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Abstract Truck platooning comprises a number of trucks equipped with automated lateral and longitudinal vehicle control technology, which allows them to move in tight formation with short following distances. This study is an initial step toward developing an understanding of the occupant injury risks associated with the multiple sequential impacts between truck platoons and roadside safety barriers, regardless of whether the crash is associated with a malfunction of automated control or human operation. Full-scale crash impacts of a tractor-trailer platoon into a concrete bridge guardrail were simulated for a specific Test Level condition according to the Manual for Assessing Safety Hardware (MASH) standards. The model of the bridge barrier was developed based on its drawings, and material properties were assigned according to literature data.

Abstract Carbon fiber reinforced plastic (CFRP) has been used in automobiles as well as airplanes. Because of its light weight and high strength, CFRP is a good choice for making vehicle bodies lighter, which would improve fuel economy. Conventional metal bodies provide a convenient body return for electric wiring and offer good shielding against electromagnetic fields. Although CFRP is a conductor, its conductivity is much lower than that of metals. Therefore, CFRP bodies are usually not useful for electric wiring. In thunderstorms, an automotive body is considered to be a Faraday cage that protects the vehicle’s occupants from the potential harms of lightning. Before CFRP becomes widely applied to automotive bodies, its electric and electromagnetic properties need to be investigated in order to determine whether it also works as a Faraday cage against lightning. In this article, CFRP and metal body vehicles were tested under artificial lightning.

Abstract In recent years, several buses have ignited in some cities in China, causing numerous deaths and significant property damage. However, few research studies have been conducted to deal with such accidents. Therefore, in this work, a linear-shaped charge jet with rectangular cross sections was used to hew out evacuation routes for burning buses, and the parameter design for the shaped charge jet was improved according to asymmetry limitations and human tolerance. A numerical finite element simulation model of the behavior of a jet penetrating the jambs was established using ANSYS/LS-DYNA software. The asymmetrical characteristics of an arc segment in the structure of a rectangular-shaped charge were analyzed, in addition to the influence on the deviations of the jet penetration capacity and blast injuries to occupants caused by the side effects of detonation.

Abstract This study aims to take the first step in bridging the gap between vehicle dynamics systems and autonomous control strategies research. More specifically, a nested method is employed to evaluate the collision avoidance ability of autonomous vehicles in the primary design stage theoretically based on both dynamics and control parameters. An integrated model is derived from a half car mathematical model in the lateral direction, consisting of two degrees of freedom, lateral deviation and yaw angle, with a traction mathematical model in the longitudinal direction, consisting of two degrees of freedom, the longitudinal velocity and rolling velocity of the wheel. The integrated model uses a mathematical power train model to generate the torque on the wheel and connects the two systems via the magic formula tyre model to represent the tyre non-linearity during augmented longitudinal and lateral dynamic attitudes.

Abstract Gasoline particulate filters (GPFs) are important aftertreatment components that enable gasoline direct injection (GDI) engines to meet European Union (EU) 6 and China 6 particulate number emissions regulations for nonvolatile particles greater than 23 nm in diameter. GPFs are rapidly becoming an integral part of the modern GDI aftertreatment system. The Active Exhaust Tuning (EXTUN) Valve is a butterfly valve placed in the tailpipe of an exhaust system that can be electronically positioned to control exhaust noise levels (decibels) under various vehicle operating conditions. This device is positioned downstream of the GPF, and variations in the tuning valve position can impact exhaust backpressures, making it difficult to monitor soot/ash accumulation or detect damage/removal of the GPF substrate. The purpose of this work is to present a unique example of subsystem control and diagnostic architecture for an exhaust system combining GPF and EXTUN.

Abstract Obstacle avoidance is an important function in self-driving vehicle control. When the vehicle move from any arbitrary start positions to any target positions in environment, a proper path must avoid both static obstacles and moving obstacles of arbitrary shape. There are many possible scenarios, manually tackling all possible cases will likely yield a too simplistic policy. In this paper reinforcement learning is applied to the problem to form effective strategies. There are two major challenges that make self-driving vehicle different from other robotic tasks. Firstly, in order to control the vehicle precisely, the action space must be continuous which can’t be dealt with by traditional Q-learning. Secondly, self-driving vehicle must satisfy various constraints including vehicle dynamics constraints and traffic rules constraints. Three contributions are made in this paper.

Abstract Potential collisions with oncoming traffic while turning left belong to the most safety-critical situations accounting for ~25% of all intersection crossing path crashes. A Left Turn Assist (LTA) was developed to reduce the number of crashes. Crucial for the effectiveness of the system is the design of the human-machine interface (HMI), i.e. defining how the system uses the calculated crash probability in the communication with the driver. A driving simulator study was conducted evaluating a warning strategy for two use cases: firstly, the driver comes to a stop before turning (STOP), and secondly, the driver moves on without stopping (MOVE). Forty drivers drove through three STOP and two MOVE scenarios. For the STOP scenarios, the study compared the effectiveness of an audio-visual warning with an additional brake intervention and a baseline. For the MOVE scenarios, the study analyzed the effectiveness of the audio-visual warning against a baseline.

