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Exhaust Gas Recirculation (EGR) coolers are commonly used in diesel and modern gasoline engines to reduce the re-circulated gas temperature. A common problem with the EGR cooler is a reduction of the effectiveness due to the fouling layer primarily caused by thermophoresis, diffusion, and hydrocarbon condensation. Typically, effectiveness decreases rapidly at first, and asymptotically stabilizes over time. There are several hypotheses of this stabilizing phenomenon; one of the possible theories is a deposit removal mechanism. Verifying such a mechanism and finding out the correlation between the removal and stabilization tendency would be a key factor to understand and overcome the problem. Some authors have proposed that the removal is a possible influential factor, while other authors suggest that removal is not a significant factor under realistic conditions.

Vehicle to Vehicle Communication use case performance heavily relies on market penetration rate. The more vehicles support a use case, the better the customer experience. Enabling these use cases with acceptable quality on vehicles without built-in navigation systems, elaborate map matching and highly accurate sensors is challenging. This paper introduces a simulation framework to assess system performance in dependency of vehicle positioning accuracy for matching approach path traces in Decentralized Environmental Notification Messages (DENMs) in absence of navigation systems supporting map matching. DENMs are used for distributing information about hazards on the road network. A vehicle without navigation system and street map can only match its position trajectory with the trajectory carried in the DENM.

As the development of autonomous vehicles rapidly advances, the use of convoying/platooning becomes a more widely explored technology option for saving fuel and increasing the efficiency of traffic. In cooperative adaptive cruise control (CACC), the vehicles in a convoy follow each other under adaptive cruise control (ACC) that is augmented by the sharing of preceding vehicle acceleration through the vehicle to vehicle communication in a feedforward control path. In general, the desired velocity optimization for vehicles in the convoy is based on fuel economy optimization, rather than driveability. This paper is a preliminary study on the impact of the desired velocity profile on the driveability characteristics of a convoy of vehicles and the controller gain impact on the driveability. A simple low-level longitudinal model of the vehicle has been used along with a PD type cruise controller and a generic spacing policy for ACC/CACC.

Lean NOx Traps (LNTs) are one type of lean NOx reduction technology typically used in smaller diesel passenger cars where urea-based Selective Catalytic Reduction (SCR) systems may be difficult to package . However, the performance of lean NOx traps (LNT) at temperatures above 400 C needs to be improved. The use of Rapidly Pulsed Reductants (RPR) is a process in which hydrocarbons are injected in rapid pulses ahead of a LNT in order to expand its operating window to higher temperatures and space velocities. This approach has also been called Di-Air (diesel NOx aftertreatment by adsorbed intermediate reductants) by Toyota. There is a vast parameter space which could be explored to maximize RPR performance and reduce the fuel penalty associated with injecting hydrocarbons. In this study, the mixing uniformity of the injected pulses, the type of reductant, and the concentration of pulsed reductant in the main flow were investigated.

In the current work, unidirectional (UD) carbon fiber composite hatsection component with two different layups are studied under dynamic three-point bending loading. The experiments are performed at various impact velocities, and the effects of impactor velocity and layup on acceleration histories are compared. A macro model is established with LS-DYNA for a more detailed study. The simulation results show that the delamination plays an important role during dynamic three-point bending test. Based on the analysis with a high-speed camera, the sidewall of hatsection shows significant buckling rather than failure. Without considering the delamination, the current material model cannot capture the post-failure phenomenon correctly. The sidewall delamination is modeled by assumption of larger failure strain together with slim parameters, and the simulation results of different impact velocities and layups match the experimental results reasonably well.

This paper focuses on finding and analyzing the relevant parameters affecting traffic flow when autonomous vehicles are introduced for ride hailing applications and autonomous shuttles are introduced for circulator applications in geo-fenced urban areas. For this purpose, different scenarios have been created in traffic simulation software that model the different levels of autonomy, traffic density, routes, and other traffic elements. Similarly, software that specializes in vehicle dynamics, physical limitations, and vehicle control has been used to closely simulate realistic autonomous vehicle behavior under such scenarios. Different simulation tools for realistic autonomous vehicle simulation and traffic simulation have been merged together in this paper, creating a realistic simulator with Hardware-in-the-Loop (HiL), Traffic-in-the-Loop (TiL), and Software in-the-Loop (SiL) simulation capabilities.

