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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.

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.

In this paper, a systems engineering approach is explored to evaluate the effect of design parameters that contribute to the performance of the embedded Automatic Speech Recognition (ASR) engine in a vehicle. This includes vehicle designs that influence the presence of environmental and HVAC noise, microphone placement strategy, seat position, and cabin material and geometry. Interactions can be analyzed between these factors and dominant influencers identified. Relationships can then be established between ASR engine performance and attribute performance metrics that quantify the link between the two. This helps aid proper target setting and hardware selection to meet the customer satisfaction goals for both teams.

This paper describes two case studies in which multiple microphone processing (beamforming) and microphone location were evaluated to determine their impact on improving embedded automatic speech recognition (ASR) in a vehicle hands-free environment. While each of these case studies was performed using slightly different evaluation set-ups, some specific and general conclusions can be drawn to help guide engineers in selecting the proper microphone location and configuration in a vehicle for the improvement of ASR. There were some outcomes that were common to both dual microphone solutions. When considering both solutions, neither was equally effective across all background noise sources. Both systems appear to be far more effective for noise conditions in which higher frequency energy is present, such as that due to high levels of wind noise and/or HVAC (heating, ventilation and air conditioning) blower noise.

This paper describes a method to validate in-vehicle speech recognition by combining synthetically mixed speech and noise samples with batch speech recognition. Vehicle cabin noises are prerecorded along with the impulse response from the driver's mouth location to the cabin microphone location. These signals are combined with a catalog of speech utterances to generate a noisy speech corpus. Several factors were examined to measure their relative importance on speech recognition robustness. These include road surface and vehicle speed, climate control blower noise, and driver's seat position. A summary of the main effects from these experiments are provided with the most significant factors coming from climate control noise. Additionally, a Signal to Noise Ratio (SNR) experiment was conducted highlighting the inverse relationship with speech recognition performance.

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.

This paper discusses the optimization of an automotive hydraulic steering pump pulley design for improved in-vehicle pump NVH performance. Levels of steering pump whine noise heard inside a vehicle were deemed objectionable. Vehicle and component transfer path analyses indicated that the dominant noise path for the whine noise was airborne in nature. Subsequent experimental modal analysis indicated that the steering pump pulley was a major contributor to the amount of radiated noise produced by the pump/pulley system. CAE analysis was used to further analyze the dynamic behavior of the pulley and develop an optimized design with decreased noise radiation efficiency. The results predicted with the CAE analysis were verified in-vehicle, resulting in a vehicle with acceptable steering pump whine noise performance.

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.

Diesel engine exhaust aftertreatment components, especially the diesel particulate filter (DPF), are subject to various modes of degradation over their lifetimes. One particular adverse effect on the DPF is the significant rise in pressure drop due to the accumulation of engine lubricant-derived ash which coats the inlet channel walls effectively decreasing the permeability of the filter. The decreased permeability due to ash in the DPF can result in increased filter pressure drop and decreased fuel economy. A unique two-step approach, consisting of experimental measurements and direct numerical simulations using ultra-high resolution 3D imaging data, has been utilized in this study to better understand the effects of ash accumulation on engine aftertreatment component functionality.

Sunroof is placed in certain high-end vehicles to give user a better driving experience. All automakers are searching alternatives to reduce weight and cost in the vehicle, in which sunroofs are also impacted. Some alternatives are already applied, as a honeycomb paper used in some sunshades that presents benefits, as less weight and with a good cost reduction. Although, due the reduced weight for this part produced in this material, it shows more susceptibility to reproduce the vibration that vehicle propagates in movement, especially in bad condition roads. The sunroof assembly is dependent of the roof reinforcement and roof skin, but in this special case, the validation could be done in the components itself because the interaction of the sunshades is directly dependent of the other sunroof parts, as rails and front frame.

