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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.

Engineers doing squeak and rattle testing of instrument panels (IP's) have successfully used large electrodynamic vibration systems to identify sources of squeaks and rattles (S&R's). Their successes led to demands to test more IP's, i.e., to increase throughput of IP's to reflect the many design, material, and/or manufacturing process changes that occur, and to do so at any stage of the development, production, or QA process. What is needed is a radically different and portable way to find S&R's in a fraction of the time and at lower capital cost without compromising S&R detection results.

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).

Automotive outside rear view mirror shape has become an important consideration in achieving wind noise and aerodynamic performance objectives. This paper describes a two step process used to develop a mirror shape which meets both wind noise and aerodynamic objectives. First, basic understanding of door mounted verses sail mounted mirrors and shape parameters was obtained by evaluating selected shapes and studying their physical measurements relative to their measured responses. Relationships between the wind noise and drag responses revealed performance range limitations for sail mounted mirrors. Second, a central composite experimental design was utilized to more closely investigate door mounted mirror shape parameters to determine optimal mirror performance potential. The resulting empirical models developed were used to determine the best overall solution.

Wind noise is the sound made as air rushes over a moving vehicle. As other vehicle sound sources are improved, the wind noise becomes the dominant source under certain conditions. The purpose of this paper is to examine the relationship between the properties of wind noise and the human perception of this sound.We find that a particular loudness measure (Zwicker loudness as defined in IS0532B) is the prime factor governing the customer perception of wind noise.

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.

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.

A series of tests have been performed on a production vehicle to determine the characteristics of the external turbulent flow field in wind tunnel and road conditions. Empirical formulas are developed to use the measured data as source levels for a Statistical Energy Analysis (SEA) model of the vehicle structural and acoustical responses. Exterior turbulent flow and acoustical subsystems are used to receive power from the source excitations. This allows for both the magnitudes and wavelengths of the exterior excitations to be taken into account - a necessary condition for consistently accurate results. Comparisons of measured and calculated interior sound levels show good correlation.

Panel acoustic contribution analysis (PACA) is an advanced engineering tool to improve the NVH quality of vehicles. Using PACA areas of vehicle body panels are categorized according to their contribution to the total sound. Positive contribution areas increase the sound level as vibration amplitude increases, negative contribution areas decrease the sound level as vibration amplitude increases, and neutral areas have no significant effect on the sound level. This knowledge is important to guide vehicle NVH refinement. This paper presents the technical approach of PACA and the results of an experiment used to validate the PACA techniques. Vehicle application results to improve NVH quality and reduce weight are also included.

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.

Brake related warranty costs are a major concern to the automotive industry. Large part of these costs are due to noise, more particularly due to the brake squeal complaints. Computer-aided engineering solutions have attracted a lot of attention from the engineering and development community for more effective brake product development. Recently, three brake squeal analysis methods were implemented on disc type brakes in a vehicle program at Ford. This paper summarizes the results and documents the experience obtained during implementation in the vehicle CAE process.

This paper describes an investigation into the sound quality of passenger car and light truck closure sounds. The closure sound events that were studied included side doors, hoods, trunklids, sliding doors, tailgates, liftgates, and fuel filler doors. Binaural recordings were made of the closure sounds and presented to evaluators. Both paired comparison of preference and semantic differential techniques were used to subjectively quantify the sound quality of the acoustic events. Major psychoacoustic characteristics were identified, and objective measures were then derived that were correlated to the subjective evaluation results. Regression analysis was used to formulate models which can quantify customers perceptions of the sounds based on the objectively derived parameters. Many times it was found that the peak loudness level was a primary factor affecting the subjective impression of component quality.

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.