The platooning of connected automated vehicles (CAV) possesses the significant potential of reducing energy consumption in the Intelligent Transportation System (ITS). Moreover, with the rapid development of eco-driving technology, vehicle platooning can further enhance the fuel efficiency by optimizing the efficiency of the powertrain. Since road grade is a main factor that affects the energy consumption of a vehicle, the estimation of the road grade with high accuracy is the key factor for a connected vehicle platoon to optimize energy consumption using vehicle-to-vehicle (V2V) communication. Commonly, the road grade is quantified by single consumer grade global positioning system (GPS) with the geodetic height data which is rough and in the meter-level, increasing the difficulty of precisely estimating the road grade.

The transportation sector is facing three revolutions: shared mobility, electrification, and autonomous driving. To inform decision making and guide smart transportation system development at the city-level, it is critical to model and evaluate how travelers will behave in these systems. Two key components in such models are (1) individual travel demands with high spatial and temporal resolutions, and (2) travelers’ sociodemographic information and trip purposes. These components impact one’s acceptance of autonomous vehicles, adoption of electric vehicles, and participation in shared mobility. Existing methods of travel demand generation either lack travelers’ demographics and trip purposes, or only generate trips at a zonal level. Higher resolution demand and sociodemographic data can enable analysis of trips’ shareability for car sharing and ride pooling and evaluation of electric vehicles’ charging needs.

Unusual noises during vehicle acceleration often reflect poorly on customer perception of product quality and must be removed in the product development process. Flow simulation can be a valuable tool in identifying root causes of exhaust noises created due to tailpipe openings surrounded by fascia structure. This paper describes a case study where an unsteady Computational Fluid Dynamics (CFD) simulation of the combined flow and acoustic radiation from an exhaust opening through fascia components provided valuable insight into the cause of an annoying flow noise. Simulation results from a coupled thermal/acoustic analysis of detailed tailpipe opening geometry were first validated with off-axis microphone spectra under wide open throttle acceleration. After studying the visualizations of unsteady flow velocity and pressure from the CFD, a problem that had proved difficult to solve by traditional “cut and try” methods was corrected rapidly.

The USDOT and the Crash Avoidance Metrics Partnership-Vehicle Safety Communications 2 (CAMP-VSC2) Consortium (Ford, GM, Honda, Mercedes, and Toyota) initiated, in December 2006, a three-year collaborative effort in the area of wireless-based safety applications under the Vehicle Safety Communications-Applications (VSC-A) Project. The VSC-A Project developed and tested communications-based vehicle safety systems to determine if Dedicated Short Range Communications (DSRC) at 5.9 GHz, in combination with vehicle positioning, would improve upon autonomous vehicle-based safety systems and/or enable new communications-based safety applications.

The United States Department of Transportation (USDOT) and the Crash Avoidance Metrics Partnership-Vehicle Safety Communications 2 (CAMP-VSC2) Consortium (Ford, General Motors, Honda, Mercedes-Benz, and Toyota) initiated, in December 2006, a three-year collaborative effort in the area of wireless-based safety applications under the Vehicle Safety Communications-Applications (VSC-A) Project. The VSC-A Project developed and tested Vehicle-to-Vehicle (V2V) communications-based safety systems to determine if Dedicated Short Range Communications (DSRC) at 5.9 GHz, in combination with vehicle positioning, would improve upon autonomous vehicle-based safety systems and/or enable new communications-based safety applications.

While the engine mount rates need to be optimized to achieve the required frequency alignment and modal decoupling for quality performance, the robustness of the system needs to be studied as well. If a system exhibits acceptable modal characteristics with nominal optimized rates, the sensitivity of the system to variation of the rates from their nominal values affects the robustness of the system. Different factors can cause variation of the rates. Among them are rate changes from part to part arising from manufacturing process. In this paper the effect of mount rates variability on the modal characteristics is discussed. Monte Carlo simulation is used to predict how the rigid body modes and their couplings vary when the rate for each mount changes according to its statistical parameters. Through different examples the statistical variability of the modes to the rates variability is presented.

Road induced structural feel “vehicle feels solidly built” is strongly related to the vehicle ride [1]. Excellent structural feel requires both structural and suspension dynamics considerations simultaneously. Road induced structural feel is defined as customer facing structural and component responses due to tire force inputs stemming from the unevenness of the road surface. The customer interface acceleration and noise responses can be parsed into performance criteria to provide design and tuning vehicle integration program recommendations. A dynamic impact bump method is developed for vehicle level structural feel performance assessment, diagnostics, and development tuning. Current state of on-road testing has the complexity of multiple impacts, averaging multiple road induced tire patch impacts over a length of a road segment, and test repeatability challenges.

