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At a time where customer preference is becoming an important product development criteria, measures which quantify subjectively perceived auditory sensations are becoming useful in developing meaningful sound quality criteria. One proposed measure which has not yet seen a great deal of application to automotive sounds is that which attempts to quantify the sensation of roughness. The applicability of such a proposed measure can be established through a series of subjective experiments. Typically, such experiments involve the presentation and evaluation of a group of sounds which vary in their degree of roughness. In order to generate test sounds, a system for the modeling and synthesis of pawertrain sound has been developed which isolates specific signal components which are known to affect the roughness of a sound.

One factor believed to influence a customer's perception of vehicle performance is the powertrain sound. However, its influence relative to other factors, such as vehicle acceleration or transmission shift characteristics, remains largely unknown. Past studies of performance perception have either neglected the effect of powertrain sound, studied its effect independent of other factors (e.g., listening to powertrain sounds over headphones), or have confounded its effect with other factors. In this paper, we describe an in-vehicle system for methodically studying the influence of powertrain sound on a customer's perception of performance. The system is beneficial in that it allows the experimenter to electronically modify the sound associated with the powertrain while not affecting other possible performance factors. Results from a corresponding experiment are also presented, in which customers rated their perceived performance of the powertrain sounds.

Mathematical models which can aid in the design of monolithic oxidation catalyst systems are described. The chemistry math model allows prediction of tailpipe CO and HC emissions throughout the course of the Federal Test Procedure. Following a brief description of the model and its required inputs, several examples of model applications are presented. In these, the effects on emissions of several design variables are determined. The pressure drop model allows evaluation of system backpressure under steady flow conditions. Its use is illustrated by a parametric study of backpressure as a function of flow rate, substrate cell density and length.