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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 Traditionally driveline ratios are selected based on trial and error method of proto vehicle testing. This consumes lot of time and increases overall vehicle development effort. Over last few decades, simulation-based design approach has been extensively used to alleviate this problem. This paper describes torque converter and final drive ratio (FDR) selection at concept phase for new Automatic Transmission (AT) vehicle development. Most of the critical data required for simulating vehicle performance and fuel economy (FE) targets were not available (e.g. shift map, clutch slip map, pedal map, dynamic torque, coast down, etc.) at an initial stage of the project. Hence, the risk for assuming right inputs and properly selecting FDR/Torque converter was particularly high. Therefore, a validated AVL Cruise simulation model based on an existing AT vehicle was used as a base for new AT vehicle development to mitigate the risk due to non-availability of inputs.

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 In this article performance of the innovative Crank-Lever Electromagnetic Damper (CLEMD) for an off-road vehicle suspension system is analyzed. To determine the characteristic behavior of the CLEMD, the damping force it provides on the suspension system is varied by changing the values of the damping coefficient in the simulations. Various parameters considered in the analyses include power regenerated, voltage, current, comfort, road-holding, etc. The behavior of all the parameters of the CLEMD is observed for an off-road vehicle by carrying out simulations on country roads since the off-road vehicles are subjected to higher road irregularities and hence provide an opportunity to regenerate a higher amount of power. A two-dimensional (2-D) model of a vehicle developed in SimMechanics is interfaced with a Simulink model of CLEMDs for the analyses.

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 A torque converter was instrumented with 29 pressure transducers inside five cavities under study (impeller, turbine, stator, clutch cavity between the pressure plate and the turbine shell). A computer model was created to establish correlation with measured torque and pressure. Torque errors between test and simulation were within 5% and K-Factor and torque ratio errors within 2%. Turbulence intensity on the computer model was used to simulate test conditions representing transmission low and high line pressure settings. When turbulence intensity was set to 5%, pressure simulation root mean square errors were within 11%-15% for the high line pressure setting and up to 34% for low line pressure setting. When turbulence intensity was increased to 50% for the low line pressure settings, a 6% reduced root mean square error in the pressure simulations was seen.

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 The development, analysis, and optimization of battery electric class-7 heavy-duty trucks equipped with multi-speed transmissions are discussed in this paper. The designs of five new traction motors-fractional-slot, concentrated winding machines-are proposed for use in heavy-duty electric trucks. The procedure for gear-ratio range selection is outlined and ranges of gear ratios for three-to six-speed transmission powertrains are calculated for each of the proposed electric traction motors. The simulation and gear-ratio optimization tasks for class-7 battery electric trucks are formulated. The energy consumption of the e-truck with the twenty possible powertrain combinations is minimized over the four driving cycles and the most efficient powertrain layouts that meet the performance criteria are recommended.

Abstract This article presents a comprehensive investigation for the interaction between vehicle ride vibration control and braking control using two degrees of freedom (2DOF) quarter vehicle model. A typical limited bandwidth active suspension system with nonlinear spring and damping characteristics of practical hydraulic and pneumatic components is controlled to regulate both suspension and tire forces and therefore provide the optimum ride comfort and braking performance of an anti-lock brake system (ABS). In order to design a suitable controller for this nonlinear integrated system, various control techniques are followed including state feedback tuned using Linear Quadratic Regulator (LQR), state feedback tuned using Genetic Algorithm (GA), Proportional Integrated (PI) tuned genetically, and Fuzzy Logic Control (FLC). The ABS control system is designed to limit skid ratio below threshold of 15%.

Abstract Constant area section length downstream to the fuel injection point is a crucial dimension of scramjet duct geometry. It has a major contribution in creating the maximum effective pressure inside the combustor that is required for propulsion. The length is limited by the thermal choking phenomenon, which occurs when heat is added in a flow through constant area duct. As per theory, to avoid thermal choking the constant area section length depends upon the inlet conditions and the rate of heat addition. The complexity related to mixing and combustion process inside the supersonic stream makes it difficult to predict the rate of heat addition and in turn the length. Recent efforts of simulating the reacting flow inside scramjet combustors are encouraging and can be useful in this regard. The presented work attempts to use simulation results of scramjet combustion for predicting the constant area section length for a typical scramjet combustor.

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 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 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 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 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 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 The study of road loads on trucks plays a major role in assessing the effect of heavy-vehicle design on fuel conservation measures. Coastdown testing with full-scale vehicles in the field offers a good avenue to extract drag components, provided that random instrumentation faults and biased environmental conditions do not introduce errors into the results. However, full-scale coastdown testing is expensive, and environmental biases which are ever-present are difficult to control in the results reduction. Procedures introduced to overcome the shortcomings of full-scale field testing, such as wind tunnels and computational fluid dynamics (CFD), though very reliable, mainly focus on estimating the effects of aerodynamic drag forces to the neglect of other road loads which should be considered.

Abstract Automated guided vehicle systems (AGVS) are the prominent one in modern material handling systems used in small manufacturing enterprises (SMEs) due to their exciting features and benefits. This article pinpoints the need of AGVS in SMEs by describing the material handling selection in SMEs and enlightening recent technological developments and approaches of the AGVS. Additionally, it summarizes the analytical and simulation-based tools utilized in design problems of AGVS along with the influence of material handling management and key hurdles of AGVS. The current study provides a limelight towards making smart automated guided vehicles (AGVs) with the simplified and proper routing system and favorable materials and more importantly reducing the cost and increasing the flexibility.

Abstract Since the tire inflation pressure has a significant influence on safety, comfort and environmental behavior of a vehicle, the choice of the optimal inflation pressure is always a conflict of aims. The development of a highly dynamic Tire Pressure Control System (TPCS) can reduce the conflict of minimal rolling resistance and maximal traction. To study the influence of the tire inflation pressure on longitudinal tire characteristics under laboratory conditions, an experimental sensitivity analysis is performed using a multivalent usable Corner Module Test Rig (CMTR) developed by the Automotive Engineering Group at Technische Universität Ilmenau. The test rig is designed to analyze suspension system and tire characteristics on a roller of the recently installed 4 chassis roller dynamometer. Camber angle, toe angle and wheel load can be adjusted continuously. In addition, it is possible to control the temperature of the test environment between −20 °C and +45 °C.