Often, when assessing the distraction or ease of use of an in-vehicle task (such as entering a destination using the street address method), the first question is “How long does the task take on average?” Engineers routinely resolve this question using computational models. For in-vehicle tasks, “how long” is estimated by summing times for the included task elements (e.g., decide what to do, press a button) from SAE Recommended Practice J2365 or now using new static (while parked) data presented here. Times for the occlusion conditions in J2365 and the NHTSA Distraction Guidelines can be determined using static data and Pettitt’s Method or Purucker’s Method. These first approximations are reasonable and can be determined quickly. The next question usually is “How likely is it that the task will exceed some limit?”
With the development of vehicles equipped with automated driving systems, the need for systematic evaluation of AV performance has grown increasingly imperative. According to ISO 34502, one of the safety test objectives is to learn the minimum performance levels required for diverse scenarios. To address this need, this paper combines two essential methodologies - scenario-based testing procedures and scoring systems - to systematically evaluate the behavioral competence of AVs. In this study, we conduct comprehensive testing across diverse scenarios within a simulator environment following Mcity AV Driver Licensing Test procedure. These scenarios span several common real-world driving situations, including BV Cut-in, BV Lane Departure into VUT Path from Opposite Direction, BV Left Turn Across VUT Path, and BV Right Turn into VUT Path scenarios.
As a part of NASA’s efforts in space, options are being examined for an Artemis moon base project to be deployed. This project requires a system of interconnected, but separate, DC microgrids for habitation, mining, and fuel processing. This in-place use of power resources is called in-situ resource utilization (ISRU). These microgrids are to be separated by 9-12 km and each contains a photovoltaic (PV) source, energy storage systems (ESS), and a variety of loads, separated by level of criticality in operation. The separate microgrids need to be able to transfer power between themselves in cases where there are generation shortfall, faults, or other failures in order to keep more critical loads running and ensure safety of personnel and the success of mission goals. In this work, a 2 grid microgrid system is analyzed involving a habitation unit and a mining unit separated by a tie line.
Motor vehicle crashes involving child Vulnerable Road Users (VRUs) remain a critical public health concern in the United States. While previous studies successfully utilized the crash scenario typology to examine traffic crashes, these studies focus on all types of motor vehicle crashes thus the method might not apply to VRU crashes. Therefore, to better understand the context and causes of child VRU crashes on the U.S. road, this paper proposes a multi-step framework to define crash scenario typology based on the Fatality Analysis Reporting System (FARS) and the Crash Report Sampling System (CRSS). A comprehensive examination of the data elements in FARS and CRSS was first conducted to determine elements that could facilitate crash scenario identification from a systematic perspective. A follow-up context description depicts the typical behavioral, environmental, and vehicular conditions associated with an identified crash scenario.
Making manned and remotely-controlled wheeled and tracked vehicles easier to drive, especially off-road, is of great interest to the U.S. Army. If vehicles are easier to drive (especially closed hatch) or if they are driven autonomously, then drivers could perform additional tasks (e.g., operating weapons or communication systems), leading to reduced crew sizes. Further, poorly driven vehicles are more likely to get stuck, roll over, or encounter mines or improvised explosive devices, whereby the vehicle can no longer perform its mission and crew member safety is jeopardized. HMI technology and systems to support human drivers (e.g., autonomous driving systems, in-vehicle monitors or head-mounted displays, various control devices (including game controllers), navigation and route-planning systems) need to be evaluated, which traditionally occurs in mission-specific (and incomparable) evaluations.
Nitric Oxide (NO) can significantly influence the autoignition reactivity and this can affect knock limits in conventional stoichiometric SI engines. Previous studies also revealed that the role of NO changes with fuel type. Fuels with high RON (Research Octane Number) and high Octane Sensitivity (S = RON - MON (Motor Octane Number)) exhibited monotonically retarding knock-limited combustion phasing (KL-CA50) with increasing NO. In contrast, for a high-RON, low-S fuel, the addition of NO initially resulted in a strongly retarded KL-CA50 but beyond the certain amount of NO, KL-CA50 advanced again. The current study focuses on same high-RON, low-S Alkylate fuel to better understand the mechanisms responsible for the reversal in the effect of NO on KL-CA50 beyond a certain amount of NO.