The fuel consumption of a vehicle is shown to be linearly proportional to (1) total vehicle work required to drive the cycle due to mass and acceleration, tire friction, and aerodynamic drag and (2) the powertrain (PT) mechanical losses, which are approximately proportional to the engine displaced volume per unit distance travelled (displacement time gearing). The fuel usage increases linearly with work and displacement over a wide range of applications, and the rate of increase is inversely proportional to the marginal efficiency of the engine. The theoretical basis for these predictions is reviewed. Examples from current applications are discussed, where a single PT is used across several vehicles. A full vehicle cycle simulation model also predicts a linear relationship between fuel consumption, vehicle work, and displacement time gearing and agrees well with the application data.

This research was performed using a designed experiment to evaluate the loss of dry surface braking performance and stability that could be associated with the disablement of specific brake positions on a tractor-semitrailer. The experiment was intended to supplement and update previous research by Heusser, Radlinski, Flick, and others. It also sought to establish reasonable limits for engineering estimates on stopping performance degradation attributable to partial or complete brake failure of individual S-cam air brakes on a class 8 truck. Stopping tests were conducted from 30 mph and 60 mph, with the combination loaded to GCW (80,000 lb.), half-payload, and with the flatbed semitrailer unladen. Both tractor and semitrailer were equipped with antilock brakes. Along with stopping distance, brake pressures, longitudinal acceleration, road wheel speed, and steering wheel position and effort were also recorded.

This paper starts describing the in-mold grain lamination and bilaminated film cover when applied to instrument panels with seamless passenger air bag doors. It then offers a comparison between two different PAB door weakening processes, the laser scoring and the scoring by milling. It further discuss the scoring by milling process and analyses its implementation on a real case instrument panel. In the implementation case, the scoring pattern is checked against a pre-defined engineering specification and correlated to the results of a drop tower test, which shows the force necessary to break the PAB door. Three iterations are performed until the results for scoring pattern and breaking force are achieved. The breaking force results are then statistically validated against the specification and capability analysis.

More than four decades ago, the concept of zero defects was coined by Phillip Crosby. It was only a vision at the time, but the introduction of Artificial Intelligence (AI) in manufacturing has since enabled it to become attainable. Since most mature manufacturing organizations have merged traditional quality philosophies and techniques, their processes generate only a few Defects Per Million of Opportunities (DPMO). Detecting these rare quality events is one of the modern intellectual challenges posed to this industry. Process Monitoring for Quality (PMQ) is an AI and big data-driven quality philosophy aimed at defect detection and empirical knowledge discovery. Detection is formulated as a binary classification problem, where the right Machine Learning (ML), optimization, and statistics techniques are applied to develop an effective predictive system.

A laboratory experiment is designed to examine the clunk phenomenon. A static torque is applied to a driveline system via the mass of an overhanging torsion bar and electromagnet. Then an applied load may be varied via attached mass and released to simulate the step down (tip-out) response of the system. Shaft torques and torsional and translational accelerations are recorded at pre-defined locations. The static torque closes up the driveline clearances in the pinion/ring (crown wheel) mesh. With release of the applied load the driveline undergoes transient vibration. Further, the ratio of preload to static load is adjusted to lead to either no-impact or impact events. Test A provides a ‘linear’ result where the contact stiffness does not pass into clearance. This test is used for confirming transient response and studying friction and damping. Test B is for mass release with sufficient applied torque to pass into clearance, allowing the study of the clunk.

This work is focused on the computer aided engineering noise and vibration control area (CAE-NVH), which is one of the most important in the automobile industry. The reason for that relevancy is that the noise and vibration effects can be directly perceived by the costumer. The vibration of the seats and steering wheel, as well as audible noises are some examples of factors that can cause discomfort to the driver. During the early design of a car, the systems are designed in a way to reach a good modal management level in order to avoid resonance problems. The finite element models, used to predict these resonances, are normally generated using only deterministic values for the model parameters such as stiffnesses, thicknesses and masses. However, these properties have an uncertainty due to the manufacturing process which is, in most cases, not taken into consideration during the design.

One-dimensional simulation tools are used extensively in the automotive industry to improve and optimize engine design for WOT performance. They are useful in target setting and in assessing the effects of certain design changes (e.g. intake manifold, valve timing, exhaust manifold, etc.). Generally the inputs to these models are “nominal” values or curves from a particular set of data and, therefore, do not take into account design or assembly variations. Often times, performance expectations are not met due to these “real world” effects and may result in significant re-design and testing efforts. The purpose of this paper is to assess the impact of typical model input variation on engine performance and to instill greater confidence in the use of these models in forecasting performance. The approach taken is to collect, analyze, and categorize actual build measurements from a 4.6L 4V Ford engine that are considered important inputs for a one-dimensional modeling.