Abstract To reduce fuel consumption and carbon dioxide (CO2) emissions from mobile air conditioning (A/C) systems, “U.S. Light-Duty Vehicle Greenhouse Gas Emissions and Corporate Average Fuel Economy Standards” identified solar/thermal technologies such as solar control glazings, solar reflective paint, and active and passive cabin ventilation in an off-cycle credit menu. National Renewable Energy Laboratory (NREL) researchers developed a sophisticated analysis process to calculate U.S. light-duty A/C fuel use that was used to assess the impact of these technologies, leveraging thermal and vehicle simulation analysis tools developed under previous U.S. Department of Energy projects. Representative U.S. light-duty driving behaviors and weighting factors including time-of-day of travel, trip duration, and time between trips were characterized and integrated into the analysis.

Abstract ISO 26262 needs to be considered when developing safety-relevant E/E systems within the automotive industry. One part of the development process according to ISO 26262 is the derivation of the safety requirements for component functions. Here, one attribute of the safety requirements is the Automotive Safety Integrity Level (ASIL). The ASIL at a component level can be determined using ASIL allocation and decomposition. Considering complex systems such as vehicle electrical systems, countless possibilities can be identified for how the ASILs at a component level can be assigned in line with safety goals. In terms of efficiency, manual assignment is not expedient. Therefore, an algorithm for automated assignment of the ASILs will be introduced which considers constraints based on a fault tree analysis. The function of the approach will be demonstrated using the example of a vehicle electrical system from an automated vehicle.

Abstract More than a decade ago, we proposed combined use of direct injection (DI) and jet ignition (JI) to produce high efficiency, high power-density, positive-ignition (PI), lean burn stratified, internal combustion engines (ICEs). Adopting this concept, the latest FIA F1 engines, which are electrically assisted, turbocharged, directly injected, jet ignited, gasoline engines and work lean stratified in a highly boosted environment, have delivered peak power fuel conversion efficiencies well above 46%, with specific power densities more than 340 kW/liter. The concept, further evolved, is here presented for unmanned aerial vehicle (UAV) applications. Results of simulations for a new DI JI ICE with rotary valve, being super-turbocharged and having gasoline or methanol as working fuel, show the opportunity to achieve even larger power densities, up to 430 kW/liter, while delivering a near-constant torque and, consequently, a nearly linear power curve over a wide range of speeds.

Abstract Sleep quality and maintenance of the optimal cognitive functioning is of crucial importance for aviation safety. Fatigue Risk Management (FRM) enables the operator to achieve the objectives set in their safety and FRM policies. As in any other risk management cycle, the FRM value can be realized by deploying suitable tools that aid robust decision-making. For the purposes of our article, we focus on fatigue hazard identification to explore the possible developments forward through the enhancement of objective tools in air transport operators. To this end we compare subjective and objective tools that could be employed by an FRM system. Specifically, we focus on an exploratory survey on 120 pilots and the analysis of 250 fatigue reports that are compared with objective fatigue assessment based on the polysomnographic (PSG) and neurocognitive assessment of three experimental cases.

Abstract Jet engine hot parts (e.g., jet nozzle) are a crucial source of aircraft’s infrared (IR) signature from the rearview, in 1.9-2.9 μm and 3-5 μm bands. The exhaust nozzle design used in a jet aircraft affects its performance and IR signature (which is also affected just by performance) from the engine layout. For supersonic aircraft (typically for M ∞ > 1.5), a converging-diverging (C-D) nozzle is preferred over a convergent nozzle for optimum performance. The diverging section of the C-D nozzle has a full range of visibility from the rearview; hence, it was not considered a prudent choice for low IR observability. This theoretical study compares the IR signature of the C-D nozzle with that of the convergent nozzle from the rearview in 1.9-2.9 μm and 3-5 μm bands for the same thrust.

Abstract The main focus of this article is the online estimation of the terminal airspace sector capacity from the Air Traffic Controller 0ATC) dynamical neural model using Neural Partial Differentiation (NPD) with permissible safe separation and affordable workload. For this purpose, a primarily neural model of a multi-input-single-output (MISO) ATC dynamical system is established, and the NPD method is used to estimate the model parameters from the experimental data. These estimated parameters have a less relative standard deviation, and hence the model validation results show that the predicted neural model response is well matched with the intervention of the ATC workload. Moreover, the proposed neural network-based approach works well with the experimental data online as it does not require the initial values of model parameters, which are unknown in practice.

