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CAE capabilities have long been used for performing static and dynamic structural analysis during the seat design process. More recently, the soft parts of the seat including foams, trim and suspension have also been modeled with CAE. The purpose of this modeling is to better understand the physical phenomena which are involved in the sitting process, to enhance seat design knowledge, and to replace as much physical testing during the design process with virtual, CAE testing. This paper presents the first part of a multi-phased, both experimental and numerical project. The aim of this first stage is to assess the capabilities of a CAE methodology to predict FMVSS 202a backset. Based on CAD data, a finite element mesh of the seat was built. The mechanical behavior of all parts was characterized through experiments on material samples.

This paper presents the second part of a multi-phased, both experimental and numerical project, devoted to the use of Virtual Prototyping techniques for seat design. The aim of this stage is to assess the capabilities of a CAE methodology to predict some comfort-related mechanical parameters, such as overall hardness and plushness, as a base engineering approach to quantify an occupant perception of both long- and short-term comfort. For hardness, a simple human surrogate (SAE AM50 Buttock Form) is applied on the bottom cushion of a fully trimmed, current production FORD seat, following a load cycle. For initial softness, a round probe is indented at different locations of both backrest and bottom cushions, following loading cycles. The resulting load-deflection curves predicted by numerical simulation are in good agreement with the experimental ones.

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.

Many studies have been conducted and supporting literature has been published to better understand thermal comfort for the automotive environment, particularly, for the HVAC system within the cabin. However, reliable assessment of occupant thermal comfort for seating systems has lacked in development and understanding. Evaluation of seat system performance in terms of comfort has been difficult to quantify and thus most tests have been established such that the hardware components are tested to determine if the thermal feature does no harm to the customer. This paper evaluates the optimal seat surface temperature range to optimize human thermal comfort for an automotive seating system application for heated and ventilated seats.

Thermal comfort in automotive seating has been studied and discussed for a long time. The available research, because it is focused on the components, has not produced a model that provides insight into the human-seat system interaction. This work, which represents the beginning of an extensive research program, aims to establish the foundation for such a model. This paper will discuss the key physiological, psychological, and biomechanical factors related to perceptions of thermal comfort in automotive seats. The methodology to establish perceived thermal comfort requirements will also be presented and discussed.

Load deflection testing is one type of test that can be used to understand the comfort performance of a complete trimmed automotive seat. This type of testing can be conducted on different areas of the seat and is most commonly used on the seatback, the seat cushion and the head restraint. Load deflection data can be correlated to a customer’s perception of the seat, providing valuable insight for the design and development team. There are several variables that influence the results obtained from this type of testing. These can include but are not limited to: seat structure design, suspension system, component properties, seat materials, seat geometry, and test set-up. Set-up of the seat for physical testing plays a critical role in the final results. This paper looks at the relationship of the load deflection data results on front driver vehicle seatbacks in a supported and unsupported test set-up condition.

Traditional automotive seat development has relied on a series of physical prototypes that are evaluated and refined in an iterative fashion. Costs are managed by sharing prototypes across multiple attributes. To further manage costs, many OEMs and Tier 1s have, over the past decade, started to investigate various levels of virtual prototyping. The change, which represents a dramatic paradigm shift, has been slow to materialize since virtual prototyping has not significantly reduced the required number of physical prototypes. This is related to the fact virtual seat prototyping efforts have been focused on only selected seat attributes - safety / occupant positioning and mechanical comfort are two examples. This requires that physical prototypes still be built for seat attributes like craftsmanship, durability, and thermal comfort.

Thermophysical properties of materials used in the design of automotive interiors are needed for computer simulation of climate conditions inside the vehicle. These properties are required for assessment of the vehicle occupants' thermal sensation as they come in contact with the vehicle interior components, such as steering wheels, arm rests, instruments panel and seats. This paper presents the results of an investigation into the thermophysical properties of materials which are required for solving the non-linear Fourier equations with any boundary conditions and taking into account materials' specific heat, volume density, thermal conductivity, and thermal optical properties (spectral and total emissivity and absorptivity). The model and results of the computer simulation will be published in a separate paper.

Position of the H-point plays a vital role during designing the seating system. The seating system provides support and comfort to the occupants while they are operating the vehicle. The traditional way to design a seat system is to use rules of thumb and experience, which often results in several costly design iterations. The purpose of this paper is to demonstrate the capability of CAE analytical tool to find the H-point at the early phase of the seating system design without compromising the comfort level of the occupant. The recently launched Lincoln Continental front seating system was used to validate this purpose. The Continental seating system has unique design features which provide special challenges in designing and simulating the seat. With the help of CAE analytical tool, the traditional process is streamlined and a seat design could be achieved in a shorter period with greater accuracy.

The demand for seating comfort is growing - in cars as well as trucks and other commercial vehicles. This is expected as the seat is the largest surface area of the vehicle that is in contact with the occupant. While it is predominantly luxury cars that have been equipped with climate controlled seats, there is now a clear trend toward this feature becoming available in mid-range and compact cars. The main purpose of climate controlled seats is to create an agreeable microclimate that keeps the driver comfortable. It also reduces the “stickiness” feeling which is reported by perspiring occupants on leather-covered seats. As part of the seat design process, a physical test is performed to record and evaluate the life cycle and the performance at ambient and extreme temperatures for the climate controlled seats as well as their components. The test calls for occupied and unoccupied seats at several ambient temperatures.

In many fields of technology, examinations of the past can provide insights into the future. This paper reviews the last 20 years of automotive seat comfort development and research as chronicled by SAE’s session titled “Human Factors in Seating Comfort”. Records suggest that “Human Factors in Seating Comfort” has existed as a separate session at SAE’s World Congress since 1999. In that time there have been 148 unique contributions (131 publications). The history is fascinating because it reflects interests of the time that are driven by technology trends, customer wants and needs, and new theories. The list of contributors, in terms of authors and their affiliations, is also telling. It shows shifts in business models and strategies around collaboration. The paper ends with a discussion of what can be learned from this historical review and the major issues to be addressed. One of the more significant contributions of this paper is the reference list.

Seat assessment is an important necessity for the growing auto industry. The design of seats is driven by customer’s demand of comfort and aesthetics of the vehicle interiors. Some of the few seat assessments are H-point prediction with H-point Machine (HPM); backset prediction with Head Restraint Measuring Device (HRMD); seat hardness and softness. Traditional seat development was through developing series of prototypes to meet requirements which involved higher costs and more time. The seat requirement of H-Point measurement is of focus in this paper. Though there are other commercial available software/methods to perform the H-point measurement simulations, the aim here was to assess the capabilities of an alternate Computer Aided Engineering (CAE) methodology using CAE tools - PRIMER and LS-Dyna. The pre-processing tools - Hypermesh and ANSA have been used for modeling and Hyperview tool used for reviewing the simulations.