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Seat Heater testing methods traditionally rely on a human subject to provide normal contact, load, and thermal conditions. This creates a thermal environment closer to what an actual customer might experience but it also introduces a variation from individual subject’s seating posture, body size, and metabolic differences. This paper describes the development and initial testing results of a passive, heated seat testing manikin (or HANIKIN) that is intended to replace human subjects for more meaningful, repeatable objective testing.

The H-point is a critical part of vehicle design as it is the basis for many engineering dimensions within the vehicle interior. A complete design process includes comparisons of the design to competitive benchmark vehicles. However, the competitive design considerations needed to determine the common standard H-point reference are often unknown. The SAE Human Accommodation and Design Devices (HADD) technical committee recently published a new standard benchmark SgRP procedure [2]. This new standard practice needed to be tested with respect to the accuracy and repeatability for determining the unknown h-point design parameters within industry benchmarking tolerances. In 2019, the SAE HADD committee conducted a study to evaluate the reproducibility of the new procedure. This paper presents detailed results of that study and discusses opportunities for applying the new benchmark practice.

This paper presents a method of controlling the seat heater using intentional oscillations between multiple, independently controlled temperatures (each with its own tolerance range). The amplitude and frequency of these oscillations can be changed based on secondary trigger events such as changes in the interior temperature. The benefits of using this technique to heat the seat surface are improved thermal sensation and reduced energy usage over the typical drive time.

Although subjective measurements are critical for qualifying seat comfort in terms of good or bad, objective measurements are the basis for quantifying these differences and ultimately controlling seat comfort performance through engineering design specs, targets, and/or guidelines. Many objective automotive seat comfort tools and techniques used today are based on methods derived in the past. This paper examines the engineering problems and solutions that make these historical influences relevant today. Particular focus is given to design considerations for the A-surface, B-surface, and the compressed surface of the seating system.

Optimizing climate seat systems requires increased complexity in seat design which in turn is driving a need for more detailed thermal simulation methods. This paper presents the model development considerations and results of a thermal simulation study aimed at improving the thermal seat comfort experience of Hyundai-Kia's heated seating systems.

Seat comfort is an important factor in the development of a vehicle; however, comfort can be measured in many ways. Many aspects of the experimental design such as the duration of the drive test, the questions asked, and the make-up of the test subjects are known to influence comfort results. This paper provides the background methodology and results of a Seat comfort study aimed at assessing long-term driving seat comfort.

Commercially available large-scale consumer surveys such as JD Power and Associates (JDPA) APPEAL Survey are often used to assess the success or failure of seat comfort design. Because access to the raw data from these surveys is limited, mean values are often the sole basis for analysis and comparison. Mean values alone, however, incompletely describe customer ratings that often lead to incorrect interpretation of the data. This can result in organizations expending capital to fix problems that do not exist. Since most companies have limited access to the raw data, this paper examines statistical and psychological factors that affect consumer survey results and describes methods for using these relationships to better interpret results of large scale, industry surveys.

Size is one of the most basic and important factors when determining fit for people. Many methods used to test occupant fit and accommodation rely on a traditional set of three different sized manikins - 5th, 50th and 95th percentiles. Anthropometry, the study of human size dimensions, however, is a complex multivariate problem. Real people, real drivers are a mixture of dimensions tall thin, short, stout, etc. This paper examines population anthropometry and these traditional percentiles specific to vehicular seat design.

Human models are viable methods of introducing human factors and ergonomic objectives into the design process at an early stage. Used correctly, they allow users to simulate and analyze potential human-machine interactions saving time and money. As with any model, mistakes can be made. The primary sources of error stem from incorrect use and misinterpretation of the results by the analyst. The development of three-dimensional human modeling software has only compounded these issues by adding a digital subject, itself a human model. This complicates the interpretation and use of these tools by layering one human model on top of another. The purpose of this paper is to highlight common categories of misuse and misinterpretation of digital human models as well as to propose a method for improving user understanding of human models through formal documentation of critical components.