Mobility in the automotive and transportation sectors has been experiencing a period of unprecedented evolution. A growing need for efficient, clean and safe mobility has increased momentum toward sustainable technologies in these sectors. Toward this end, battery electric vehicles have drawn keen interest and their market share is expected to grow significantly in the coming years, especially in light-duty applications such as passenger cars. Although the battery electric vehicles feature high performance and zero tailpipe emission characteristics, economic and technical issues such as battery cost, driving range, recharging time and infrastructure remain main hurdles that need to be fully addressed. In particular, the low power density of the battery limits its broad adoption in heavy-duty applications such as class 8 semi-trailer trucks due to the required size and weight of the battery and electric motor.
With the evolution of telemetry technology in vehicles, Advanced Automatic Collision Notification (AACN), which detects occupants at risk of serious injury in the event of a crash and triages them to the trauma center quickly, may greatly improve their treatment. An Injury Severity Prediction (ISP) algorithm for AACN was developed using a logistic regression model to predict the probability of sustaining an Injury Severity Score (ISS) 15+ injury. National Automotive Sampling System Crashworthiness Data System (NASS-CDS: 1999-2015) and model year 2000 or later were filtered for new case selection criteria, based on vehicle body type, to match Subaru vehicle category. This new proposed algorithm uses crash direction, change in velocity, multiple impacts, seat belt use, vehicle type, presence of any older occupant, and presence of any female occupant.
Nyquist plots are a classical means to visualize a complex vibration frequency response function. By graphing the real and imaginary parts of the response, the dynamic behavior in the vicinity of resonances is emphasized. This allows insight into how modes are coupling, and also provides a means to separate the modes. Mathematical models such as Nyquist analysis are often embedded in frequency analysis hardware. While this speeds data collection, it also removes this visually intuitive tool from the engineer’s consciousness. The behavior of a single degree of freedom system will be shown to be well described by a circle on its Nyquist plot. This observation allows simple visual examination of the response of a continuous system, and the determination of quantities such as modal natural frequencies, damping factors, and modes shapes. Vibration test data from an auto rickshaw chassis are used as an example application.
This work is a comprehensive technical review of existing literature and a synthesis of current understanding of the governing physics behind the interaction of multiple fuel injections, ignition, and combustion behavior of multiple-injections in diesel engines. Multiple-injection is a widely adopted operating strategy applied in modern compression-ignition engines, which involves various combinations of small pre-injections and post-injections of fuel before and after the main injection and splitting the main injection into multiple smaller injections. This strategy has been conclusively shown to improve fuel economy in diesel engines while achieving simultaneous NOX, soot, and combustion noise reduction - in addition to a reduction in the emissions of unburned hydrocarbons (UHC) and CO by preventing fuel wetting and flame quenching at the piston wall.
The effect of an annular, piston bowl-rim cavity on in-cylinder and engine-out soot emissions is measured in a heavy-duty, optically accessible, single-cylinder diesel engine using in-cylinder soot diagnostics and exhaust smoke emission measurements. The baseline piston configuration consists of a right-cylindrical bowl, while the cavity-piston configuration features an additional annular cavity that is located below the piston bowl-rim and connected to the main-combustion chamber through a thin annular passage, accounting for a 3% increase in the clearance volume, resulting in a reduction in geometric compression ratio (CR) from 11.22 to 10.91. Experiments using the cavity-piston configuration showed a significant reduction of engine-out smoke ranging from 20-60% over a range of engine loads.
Appropriate spray modeling in multidimensional simulations of diesel engines is well known to affect the overall accuracy of the results. More and more accurate models are being developed to deal with drop dynamics, breakup, collisions, and vaporization/multiphase processes; the latter ones being the most computationally demanding. In fact, in parallel calculations, the droplets occupy a physical region of the in-cylinder domain, which is generally very different than the topology-driven finite-volume mesh decomposition. This makes the CPU decomposition of the spray cloud severely uneven when many CPUs are employed, yielding poor parallel performance of the spray computation. Furthermore, mesh-independent models such as collision calculations require checking of each possible droplet pair, which leads to a practically intractable O(np2/2) computational cost, np being the total number of droplets in the spray cloud, and additional overhead for parallel communications.
Tanker trucks are commonly used for transporting liquid material including chemical and petroleum products. On the one hand, tanker trucks are susceptible to rollover accidents due to the high center of gravity when they are loaded and due to the liquid sloshing effects when the tank is partially filled. On the other hand, tanker truck rollover accidents are among the most dangerous vehicle crashes, frequently resulting in serious to fatal driver injuries and significant property damage, because the liquid cargo is often hazardous and flammable. Therefore, effective schemes for tanker truck rollover avoidance are highly desirable and can bring a considerable amount of societal benefit. Yet, the development of such schemes is challenging, as tanker trucks can operate in various environments and be affected by manufacturing variability, aging, degradation, etc. This paper considers the use of Learning Reference Governor (LRG) for tanker truck rollover avoidance.