Squeak and rattle are two undesirable occurrences during component operation and during vehicle driving condition, resulting in one of the top complains from costumers. One common grievance could happen during the user exterior handle operation and during side door closing. The exterior handle system during the operation could generate a squeak between interface parts, if materials and geometric tolerances was not been carefully designed. Also, vibration generated during door closing effort, might generate squeak between parts since the reinforcement for exterior handle touches the outer sheet metal internally. For this reason several guidelines might be included to avoid potential noise condition for this system during vehicle lifetime as correct material reduce friction between parts, taking into consideration the geometric condition between parts. Plus, coupling system on handles two pieces should also be evaluated to avoid squeak during use.

A measurement technique is presented to detect and quantify piston pin tick noise, thereby aiding optimization of piston pin bushing design. Furthermore, the characteristics of two types of piston pin noise are described. The first is caused by excessive clearance between the pin and the connecting rod bushing. A noncircular clearance between the pin and the connecting rod bushing causes the second type of the piston pin tick noise. Finally, a process is discussed to consider pin tick in the design and verification of the piston and connecting rod assembly. The method presented could also be used to investigate other unusual engine noises.

In this paper, a new technology for the design of silent transaxles is developed, where topography optimization is adopted and an artificial parameter called β is proposed as an objective function, representing an upper bound of the surface velocity. The strategy of the optimization is to minimize β while getting the surface velocities less than β. as the constraints. A numerical example of reducing transaxle's radiated noise by using the new optimization technology is given in the paper. In the example, an entire Ford transaxle system was modeled numerically, where most internal components were included. First a modal frequency velocity analysis was conducted. Then an acoustic power analysis based on the Acoustic Transfer Vector (ATV) was carried out. Finally, a topography optimization based on the β - method for the transaxle was performed to minimize the radiated noise.

Many decisions need to be made when test track data is used to set up Squeak & Rattle evaluations of subsystems or components. These decisions are judgment-based so different people with different backgrounds and experience levels will make different decisions - few of which can be called right or wrong - but they are different which causes problems. Squeak & Rattle evaluation has become more scientific in recent years as subjective evaluation has been replaced by quantitative methods like N10 Loudness and shakers have become quiet. It is the authors' contention that the variations caused by different judgment calls can no longer be tolerated. Therefore a methodical process was developed which assures that different people will get the same results from the same set of test track data.

A computational design study, performed in conjunction with experiments, to reduce the howl noise caused by the roof rack crossbars of a production automobile is presented. This goals were to obtain insight into the flow phenomenon causing the noise, and to do a design iteration study that would lead to a small number of cross-section recommendations for crossbars that would be tested in the wind tunnel. The flow condition for this study is 0 yaw at 30 mph inlet speed, which experimentally gives the strongest roof rack howl for the vehicle considered for this study. The numerical results have been obtained using the commercial CFD/CAA software PowerFLOW. The simulation kernel of this software is based on the numerical scheme known as the Lattice Boltzmann Method (LBM), combined with a two-equation RNG turbulence model.

Rear Window Buffeting (RWB) is the low-frequency, high amplitude, sound that occurs in many 4-door vehicles when driven 30-70 mph with one rear window lowered. The goal of this paper is to demonstrate that the mechanisms of RWB are similar to that of sun roof buffeting and to describe the results of several actions suspected in contributing to the severity of RWB. Finally, the results of several experiments are discussed that may lend insight into ways to reduce the severity of this event. A detailed examination of the side airflow patterns of a small Sport Utility Vehicle (SUV) shows these criteria exist on a small SUV, and experiments to modify the SUV airflow pattern to reduce RWB are performed with varying degrees of success. Based on the results of these experiments, design actions are recommended that may result in the reduction of RWB.

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.

The Engine-Out Particulate Matter (EOPM) was collected from a spark ignition engine operating in steady state using a heated quartz fiber filter. The samples were weighted to obtain an EOPMindex and were analyzed using Scanning Electron Microscopy. The EOP Mindex was not sensitive to the engine rpm and load. When the mixture is very rich (air equivalence ratio λ less than ∼ 0.7), the EOPM comprise mostly of soot particles from fuel combustion. In the lean to slightly rich region (0.8 < λ < 1.2), however, the EOPM are dominated by particles derived from the lubrication oil.