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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).

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.

Dedicated Exhaust Gas Recirculation (D-EGR®) technology provides a novel means for fuel efficiency improvement through efficient, on-board generation of H2 and CO reformate [1, 2]. In the simplest form of the D-EGR configuration, reformate is produced in-cylinder through rich combustion of the gasoline-air charge mixture. It is also possible to produce more H2 by means of a Water Gas Shift (WGS) catalyst, thereby resulting in further combustion improvements and overall fuel consumption reduction. In industrial applications, the WGS reaction has been used successfully for many years. Previous engine applications of this technology, however, have only proven successful to a limited degree. The motivation for this work was to develop and optimize a WGS catalyst which can be employed to a D-EGR configuration of an internal combustion engine. This study consists of two parts.

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.

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.

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.

The diesel particulate filter (DPF) is a critical aftertreatment device for control of particulate matter (PM) emissions from a diesel engine. DPF survivability is challenged by several key factors such as: excessive thermal stress due to DPF runaway regenerations (or uncontrolled regeneration) may cause DPF substrate and washcoat failure. Catalyst poisoning elements from the diesel fuel and engine oil may cause performance degradation of the catalyzed DPF. Harsh vibration from the powertrain, as well as from the road surface, may lead to mechanical failure of the substrate and/or the matting material. Evaluations of these important validation parameters were performed.

Realistic vehicle fuel economy studies require real-world vehicle driving behavior data along with various factors affecting the fuel consumption. Such studies require data with various vehicles usages for prolonged periods of time. A project dedicated to collecting such data is an enormous and costly undertaking. Alternatively, we propose to utilize two publicly available vehicle travel survey data sets. One is Puget Sound Travel Survey collected using GPS devices in 484 vehicles between 2004 and 2006. Over 750,000 trips were recorded with a 10-second time resolution. The data were obtained to study travel behavior changes in response to time-and-location-variable road tolling. The other is Atlanta Regional Commission Travel Survey conducted for a comprehensive study of the demographic and travel behavior characteristics of residents within the study area.

Gasoline particulate filters (GPF) with high filtration efficiency (>80%) at zero mileage are in growing demand to meet increasingly tight vehicle emission standards for particulate matter being implemented in US, EU, China and elsewhere. Current efforts to achieve high filter performance mainly focus on fine-tuning the filter structure, such as the pore size distribution and porosity of the bare substrate, or the washcoat loading and location of catalyzed substrates. However, high filtration efficiency may have a cost in high backpressure that negatively affects engine power. On the other hand, it has been recognized in a few reports that very low amounts of ash deposits (from non-combustible residue in the exhaust) can significantly increase filtration efficiency with only a mild backpressure increase.

Statistical Energy Analysis (SEA) is used to predict high-frequency acoustic and vibration response in vehicle NVH design. Early in the design cycle prototype hardware is not yet available for testing and the geometry is still too poorly defined and changing too quickly for Finite Element Analysis or Boundary Element Analysis to be an effective NVH analysis tool. For most of the concept phase and early design phase, SEA uniquely offers the ability to virtually predict the main noise transfer paths and to support target setting for component and full vehicle NVH design. At later stages of the design process, SEA combines with NVH testing to provide more accurate predictions and to provide guidance for more efficient testing. This paper describes the established uses of SEA in the vehicle industry and presents an overview of the NVH design cycle and how SEA is used to support NVH development at different stages.

Statistical Energy Analysis (SEA) vehicle models are well-accepted tools for predicting the high-frequency interior acoustic effects of a design change to the structure or sound package of the vehicle. [1] SEA models do not strongly depend on geometric details, which allows SEA to be uniquely used as an analysis tool very early in the vehicle design phase to identify potential Noise, Vibration, and Harshness (NVH) issues caused by proposed changes to acoustic or vibration source levels, component materials, construction details, or sound package details of the vehicle. SEA models can also be used to suggest alternatives while the vehicle is still in the development stages to compensate for a predicted or known degradation to NVH in a vehicle due to a design or source level change. This paper presents a case study in which validation testing and an SEA model were combined to obtain recommendations for the most effective sound package changes to meet NVH targets.