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A wet clutch model is required in automotive propulsion system simulations for enabling robust design and control development. It commonly assumes Coulomb friction for simplicity, even though it does not represent the physics of hydrodynamic torque transfer. In practice, the Coulomb friction coefficient is treated as a tuning parameter in simulations to match vehicle data for targeted conditions. The simulations tend to deviate from actual behaviors for different drive conditions unless the friction coefficient is adjusted repeatedly. Alternatively, a complex hydrodynamic model, coupled with a surface contact model, is utilized to enhance the fidelity of system simulations for broader conditions. The theory of elastic asperity deformation is conventionally employed to model clutch surface contact. However, recent examination of friction material shows that the elastic modulus of surface fibers significantly exceeds the contact load, implying no deformation of fibers.

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.

Morphological features of voids were characterized for T300/924 12-ply and 16-ply composite laminates at different porosity levels through the implementation of a digital microscopy (DM) image analysis technique. The composite laminates were fabricated through compression molding. Compression pressures of 0.1MPa, 0.3MPa, and 0.5MPa were selected to obtain composite plaques at different porosity levels. Tension-tension fatigue tests at load ratio R=0.1 for composite laminates at different void levels were conducted, and the dynamic stiffness degradation during the tests was monitored. Fatigue mechanisms were then discussed based on scanning electron microscope (SEM) images of the fatigue fracture surfaces. The test results showed that the presence of voids in the matrix has detrimental effects on the fatigue resistance of the material, depending on the applied load level.

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.

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.

Autonomous Vehicles (AVs) operate based on image information and 3D maps generated by sensors like cameras, LIDARs and RADARs. This information is processed by the on-board processing units to provide the right actuation signals to drive the vehicle. For safe operation, these sensors should provide continuous high quality data to the processing units without interruption in all driving conditions like dust, rain, snow and any other adverse driving conditions. Any contamination on the sensor surface/lens due to rain droplets, snow, and other debris would result in adverse impact to the quality of data provided for sensor fusion and this could result in error states for autonomous driving. In particular, snow is a common contamination condition during driving that might block a sensor surface or camera lens. Predicting and preventing snow accumulation over the sensor surface of an AV is important to overcome this challenge.

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.

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.

With the rapid development of artificial intelligence, the autonomous vehicles (AV) have attracted considerable attention in the automotive industry. However, different factors negatively impact the adoption of the AVs, delaying their successful commercialization. Accretion of atmospheric icing, especially wet snow, on AV sensors causes blockage on their lenses, making them prone to lose their sight, in turn, increasing potential chances of accidents. In this study, two different designs are proposed in order to prevent snow accretion on the lenses of AVs via air flow across the lens surface. In both designs, lenses made of plain glass and superhydrophobic coated glass surfaces are tested. While some researchers have shown promise of water repellency on superhydrophobic surfaces, more snow accretion is observed on the superhydrophobic surfaces, when compared to the plain glass lenses.

As an alternative lightweight material, chopped carbon fiber reinforced Sheet Molding Compound (SMC) composites, formed by compression molding, provide a new material for automotive applications. In the present study, the monotonic and fatigue behavior of chopped carbon fiber reinforced SMC is investigated. Tensile tests were conducted on coupons with three different gauge length, and size effect was observed on the fracture strength. Since the fiber bundle is randomly distributed in the SMC plaques, a digital image correlation (DIC) system was used to obtain the local modulus distribution along the gauge section for each coupon. It was found that there is a relationship between the local modulus distribution and the final fracture location under tensile loading. The fatigue behavior under tension-tension (R=0.1) and tension-compression (R=-1) has also been evaluated.

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.

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.

The effect of friction modifiers on the low-speed frictional properties of automatic transmission fluids (ATFs) was investigated by scanning force microscopy (SFM). A clutch lining material was covered by a droplet of test ATF, and a steel tip was scanned over the sample. The scanning speeds were varied from 0.13 to 8.56 mm /sec, and the frictional force was deduced from the torsion of the SFM cantilever. A reduction in dynamic friction due to the addition of the friction modifier was clearly observed over the entire speed range. This indicates that the boundary lubrication mechanism is dominant under this condition, and therefore surface-active friction modifiers can effectively improve the frictional characteristics. The friction reduction was more pronounced at lower sliding speeds. Thus addition of friction modifiers produced a more positive slope in the μ-ν (friction vs. sliding speed) plots, and would contribute to make wet clutch systems less susceptible to shudder vibrations.

Stress analyses of complex automotive components can be nearly impossible to achieve due to extreme difficulties in generating a realistic finite element model. A digital image based finite element approach was used to generate a 3-D finite element model from computed tomography (CT) scans of two automotive transmission cases. For the first case, original CT slices of 1024x1024x208 provided by ARACOR Inc. (Sunnyvale, CA) were used to generate a 3-D finite element model containing nearly 400,000 8-node brick elements. For the second case, 770x870x759 CT slices were used to generate a 3-D finite element model containing approximately 650,000 3-D elements. The mesh data generation from CT data for both cases took 6 minutes each on an engineering workstation. The resulting finite element meshes were analyzed using a specially designed finite element equation solver.

Hardware benchmarking of body overall stiffness and joint stiffness of the best-in-class competitive vehicles is a common practice in the automobile industry. However, this process does not provide design insights of competitive body structures, which relate stiffness performance to key architectural designs. To overcome this drawback, a CAD body-in-prime model of a competitive vehicle is developed using laser/optical scanning technology and a corresponding CAE model is built based on the CAD data. A deep-dive structural efficiency study is conducted using this model and “pros” and “cons” of the architectural design of each individual joint and each section of major load-carrying members of this body structure are identified. This analytical benchmarking (or reverse engineering) process enables a company to adopt best-in-class design practices and achieve competitive advantages in vehicle designs.

With the increasing demand for safety, energy saving and emission reduction, Advanced High Strength Steels (AHSS) have become very attractive materials for automobile makers. Welding of AHSS remains one of the technical challenges in the successful application of AHSS in automobile structures, especially when durability of the welded structures is required. In this study, 2.0 mm uncoated DP780 was investigated. GMAW welding parameters for lap joints of this steel were developed in order to obtain different weld geometries defined by weld toe angle, weld leg sizes, and weld penetration. Metallurgical properties of the joints were evaluated using optical microscopy and scanning electron microscopy (SEM). Static and fatigue tests were conducted on the welded joints. Effect of weld geometry and HAZ softening on fatigue performance including fatigue life, crack initiation site and propagation path of the joints will be analyzed.