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A Dual Power Split Electronic Continuously Variable Transmission (DPS-ECVT) with an input-split, output coupled, split-power-path configuration is proposed for improving overall system efficiency and range for electric vehicles. By modulating the power split ratio between the mechanical (planetary gear meshes) and electrical (Motor Generator Units) driveline components, a continuous range of gear ratios operating at higher efficiency is obtained. The proposed concept leverages two power-split units that lead to significantly reduced power flow through the electrical drivelines (compared with single speed EV transmissions as well as single power-split E-CVTs) while providing the same overall ratio spread for transmission operation.

Advanced Driver Assistance Systems (ADAS) like Lane Departure Warning (LDW) and Lane Centering Assistance (LCA) have experienced low customer acceptance and market penetration despite the technology being in active development for several years now. This trend is attributed to the inability of many of the perception systems to consistently detect lane markings and localize the vehicle on roads with poor lane markings, changing weather conditions, and occlusions. Currently, no standards or benchmarks are available to evaluate the quality of either the lane markings or the perception algorithms. This work seeks to establish a reference framework that can be used by transportation agencies to evaluate the effect of pavement markings on ADAS functions. Previous works have looked at these problems using on-road pavement markings. However, environmental factors like sun glare, shadows, and road illumination, affect Lane Detection (LD) performance with changing roads and driving directions.

Object detection and tracking is a central aspect of perception for autonomous vehicles. While there has been significant development in this field in recent years, many perception algorithms still struggle to provide reliable information in challenging weather conditions which include night-time, direct sunlight, glare, fog, etc. To achieve full autonomy, there is a need for a robust perception system capable of handling such challenging conditions. In this paper, we attempt to bridge this gap by proposing an algorithm that combines the strength of automotive radars and infra-red thermal cameras. We show that these sensors complement each other well and provide reliable data in poor visibility conditions. We demonstrate the advantages of a thermal camera over a visible-range camera in these situations and employ YOLOv3 for object detection.

This paper presents calculations of engine flows by using the Partially-Averaged Navier Stokes (PANS) method (Girimaji [1]; [2]). The PANS is a scale-resolving turbulence computational approach designed to resolve large scale fluctuations and model the remainder with appropriate closures. Depending upon the prescribed cut-off length (filter width) the method adjusts seamlessly from the Reynolds-Averaged Navier-Stokes (RANS) to the Direct Numerical Solution (DNS) of the Navier-Stokes equations. The PANS method was successfully used for many applications but mainly on static geometries, e.g. Basara et al. [3]; [4]. This is due to the calculation of the cut-off control parameter which requires that the resolved kinetic energy is known and this is usually obtained by suitably averaging of the resolved field. Such averaging process is expensive and impractical for engines as it would require averaging per cycles.

NASA and the FAA conducted two flight campaigns to quantify onboard weather radar measurements with in-situ measurements of high concentrations of ice crystals found in deep convective storms. The ultimate goal of this research was to improve the understanding of high ice water content (HIWC) and develop onboard weather radar processing techniques to detect regions of HIWC ahead of an aircraft to enable tactical avoidance of the potentially hazardous conditions. Both HIWC RADAR campaigns utilized the NASA DC-8 Airborne Science Laboratory equipped with a Honeywell RDR-4000 weather radar and in-situ microphysical instruments to characterize the ice crystal clouds. The purpose of this paper is to summarize how these campaigns were conducted and highlight key results. The first campaign was conducted in August 2015 with a base of operations in Ft. Lauderdale, Florida.

This paper discusses different computer vision techniques investigated by the authors for identifying Emergency Vehicles (EV). Two independent EV identification frameworks were investigated: (1) A one-stage framework where an object detection algorithm is trained on a custom dataset to detect EVs, (2) A two-stage framework where an object classification algorithm is implemented in series with an object detection pipeline to classify vehicles into EVs and non-EVs. A comparative study is conducted for different multi-spectral feature vectors of the image, against several classification models implemented in framework 2. Additionally, a user-defined feature vector is defined and its performance is compared against the other feature vectors. Classification outputs from each of the frameworks are compared to the ground truth, and results are quantitatively listed to conclude upon the ideal decision rule.