Knee airbags (KABs) are one countermeasure in newer vehicles that could influence lower extremity (LEX) injury, the most frequently injured body region in frontal crashes. To determine the effect of KABs on LEX injury for drivers in frontal crashes, the analysis examined moderate or greater LEX injury (AIS 2+) in two datasets. Logistic regression considered six main effect factors (KAB deployment, BMI, age, sex, belt status, driver compartment intrusion). Eighty-five cases with KAB deployment from the Crash Injury Research and Engineering Network (CIREN) database were supplemented with 8 cases from the International Center for Automotive Medicine (ICAM) database and compared to 289 CIREN non-KAB cases. All cases evaluated drivers in frontal impacts (11 to 1 o’clock Principal Direction of Force) with known belt use in 2004 and newer model year vehicles. Results of the CIREN/ICAM dataset were compared to analysis of a similar dataset from NASS-CDS (5441 total cases, 418 KAB-deployed).
High-pressure gasoline injection can improve combustion efficiency and lower engine-out emissions; however, the spray characteristics of high-pressure gasoline (>500 bar) are not well known. Effects of different injector nozzle geometry on high-pressure gasoline sprays were studied using a constant volume chamber. Five nozzles with controlled internal flow features including differences in nozzle inlet rounding, conicity, and outlet diameter were investigated. Reference grade gasoline was injected at fuel pressures of 300, 600, 900, 1200, and 1500 bar. The chamber pressure was varied using nitrogen at ambient temperature and pressures of 1, 5, 10, and 20 bar. Spray development was recorded using diffuse backlit shadowgraph imaging methods.
Innovations in mobility are built upon a management of complex interactions between sub-systems and components. A need for CAE tools that are capable of system simulations is well recognized, as evidenced by a growing number of commercial packages. However impressive they are, the predictability of such simulations still rests on the representation of the base components. Among them, a wet clutch actuator continues to play a critical role in the next generation propulsion systems. It converts hydraulic pressure to mechanical force to control torque transmitted through a clutch pack. The actuator is typically modeled as a hydraulic piston opposed by a mechanical spring. Because the piston slides over a seal, some models have a framework to account for seal friction. However, there are few contributions to the literature that describe the effects of seals on clutch actuator behaviors.
Understanding and prediction of flash-boiling spray behavior in gasoline direct-injection (GDI) engines remains a challenge. In this study, computational fluid dynamics (CFD) simulations using the homogeneous relaxation model (HRM) for not only internal nozzle flow but also external spray were evaluated using CONVERGE software and compared to experimental data. High-speed extinction imaging experiments were carried out in a real-size axial-hole transparent nozzle installed at the tip of machined GDI injector fueled with n-pentane under various ambient pressure conditions (Pa/Ps = 0.07 - 1.39). The width of the spray during injection was assessed by means of projected liquid volume, but the structure and timing for boil-off of liquid within the sac of the injector were also assessed after the end of injection, including cases with different designed sac volumes.
An accurate prediction of internal nozzle flow in fuel injector offers the potential to improve predictions of spray computational fluid dynamics (CFD) in an engine, providing a coupled internal-external calculation or by defining better rate of injection (ROI) profile and spray angle information for Lagrangian parcel computations. Previous research has addressed experiments and computations in transparent nozzles, but less is known about realistic multi-hole diesel injectors compared to single axial-hole fuel injectors. In this study, the transient injector opening and closing is characterized using a transparent multi-hole diesel injector, and compared to that of a single axial hole nozzle (ECN Spray D shape). A real-size five-hole acrylic transparent nozzle was mounted in a high-pressure, constant-flow chamber. Internal nozzle phenomena such as cavitation and gas exchange were visualized by high-speed long-distance microscopy.
This SAE EDGE Research Report explores the many legal issues raised by the advent of automated vehicles. While promised to bring major changes to our lives, there are significant legal challenges that have to be overcome before they can see widespread use. A century’s worth of law and regulation were written with only human drivers in mind, meaning they have to be amended before machines can take the wheel. Everything from key federal safety regulations down to local parking laws will have to shift in the face of AVs. This report undertakes an examination of the AV laws of Nevada, California, Michigan, and Arizona, along with two failed federal AV bills, to better understand how lawmakers have approached the technology. States have traditionally regulated a great deal of what happens on the road, but does that still make sense in a world with AVs? Would the nascent AV industry be able to survive in a world with fifty potential sets of rules?