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There are many different vibration sources in a car. Engine, gears, road roughness, impacts against the wheels cause vibration and sound that can decrease the parts and the car durability as well as affect drivability, safety and passengers and community comfort. In 4×4 cars, some extra vibration sources are the parts responsible for transmitting the torque and power to the rear wheels. Each of them has their own vibration modes, excited mostly by its imbalance or by the second order engine vibration. The engine vibration is a very well known phenomena and the rear driveshaft is designed not to have any vibration mode in the range of frequencies that the engine works or its second order. The imbalance of a driveshaft is also a design requirement. That means, the acceptable imbalance of the driveshaft is limited to a maximum value.

The extensive use of rotative machines in the diverse branches of the modern world has made the rising undesirable mechanical and acoustic vibration levels to be a problem of special importance for the machines normal operation as for the communities that are each time more affected by the problem. It makes the study of vibration and acoustic phenomena also to be even more important and the applications of its concepts more sophisticated. Several are the concepts used for decreasing vibration levels, like common dampers, hydraulic dampers, active dampers, natural frequencies changes and others. The choice of use of one or another depends greatly on the engineering possibilities (weight, energy, physical space, other components functional interference, vibration levels, etc.) as well as the cost of implementation of each one.

An L18 Taguchi-style Design of Experiments (DOE) with eight factors was used to optimize exterior mirrors for wind noise and drag. Eighteen mirror properties were constructed and tested on a full size greenhouse buck at the Lockheed low-speed wind tunnel in Marietta, GA. Buck interior sound data and drag measurements were taken at 80 MPH wind speed (0° yaw angle). Key wind noise parameters were the fore/aft length of mirror housing and the plan view angle of the mirror housing's inboard surface. Key drag parameters were the fore/aft length of the mirror housing, the cross-section shape of the mirror pedestal, and the angle of the pedestal (relative to the wind).

Dimethyl ether (DME) is an alternative to diesel fuel for use in compression-ignition engines with modified fuel systems and offers potential advantages of efficiency improvements and emission reductions. DME can be produced from natural gas (NG) or from renewable feedstocks such as landfill gas (LFG) or renewable natural gas from manure waste streams (MANR) or any other biomass. This study investigates the well-to-wheels (WTW) energy use and emissions of five DME production pathways as compared with those of petroleum gasoline and diesel using the Greenhouse gases, Regulated Emissions, and Energy use in Transportation (GREET®) model developed at Argonne National Laboratory (ANL).

Weld lines occur when melt flow fronts meet during the injection molding of plastic parts. It is important to investigate the weld line because the weld line area can induce potential failure of structural application. In this paper, a weld line factor (W-L factor) was adopted to describe the strength reduction to the ultimate strength due to the appearance of weld line. There were two engineering thermoplastics involved in this study, including one neat PP and one of talc filled PP plastics. The experimental design was used to investigate four main injection molding parameters (melt temperature, mold temperature, injection speed and packing pressure). Both the tensile bar samples with/without weld lines were molded at each process settings. The sample strength was obtained by the tensile tests under two levels of testing speed (5mm/min and 200mm/min) and testing temperatures (room temperature and -30°C). The results showed that different materials had various values of W-L factor.

A wavelet-based technique for reducing the impulsive character of sound recordings is presented. The amount of impulsive content removed may be adjusted by varying a statistical threshold. The technique is validated for a diesel idle sound-quality application. The wavelet-based modification produces a substantial decrease in impulsive character as verified by an objective sound-quality metric for engine “ticking”. Informal subjective assessment of the modified results found them to be realistic and free from artifacts. The procedure is expected to be useful for sound-quality simulation and target-setting for diesel powertrain noise and other automotive sounds containing both impulsive and non-impulsive content.

Recent applied mathematics research on the properties of the invertible shift-invariant discrete wavelet transform has produced new ways to visualize, separate, and synthesize impulsive sounds, such as thuds, slaps, taps, knocks, and rattles. These new methods can be used to examine the joint time-frequency characteristics of a sound, to select individual components based on their time-frequency localization, to quantify the components, and to synthesize new sounds from the selected components. The new tools will be presented in a non-mathematical way illustrated by two real-life sound quality problems, extracting the impulsive components of a windshield wiper sound, and analyzing a door closing-induced rattle.

Scalograms based on shift-invariant orthonormal wavelet transforms can be used to analyze impulsive and transient sounds in the presence of more stationary sound backgrounds, such as wind noise or drivetrain noise. The visual threshold of detection for impulsive features on the scalogram (signal energy content vs. time and frequency,) is shown to be similar to the audible threshold of detection of the human auditory system for the corresponding impulsive sounds. Two examples of impulsive sounds in a realistic automotive sound background are presented: automotive interior rattle in a vehicle passenger compartment, and spark knock recorded in an engine compartment.

This paper proposes a film dynamics model for liquid film resulting from fuel spray impinging on a wall surface. It is based on a thin film assumption and uses numerical particles to represent the film to be compatible with the particle spray models developed previously. The Lagrangian method is adopted to govern the transport of the film particles. A new, statistical treatment was introduced of the momentum exchange between the impinging spray and the wall film to account for the directional distribution of the impinging momentum. This model together with the previously published models for outgoing droplets constitutes a complete description of the spray wall impingement dynamics. For model validation, films resulting from impinging sprays on a flat surface with different impingement angles were calculated and the results were compared with the corresponding experimental measurements.

This work describes a single camera based object distance estimation system. As technology on vehicles is constantly advancing on the road to autonomy, it is critical to know the locations of objects in 3D space for safe behavior of the vehicle. Though significant progress has been made on object detection in 2D sensor space from a single camera, this work additionally estimates the distance to said object without requiring stereo vision or absolute knowledge of vehicle motion. Specifically, our proposed system is comprised of three modules: vision based ego-motion estimation, object-detection, and distance estimation. In particular, we compensate for the vehicle ego-motion by using pin-hole camera model to increase the accuracy of the object distance estimation.