The dimensions of an automobile seat are important factors affecting a driver’s seating comfort, fit, and satisfaction. In this regard, seat engineers put forth tremendous efforts to evaluate the dimensions of a product seat until the dimensions are consistent with the design reference in a computer aided design (CAD). However, the existing evaluation process is heavily reliant on seat engineers’ manual tasks which are highly repetitive, labor intensive, and time-demanding tasks. The objective of this study is to develop an automated system that can efficiently and accurately evaluate seat products by comparing estimated seat dimensions from a CAD model or a 3D scan model. By using the developed system, the evaluation time for comparing 18 seat dimensions on CAD and scan models has been substantially reduced to less than one minute, which is 99% time saving compared to two hours in the manual process.

This article presents strategies for evaluating the mean, variance, and failure probability of a response variable given measurements subject to both epistemic and aleatory uncertainties. We focus on a case in which standard sensor calibration techniques cannot be used to eliminate measurement error since the uncertainties affecting the metrology system depend upon the measurement itself (e.g., the sensor bias is not constant and the measurement noise is colored). To this end, we first characterize all possible realizations of the true response that might have led to each of such measurements. This process yields a surrogate of the data for the unobservable true response taking the form of a random variable. Each of these variables, called a Random Datum Model (RDM), is manufactured according to a measurement and to the underlying structure of the uncertainty.

This paper investigates the effect of the cetane number (CN) of a diesel fuel on the energy balance between a light duty (1.9L) and medium duty (4.5L) diesel engine. The two engines have a similar stroke to bore (S/B) ratio, and all other control parameters including: geometric compression ratio, cylinder number, stroke, and combustion chamber, have been kept the same, meaning that only the displacement changes between the engine platforms. Two Coordinating Research Council (CRC) diesel fuels for advanced combustion engines (FACE) were studied. The two fuels were selected to have a similar distillation profile and aromatic content, but varying CN. The effects on the energy balance of the engines were considered at two operating conditions; a “low load” condition of 1500 rev/min (RPM) and nominally 1.88 bar brake mean effective pressure (BMEP), and a “medium load” condition of 1500 RPM and 5.65 BMEP.

A comprehensive analysis of engine performance and fuel consumption was carried out to study Low Heat Rejection (LHR) concepts in the conventional light-duty diesel engine. From most previous studies on LHR diesel engines, thermal-barrier coatings (TBCs) have been recognized as a conventional way of insulating engine parts; while for the cases studied in this paper, the LHR concept is realized by altering engine coolant temperature (ECT). This paper presents engine simulation of a multi-cylinder, four-stroke, 1.9L diesel engine operating at 1500 rpm with five cases having different ECTs. The simulated results have been validated against experimental data. Calibration strategy for the engine simulation model is detailed in a systematic methodology for a better understanding of this simulation-development process. The calibrated model predicts the performance and fuel consumption within tolerated uncertainties.

It is important for engineering firms to be able to develop forecasts of recommended courses of action based on available information. In particular, engineering firms must be able to assess the benefit of performing information-gathering actions. For example, an automobile manufacturer may use a computer simulation of a hydraulic motor and pump in the design of a new vehicle. The model may contain random variables that can be more accurately determined through expensive information-gathering actions, e.g., physical experiments, surveys, etc. To decide whether to perform these information-gathering actions, the automobile manufacturer must be able to quantify the expected value to the firm of conducting them. However, the cost of computing the expected value of information (through optimization, Monte Carlo sampling, etc.) grows exponentially with the amount of information that is to be gathered and can often exceed the cost of actually gathering the information.

The objective of this study is to optimize the injector power drive system for improved fuel injection quantity and timing control. The power drive system was optimized for improved injection repeatability under different operating conditions such as fuel supply pressures. A coupled simulation of injector electromagnetic, pintle (needle) rigid body motion and computational fluid dynamics (CFD) model was employed to generate the optimal values of the 1st stage current, the 1st stage on-time and the 2nd stage current. The simulation results were validated against the experimental data measured with a photo detector measurement system.

Research on dual-fuel engine systems is regaining interest as advances in combustion reveal enabling features for attaining high efficiencies. Although this movement is manifested by development of advanced modes of combustion (e.g., reactivity controlled compression ignition combustion, or RCCI), the possibility of gasoline / diesel conventional combustion exists, which is characterized by premixed gasoline and direct-injected diesel fuel at conventional diesel injection timing. This study evaluates the effects of operating parameter on fuel conversion efficiency for gasoline / diesel conventional combustion in a medium duty diesel engine. Through adjustment of gasoline ratio (mass basis), injection timing and rail pressure (with adjustments to diesel fuel quantity to hold torque constant), the combustion, performance and emissions are studied.

