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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 A number of studies have shown that driving an unfamiliar vehicle has the potential to introduce additional risk, especially for novice drivers. However, such studies have generally used statistical methods based on analyzing crash and near-crash data from a range of driver groups, and therefore the evaluation has the potential to be subjective and limited. For a more objective perspective, this study suggests that it would be worthwhile to consider vehicle dynamic signals obtained from the Controller Area Network (CAN-Bus) and smartphones. This study, therefore, is focused on the effect of driver experience and vehicle familiarity for issues in driver modeling and distraction. Here, a group of 20 drivers participated in our experiment, with 13 of them having participated again after a one-year time lapse in order for analysis of their change in driving performance.

Abstract Lane changes are stressful maneuvers for drivers, particularly during high-speed traffic flows. However, modeling driver’s lane-changing decision and implementation process is challenging due to the complexity and uncertainty of driving behaviors. To address this issue, this article presents a personalized Lane-Changing Model (LCM) for Advanced Driver Assistance System (ADAS) based on deep learning method. The LCM contains three major computational components. Firstly, with abundant inputs of Root Residual Network (Root-ResNet), LCM is able to exploit more local information from the front view video data. Secondly, the LCM has an ability of learning the global spatial-temporal information via Temporal Modeling Blocks (TMBs). Finally, a two-layer Long Short-Term Memory (LSTM) network is used to learn video contextual features combined with lane boundary based distance features in lane change events.

Abstract In today’s competitive automobile market, driver comfort is at utmost importance and the bar is being raised continuously. Gear Shifting is a crucial customer touch point. Any issue or inconvenience caused while shifting gear can result into customer dissatisfaction and will impact the brand image. While there are continual efforts being taken by most of the car manufactures, “Double Bump” in gearshift has remained as a pain area and impact severely on the shift feel. This is more prominent in North-South (N-S) transmissions. In this paper ‘Double Bump’ is a focus area and a mathematical / analytical approach is demonstrated by analyzing ‘impacting parameters’ and establishing their co-relation with double bump. Additionally, the results are also verified with a simulation model.

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 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 Making use of a specifically designed dynamical vehicle model, the authors here presented the results of an activity for the evaluation of energy consumption and CO2 emissions of buses for urban applications. Both conventional and innovative (series hybrid, and fully electric) vehicles were considered to obtain interesting comparative conclusions. The derived tool was used to simulate the dynamical behaviour of these vehicles on a number of kinematic profiles measured during real buses operation in different contexts, varying from really congested city centre routes to fast-lane operated services. It was so possible to evaluate the energetic performances of those buses on a Tank-to-Wheel (TTW) basis.

Abstract Joining titanium (Ti) alloys with conventional processes is difficult due to their complex structural properties and ability of phase transformation. Concerning all the difficulties, diffusion bonding is considered as an appropriate process for joining Ti alloys. Ti6Al4V, which is an α+β alloy widely used for aero engine component manufacturing, is diffusion bonded in this investigation. The diffusion bonding process parameters such as bonding temperature, bonding pressure, and holding time were optimized to achieve desired bonding characteristics such as shear strength, bonding strength, bonding ratio, and thickness ratio using response surface methodology (RSM). Empirical relationships were developed for the prediction of the bond characteristics, and sensitivity analysis was performed to determine the increment and decrement tendency of the shear strength with respect to the bonding parameters.

Abstract A key problem of the construction of fully electric aircraft is the limited energy density of battery packs. It is generally accepted that this can only be overcome via new, denser battery chemistry together with a further increase in the efficiency of power utilization. One appealing approach for achieving the latter is using laser-assisted filler-based joining technologies, which offers unprecedented flexibility for achieving battery cell connections with the least possible electrical loss. This contribution presents our results on the effect of various experimental and process parameters on the electrical and mechanical properties of the laser-formed bond.

Abstract A methodology for the development of catalyst models is presented. Also, a methodology of the implementation of such models into a modular simulation tool, which simulates the units in succession, is presented. A case study is presented illustrating how suitable models can be found and used for simulations. Such simulations illustrate the behavior of the individual units and the overall system. It is shown how, by simulating the units in succession, the entire after treatment system can be tested and optimized, because the integration makes it possible to observe the effect of the modules on one another.

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 Commercial vehicles contribute to the majority of freight transportation in the United States. They are also significant fuel consumers, with over 23% of fuel used in transportation in the United States. The gas price volatility and increasingly stringent regulation on greenhouse-gas emissions have driven manufacturers to adopt new fuel-efficient technologies. Among others, an advanced transmission control strategy, which can provide tangible improvement with low incremental cost. In the commercial sector, individual drivers have little or no interest in vehicle fuel economy, contrary to fleet owners. Aggressive driving behavior can greatly increase the real-world vehicle fuel consumption. However, the effectiveness of transmission calibration to match the shift strategy to the driving characteristics is still a challenge.

