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The prospect of using automatic control for astronaut thermal comfort regulation during extravehicular activity (EVA) requires an investigation of issues concerning the current state of the art of human thermal models. The analysis presented includes, but is not limited to, the discussion of assumptions and the accuracy, range and relative significance of parameters (e.g., thermal properties, physical dimensions, etc.) of transient human thermal models. The Wissler 1D model attracts primary consideration; however, there exists the appropriate inclusion of the 41-Node Man model for reflection and study.

The duration and frequency of extravehicular activity (EVA) is expected to increase with the anticipation of challenging missions ahead. This necessitates the development of an automatic controller for astronaut thermal comfort regulation. A reliable human thermal model is essential in order to predict the thermal response of subjects under various conditions to aid in automatic controller development. This paper examines thermal response sensitivity to several parameters and input modifications using a popular human thermal model. These parameter and input variations are based either on values reported in the literature or realistic estimates.

This paper discusses several issues related to the PLSS thermal model requirements for a planned generalized EVA Simulation Test Bed. The existing models of the extravehicular mobility unit (EMU) are briefly discussed and then the paper focuses specifically on the NASA JSC Shuttle EMU model (referred to as SINDA EMU). After the SINDA EMU model review, the PLSS thermal model requirements for the EVA Simulation Test Bed are discussed in detail.

NASA is funding a research project at the University of Missouri - Columbia as part of a more general effort to learn about the human physiological response to the types of exercise that astronauts perform on EVA missions. The authors created a dynamic state-space mathematical model representing the thermal behavior of the NASA environmental chamber located at the Ames Research Center. This model predicts chamber performance from which the authors identify modifications to the system which will improve its accuracy and usefulness. Simulation results closely match expected values for chamber performance. Recommendations are presented to improve chamber performance and instrumentation measurement accuracy.

Automatic thermal comfort control for the minimum consumables PLSS is undertaken using several control approaches. Accuracy and performance of the strategies using feedforward, feedback, and gain scheduling are evaluated through simulation, highlighting their advantages and limitations. Implementation issues, consumable usage, and the provision for the extension of these control strategies to the cryogenic PLSS are addressed.