Abstract The effects of exhaust emissions on public welfare have prompted the US Environmental Protection Agency to take various actions toward understanding, modeling, and reducing air pollution from vehicles. This study was performed to better understand exhaust emissions of heavy-duty diesel-powered tractor-trailer trucks that operate in drayage service, which involves the moving of shipping containers to or from port terminals. The study involved the use of portable emissions measurement systems (PEMS) to measure both gaseous and particulate matter (PM) mass emission rates and record various vehicle and engine parameters from the test trucks as they performed their normal drayage service. These measurements were supplemented with port terminal gate entry/exit logs for all drayage trucks entering the two Port of Houston Authority container terminals.

Abstract Particulates are a major source of emission from diesel engine. They consist of particles of carbon, sulfates, oil, fuel, and water. These constituents are measured by filtering a sample diluted in a partial- or full-flow tunnel and weighing them. It is a general trend for measuring particulate matter (PM) on cycle basis. But 1-D simulation needs complete PM 3-D contour map considering all engine operating region. It is very tedious work for generating PM on each steady-state point on engine test bed. Hence, Filter smoke meter or opacimeter measurements can be used for estimating PM. Filter smoke meters measured the light reflected from a filter paper through which a known volume of exhaust gas was passed. Opacity meters measure light absorbed by a standard column of exhaust. Both equipments measure visible black smoke comparatively at lower expenditure cost. They are designed to control measurement noise, resolution and repeatability with acceptable accuracy level.

Abstract With increased consumer demand for fuel efficient vehicles as well as more stringent greenhouse gas regulations and/or Corporate Average Fuel Economy (CAFE) standards from governments around the globe, the automotive industry, including the OEM (Original Equipment Manufacturers) and suppliers, is working diligently to innovate in all areas of vehicle design. In addition to improving aerodynamics, enhancing internal combustion engines and transmission technologies, and developing alternative fuel vehicles, mass reduction has been identified as an important strategy in future vehicle development. In this article, the development, analysis, and experiment of multi-cornered structures are presented. To achieve mass reduction, two non-traditional multi-cornered structures, with twelve- and sixteen-cornered cross-sections, were developed separately by using computer simulations.

Abstract This article focuses on the development of a two-way coupled methodology to predict gear temperature of oil jet lubricated transmissions using commercial software for computational fluid dynamics simulation. The proposed methodology applies an overset mesh technique to model the gear interlocking motion, multiphase of air-oil mixture, and heat transfer. Two gear pairs were used to develop and validate the methodology, an overdrive helical gear pair of a commercial vehicle transmission and a standard spur gear pair. Different oil jet lubrication methods were investigated using the proposed methodology, such as oil jet directed at the into-mesh position and at the out-of-mesh position. This investigation showed that out of mesh lubrication direction shows better cooling performance which is in well agreement with previous studies of literature.

Abstract The selective catalytic reduction (SCR) of nitrogen oxides seems to be the most promising technique to meet prospective emission regulations of diesel-driven commercial vehicles. In the case of developing cost-effective catalytic converters with comparably high activity, selectivity, and resistance against aging, ion-exchanged zeolites play a major role. This study presents, firstly, a brief literature review and subsequently a discussion of an extensive conversion analysis of exemplary Cu/ and Fe/zeolites, as well as a homogeneous admixture of both. The aging stages of SCR catalysts deserve particular attention in this study. In addition, the aging condition of the diesel oxidation catalyst (DOC) was analyzed, which influences the nitrogen dioxide (NO2) formation, because the NO2/nitrogen oxides (NOx) ratio upstream from the SCR converter could be identified as a key factor for low temperature NOx conversion.

Abstract Powertrain simulations and catalyst studies showed the efficiency credits and feasibility of onboard reforming as a way to recover waste heat from heavy duty vehicles (HDVs) fueled by natural gas (NG). Onboard reforming involves 1) injecting NG into the exhaust gas recycle (EGR) loop of the HDV, 2) reforming NG on a catalyst in the EGR loop to hydrogen and carbon monoxide, and 3) combusting the reformed fuel in the engine. The reformed fuel has increased heating value (4-10% higher LHV) and flame speed over NG, allowing stable flames in spark ignition (SI) engines at EGR levels up to 25-30%. A sulfur-tolerant reforming catalyst was shown to reform a significant amount of NG (15-30% conversion) using amounts of precious metal near the current practice for HDV emissions control (10 g rhodium). Engine simulations showed that the high EGR levels enabled by onboard reforming are used most effectively to control engine load instead of waste-gating or throttling.

Abstract A key element in an ergonomically designed driver’s seat in a car is the correct identification of driver seating position and posture accommodation. Current practice by the automotive Original Equipment Manufacturer (OEM) is to utilize the Society of Automotive Engineering (SAE) J1517 standard practice as a reference. However, it was found that utilizing such guidelines, which were developed based on the American population, did not fit well with the anthropometry and stature of the Malaysian population. This research seeks to address this issue by comparing the SAE J1517 Model against Malaysian preferred driving position. A total of 62 respondents were involved for the driver seating position and accommodation study in the vehicle driver’s seat buck mockup survey and measurements. The results have shown that the Malaysian drivers prefer to sit forward as compared to the SAE J1517 Model and have shorter posture joint angle.