Abstract Dynamic stresses exist in parts of a catalyst muffler caused by the vibration of a moving vehicle, and it is important to clarify and predict the vibration response properties for preventing fatigue failures. Assuming a vibration isolating installation in the vehicle frame, the vibration transmissibility and local dynamic stress of the catalyst muffler were examined through a vibration machine. Based on the measured data and by systematically taking vibration theories into consideration, a new prediction method of the vibration modes and parameters was proposed that takes account of vibration isolating and damping. A lumped vibration model with the six-element and one mass point was set up, and the vibration response parameters were analyzed accurately from equations of motion. In the vibration test, resonance peaks from the hanging bracket, rubber bush, and muffler parts were confirmed in three excitation drives, and local stress peaks were coordinate with them as well.

Abstract Electric heavy-duty tractor-trailers (EHDTT) offer an important option to reduce greenhouse gases (GHG) for the transportation sector. However, to increase the range of the EHDTT, this effort investigates critical vehicle design features that demonstrate a gain in overall freight efficiency of the vehicle. Specifically, factors affecting aerodynamics, rolling resistance, and gross vehicle weight are essential to arrive at practical input parameters for a comprehensive numerical model of the EHDTT, developed by the authors in a subsequent paper. For example, drag reduction devices like skirts, deturbulators, vortex generators, covers, and other commercially available apparatuses result in an aggregated coefficient of drag of 0.367. Furthermore, a mixed utilization of single-wide tires and dual tires allows for an optimized trade-off between low rolling resistance tires, traction, and durability.

Abstract Vehicle cabin air quality depends on various parameters such as number of passengers, fan speed, and vehicle speed. In addition to controlling the temperature inside the vehicle, HVAC control system has evolved to improve cabin air quality as well. However, there is no standard test method to ensure reliable and repeatable comparison among different cars. The current study defined Cabin Air Quality Index (CAQI) and proposed a test method to determine CAQI. CAQIparticles showed dependence on the choice of metrics among particle number (PN), particle surface area (PS), and particle mass (PM). CAQIparticles is less than 1 while CAQICO2 is larger than 1. The proposed test method is promising but needs further improvement for smaller coefficient of variations (COVs).

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 This study investigates methods to precisely control a coolant pump in an internal combustion engine. The goal of this research is to minimize power consumption while still meeting optimal performance, reliability and durability requirements for an engine at all engine-operating conditions. This investigation achieves reduced fuel consumption, reduced emissions, and improved powertrain performance. Secondary impacts include cleaner air for the earth, reduced operating costs for the owner, and compliance with US regulatory requirements. The study utilizes mathematical modeling of the cooling system using heat transfer, pump laws, and boiling analysis to set limits to the cooling system and predict performance changes.

Abstract The Friction stir welding (FSW) is recently presented so to join different materials without the melting process as a solid-state joining technique. A widely application for the FSW process is recently developed in automotive industries. To create the welded components by using the FSW, the plunged probe and shoulder as welding tools are used. The Finite Element Method (FEM) can be used so to simulate and analyze material flow during the FSW process. As a result, thermal and mechanical stresses on the workpiece and welding tool can be analyzed and decreased. Effects of the welding process parameters such as tool rotational speed, welding speed, tool tilt angle, depth of the welding tool, and tool shoulder diameter can be analyzed and optimized so to increase the efficiency of the production process. Material characteristics of welded parts such as hardness or grain size can be analyzed so to increase the quality of part production.

Abstract The present study aims to join the dissimilar materials such as Dual-Phase (DP) 600 Steel and AA6082-T6 Aluminum (Al) alloy via the friction stir welding (FSW) process with a reduced intermetallic compound (IMC) layer. The five different tool tilt angles of 0°, 0.5°, 1°, 1.5°, and 2° were selected to fabricate the joints. The weld characteristics such as tensile strength, hardness, macrostructure, and microstructure were analyzed. The weld interface was studied by employing an optical microscope and scanning electron microscope (SEM) equipped with energy-dispersive X-ray spectroscopy (EDS) and X-ray diffraction (XRD) techniques. The joint produced with a 0.5° tilt angle has achieved the highest ultimate tensile strength (UTS) of 240 MPa. The IMCs were identified as Fe2Al8 and FeAl2 from the joint interface studies.