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As the vehicle and wind speeds and directions change, the unsteady flow creates non-stationary wind noise. To investigate people’s perceptions of non-stationary wind noise, a method to simulate the non-stationary wind noise is needed. Previously, a method was developed that used stationary recordings taken at several speeds and directions to create a set of sound pressure level predictions in each one-third octave band that are a function of wind speed and direction. These functions are used to create time-varying filters based on provided wind profiles. A reference wind noise measurement is then filtered to produce the sounds. A drawback of this method is that many stationary wind condition measurements are needed to form accurate sound pressure level functions, which can be time consuming. A method requiring fewer measurements was investigated.

Component sound quality is an important factor in the design of competitive diesel engines. One component noise that causes complaints is the gear rattle that originates in the front-of-engine gear train which drives the fuel pump and other accessories. The rattle is caused by repeated tooth impacts resulting from fluctuations in differential torsional acceleration of the driving gears. These impacts generate a broadband, impulsive noise that is often perceived as annoying. In most previous work, the overall sound quality of diesel engines has been considered without specifically focusing on predicting the perception of gear rattle. Gear rattle level has been quantified based on angular acceleration measurements, but those measurements can be difficult to perform. Here, the emphasis was on developing a metric based on subjective testing of the perception of gear rattle.

Flexible polyurethane foam is the main cushioning element used in car seats. Optimization of an occupied seat's static and dynamic behavior requires models of foam that are accurate over a wide range of excitation and pre-compression conditions. In this research, a method is described to estimate the parameters of a global model of the foam behavior from data gathered in a series of impulse tests at different settling points. The estimated model is capable of describing the responses gathered from all the impulse tests using a unique set of parameters. The global model structure includes a nonlinear elastic term and a hereditary viscoelastic term. The model can be used to predict the settling point for each mass used and, by expanding the model about that settling point, local linear models of the response to impulsive excitation can be derived. From this analysis the relationship between the local linear model parameters and the global model parameters is defined.

The identification of the dominant noise sources in diesel engines and the assessment of their contribution to far-field noise is a process that can involve both fired and motored testing. In the present work, the cross-spectral densities of signals from cylinder pressure transducers, accelerometers mounted on the engine surface, and microphones (in the near and far fields), were used to identify dominant noise sources and estimate the transfer paths from the various “inputs” (i.e., the cylinder pressures, the accelerometers and the near field microphones) to the far field microphones. The method is based on singular value decomposition of the input cross-spectral matrix to relate the input measurements to independent virtual sources. The frequencies at which a particular input is strongly affected by an independent source are highlighted, and with knowledge of transducer locations, inferences can be drawn as to possible noise source mechanisms.

Vehicle occupants are exposed to low frequency vibrations which can adversely affect the ride comfort. Exposure to vibrations can also lead to problems ranging from fatigue and lower back pain to more serious issues like injuries to the spine. The transmission of vibration to seated occupants can be controlled by appropriately designing car seats, which requires a deep understanding of the seat-occupant system behavior. A seat-occupant system is composed of two main components: the seat and the occupant. A key element in the seat, which is a challenge to model, is the flexible polyurethane foam in the seat cushion, which is a nonlinear and viscoelastic material exhibiting behavior on multiple time-scales. The multi-body occupant model is also geometrically nonlinear. The combined model also incorporates profiles of the seat and the occupant, and includes relatively simple friction models at the occupant and seat interfaces.

Polyurethane foam is often a major constituent of automotive seating, and exhibits highly nonlinear behavior under normal operating conditions. Efficient design requires an understanding, as well a good model, of the foam behavior. The work presented here is an attempt to link continuum and microstructural approaches to modeling foamed materials and take advantage of the utility in each. The outcome will ultimately be the ability to generate a foam superelement that is sensitive to microstructural properties but does not require the computational complexity of a microstructural finite element model. This will facilitate the iterative design of seating for comfort and other dynamic considerations. To this end, an Ogden-type continuum model for compressible rubber-like solids, is fitted to the results of numerous simulated compression tests conducted on finite element models of two-dimensional foam.

Hip joint location (H-point) is an important design specification used by car seat manufacturers. Since most of the modern car seats are full-foam seats, the H-point location is primarily dependent on the quasi-static behavior of foam which is a highly nonlinear and viscoelastic material. In this work, a constitutive model is developed for flexible polyurethane foam. The stiffness characteristics of foam are described by a polynomial in displacement and the viscoelastic behavior is described by a convolution of the response with a kernel which is assumed to be a sum of exponentials. A system identification procedure, based on linear least squares fitting and ARMA modeling, is developed to identify the parameters from data collected in quasi-static foam experiments.

In recent years, Nearfield Acoustical Holography (NAH) has been used to identify stationary vehicle exterior noise sources. However that application has usually been limited to individual components. Since powertrain noise sources are hidden within the engine compartment, it is difficult to use NAH to identify those sources and the associated partial field that combine to create the complete exterior noise field of a motor vehicle. Integrated Nearfield Acoustical Holography (INAH) has been developed to address these concerns: it is described here. The procedure entails sensing the sources inside the engine compartment by using an array of reference microphones, and then calculating the associated partial radiation fields by using NAH. In the second part of this paper, the use of farfield arrays is considered. Several array techniques have previously been applied to identify noise sources on moving vehicles.

An overview of model development for seated occupants is presented. Two approaches have been investigated for modeling the vertical response of a seated dummy: finite element and simplified mass-spring-damper methods. The construction and implementation of these models are described, and the various successes and drawbacks of each modeling approach are discussed. To evaluate the performance of the models, emphasis was also placed on producing accurate, repeatable measurements of the static and dynamic characteristics of a seated dummy.