Virtual Prototyping (VP) is an important method to assess the sound performance of possible designs in earlier stages of development. The common noise simulation with simple level determination can now be combined with subjective assessments that can be particularly interesting for noise content judgment. This paper will revise the literature found in this field that is applicable to the Engine Air Induction System inlet orifice noise and presents an example to illustrate the main advantages and difficulties in the implementation of VP.

Exhaust temperature models are widely used in the automotive industry to estimate catalyst and exhaust gas temperatures and to protect the catalyst and other vehicle hardware against over-temperature conditions. Modeled exhaust temperatures rely on air, fuel, and spark measurements to make their estimate. Errors in any of these measurements can have a large impact on the accuracy of the model. Furthermore, air-fuel imbalances, air leaks, engine coolant temperature (ECT) or air charge temperature (ACT) inaccuracies, or any unforeseen source of heat entering the exhaust may have a large impact on the accuracy of the modeled estimate. Modern universal exhaust gas oxygen (UEGO) sensors have heaters with controllers to precisely regulate the oxygen sensing element temperature. These controllers are duty cycle based and supply more or less current to the heating element depending on the temperature of the surrounding exhaust gas.

On the development process of truck vehicles, the dynamic behavior must be considered together with the costs involved in this development. Objective measurements, subjective evaluations and CAE simulations are used in order to support this development process. Ride comfort, acceleration and braking performance, handling and NVH are examples of attributes considered in the dynamic behavior evaluation of a tuck. Some characteristics of steering column vibration, noise and harshness are relevant to guarantee driver comfort level and vehicle safety. In this work, CAE models validated by experimental measurements were used to identify cab and vehicle modes of vibration which have significant influence on steering column response. Using this procedure, an alternative was proposed in order to decrease the amplitudes of cab and steering column vibration.

Vehicle chassis mounted cantilevered components should meet two critical design targets: 1) NVH criterion to avoid resonance with road noise and engine vibration and 2) satisfied durability performance to avoid any incident in structure failure and dysfunction. Generally, two types of testing are performed to validate chassis mounted cantilevered component in the design process: shaker table testing and vehicle proving ground testing. Shaker table testing is a powered vibration endurance test performed with load input summarized from real proving ground data and accurate enough to replicate the physical test. The proving ground test is typically performed at critical milestones with full vehicles. Most tests are simplified lab testing to save cost and effort. CAE procedures that virtually replicate these lab tests is even more helpful in the design verification stages.

A DMS (Driver Monitoring System) is one of the most important safety features that assist in the monitoring functions and alert drivers when distraction or drowsiness is detected. The system is based in a DSMC (Driver Status Monitoring Camera) mounted in the vehicle's dash, which has a predefined set of operational requirements that must be fulfilled to guarantee the correct operation of the system. These conditions represent a trade space analysis challenge for each vehicle since both the DSMC and the underlying vehicle’s requirements must be satisfied. Relying upon the camera’s manufacturer evaluation for every iteration of the vehicle’s design has proven to be time-consuming, resources-intensive, and ineffective from the decision-making standpoint.

The increasing trend toward electric and hybrid-electric vehicles (HEVs) has created unique challenges for NVH development and refinement. Traditionally, characterization of in-vehicle powertrain noise and vibration has been assessed through standard operating conditions such as fixed gear engine speed sweeps at varied loads. Given the multiple modes of operation which typically exist for HEVs, characterization and source-path analysis of these vehicles can be more complicated than conventional vehicles. In-vehicle NVH assessment of an HEV powertrain requires testing under multiple operating conditions for identification and characterization of the various issues which may be experienced by the driver. Generally, it is necessary to assess issues related to IC engine operation and electric motor operation (running simultaneously with and independent of the IC engine), under both motoring and regeneration conditions.

Recent trends show a growing demand for improved powertrain noise and vibration quality. In particular, there is little customer acceptance of vibration and noise (“boom”) at engine idle speeds. CAE analysis is being used increasingly as an aid for reducing overall vehicle level responses. Traditionally, analytical idle response is evaluated for only one particular engine order at a time. An efficient Excel based tool called VeCTRA (Vehicle Cascade & Target Response Analysis) was developed to accurately assess the effects of multiple powertrain orders on the vehicle level idle response. VeCTRA is capable of predicting the overall vehicle level response (tactile and acoustic) as well as determining the contribution from each engine order and the specific component excitations within an order. VeCTRA is capable of using analytical or experimentally measured sensitivity and/or excitation data.

Valvetrain ticking noise is one of the key failure modes in noise vibration harshness (NVH) evaluation at idle. It affects customer satisfaction inversely. In this paper, the root cause of the valvetrain ticking noise and key parameters that impact ticking noise will be presented. A physics based math model has been developed and integrated into a parameterized multi-body dynamic model. The analytical prediction has been correlated with testing data. Valvetrain ticking noise control is discussed.

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.

This paper presents an alternative and relatively simple method which allows the use of ordinary ejector-type diluters over a wide range of sample inlet conditions including elevated pressures and temperatures. After calibration of the ejector diluter, the dilution can be accurately characterized using only the pressures at the inlet and the outlet of the diluter and the sample temperature. The method is based on a semi-empirical, stationary model taking into account the critical parameters needed to predict the dilution factor. Under steady state operation it achieves accuracies estimated to be below ±8% (95% confidence interval) for diluter inlet pressures in the range of 1000 - 4000 mbar absolute and temperatures between 20 - 200°C. Performance under actual vehicle testing conditions is evaluated upstream of the DPF for a diesel vehicle run on a chassis dynamometer.