Future electronics and photonics systems, weapons systems, and environmental control systems in aircraft will require advanced thermal management technology to control the temperature of critical components. Two-phase Thermal Management Systems (TMS) are attractive because they are compact, lightweight, and efficient. However, maintaining stable and reliable cooling in a two-phase flow system presents unique design challenges, particularly for systems with parallel evaporators during thermal transients. Furthermore, preventing ingress of liquid into a vapor compressor during variable-gravity operation is critical for long-term reliability and life. To enable stable and reliable cooling, a highly stable two-phase system is being developed that can effectively suppress flow instability in a system with parallel evaporators. Flow stability is achieved by ensuring that only single-phase liquid enters the evaporators.

A major decision to make in design projects is the selection of the best technology to provide some needed system functionality. In making this decision, the designer must consider the range of technologies available and the performance of each. During the useful life of the product, the technologies composing the product evolve as research and development efforts continue. The performance evolution rate of one technology may be such that even though it is not initially a preferably technology, it becomes a superior technology after a few years. Quantifying the evolution of these technologies complicates the technology selection decision. The selection of energy storage technology in the design of an electric car is one example of a difficult decision involving evolving technologies.

Tradeoff studies are a common part of engineering practice. Designers conduct tradeoff studies in order to improve their understanding of how various design considerations relate to one another and to make decisions. Generally a tradeoff study involves a systematic multi-criteria evaluation of various alternatives for a particular system or subsystem. After evaluating these alternatives, designers eliminate those that perform poorly under the given criteria and explore more carefully those that remain. One limitation of current practice is that designers cannot combine the results of preexisting tradeoff studies under uncertainty. For deterministic problems, designers can use the Pareto dominance criterion to eliminate inferior designs. Prior work also exists on composing tradeoff studies performed under certainty using an extension of this criterion, called parameterized Pareto dominance.

As emission standards become more stringent, many studies have been carried out to understand and reduce the emissions from diesel combustion engines, among which nitric oxide (NO) emissions and soot are known to have the trade-off relation during combustion processes. One aspect of this trade-off is manifested by the role radiation heat transfer plays on post-flame gas temperature, thus affecting NO formation. For example, a decrease in in-cylinder soot decreases radiation heat transfer causing an increase in post-flame gas temperature and partially contributing to the corresponding soot-NO relationship with an increase in NO formation. This topic has re-emerged with the increased use of biodiesel; a potential explanation for the so-called "biodiesel NOx penalty" is biodiesel's inherently reduced in-cylinder soot.

Commercial aviation relies almost entirely on subsonic fixed wing aircraft to constantly move people and goods from one place to another across the globe. While air travel is an effective means of transportation providing an unmatched combination of speed and range, future subsonic aircraft must improve substantially to meet efficiency and environmental targets. The NASA Fundamental Aeronautics Subsonic Fixed Wing (SFW) Project addresses the comprehensive challenge of enabling revolutionary energy-efficiency improvements in subsonic transport aircraft combined with dramatic reductions in harmful emissions and perceived noise to facilitate sustained growth of the air transportation system. Advanced technologies, and the development of unconventional aircraft systems, offer the potential to achieve these improvements.

Cloud properties retrieved from satellite data are used to diagnose aircraft icing threat in single layer and multilayered ice-over-liquid clouds. The algorithms are being applied in real time to the Geostationary Operational Environmental Satellite (GOES) data over the CONUS with multilayer data available over the eastern CONUS. METEOSAT data are also used to retrieve icing conditions over western Europe. The icing algorithm's methodology and validation are discussed along with future enhancements and plans. The icing risk product is available in image and digital formats on NASA Langley ‘s Cloud and Radiation Products web site, http://www-angler.larc.nasa.gov.

An experimental research effort was begun to develop a database of airplane aerodynamic characteristics with simulated ice accretion over a large range of incidence and sideslip angles. Wind-tunnel testing was performed at the NASA Langley 12-ft Low-Speed Wind Tunnel using a 3.5% scale model of the NASA Langley Generic Transport Model. Aerodynamic data were acquired from a six-component force and moment balance in static-model sweeps from α = -5 to 85 deg. and β = -45 to 45 deg. at a Reynolds number of 0.24x10⁶ and Mach number of 0.06. The 3.5% scale GTM was tested in both the clean configuration and with full-span artificial ice shapes attached to the leading edges of the wing, horizontal and vertical tail. Aerodynamic results for the clean airplane configuration compared favorably with similar experiments carried out on a 5.5% scale GTM.