of the given dataset. Each insight delivers a quick look at the collected data by summarizing the operation and identifying key findings of the initial analysis. This FleetREDI insight explores propane and diesel Class 6 mail delivery trucks. Propane-powered commercial vehicles can achieve the same duty cycles and match the power, acceleration, and cruising speeds of conventionally fueled vehicles while producing significantly less emissions of tailpipe oxides of nitrogen (NOx). The primary goal of the project was to demonstrate alternative fuel vehicles in a mail transport application and evaluate the viability of propane as a cost-effective alternative to conventional diesel trucks. ![FleetREDI clean delivery trucks](FleetREDI-clean-delivery.jpg)

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