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The automotive seating industry has established static pressure distribution criteria against which to evaluate seats. The technologies used for this purpose have, in most instances, been obtained and integrated without extensive consideration of the procedural aspects associated with the specific application. This makes it difficult to reduce the established criteria into seat design recommendations. This may, in part, explain the difficulty researchers are having demonstrating the link between static pressure distribution and subjective perceptions of comfort (i.e. establishing validity). This study, based on six separate investigations, provides specific recommendations concerning [1] system set-up, [2] subject selection, and [3] protocol execution (e.g. in-lab vs. in-vehicle).

This paper will explore the performance of two polyurethane foam formulations, one that is designed to be high resilient and one that is designed to be low resilient. The two formulations are placed into a full foam seat suspension. Data is generated with each formulation by a forced vibration test with a tekken mass, both at one point in time and over several hours to simulate in vehicle performance. The Seat Effectiveness Amplitude Transmissibility (SEAT) is read over a one-hour course that includes paved and rough roads, which is repeated three times for a total of three hours of data. This data is then compared to the foam data. The data shows that the low resilient foam will have some improvement in the paved roads but will have a vast improvement in the area of the rough roads. Data will be done by road to show the fatigue level occupant, road type, hour of the ride and drive and the foam type.

Digital human models have greatly enhanced design for the automotive driving environment. The major advantage of the models today is their ability to quickly test a broad range of the population within specific design parameters. The need to create expensive prototypes and run time consuming clinics can be significantly reduced. However, while the anthropometric databases within these models are comprehensive, the ability to position the manikins in a driving posture is limited. This study collected driving postures for occupants in two vehicle packages, a passenger car and utility-type vehicle. In all instances the occupant was instructed to adjust the vehicle parameters so they were in their most comfortable position. The posture of the occupants was then compared to postural output from RAMSIS and Catia V5 HumanBuilder.