Thermal modeling, analysis and control of a space suit

The thermal dynamics of two space suits, the Space Shuttle EMU and the MPLSS Advanced Space Suit, are considered as they relate to astronaut thermal comfort control. The activities documented in this dissertation cover three related areas, modeling, analysis, and control.; A detailed dynamic lumped capacitance thermal model of the operational Space Shuttle EMU is used to analyze the thermal dynamics of the system with observations verified using experimental and flight data. Prior to using the model to define performance characteristics and limitations for the space suit, the model is first evaluated and improved. This evaluation includes determining the effect of various model parameters on model performance and quantifying various temperature prediction errors in terms of heat transfer and heat storage. The thermal dynamics and design of an Advanced Space Suit are next considered. A transient model of the MPLSS Advanced Space Suit design is developed and implemented using MATLAB/Simulink, to help with sizing, with design evaluation, and with the development of an automatic thermal comfort control strategy. The model is described and the thermal characteristics of the Advanced Space Suit are investigated including various parametric design studies. The steady state performance envelope for the Advanced Space Suit is defined in terms of the thermal environment and human metabolic rate and the transient response of the human-suit-MPLSS system is analyzed.; The observations and insights about the thermal dynamics of a space suit are then applied to the automatic thermal comfort control of the MPLSS Advanced Space Suit. Automatic thermal comfort control for the Advanced Space Suit is investigated using three proposed strategies. These strategies use a transient thermal comfort definition based on body heat storage. The first strategy is measurement based using a proposed body heat storage estimation method to determine the astronaut's thermal state. The second strategy is model based using a model to determine the desired liquid cooling garment inlet temperature to provide thermal comfort. The third strategy is a hybrid strategy combining the measurement based and model based approach using the Generalized Predictive Control framework. Each strategy then uses a resource allocation decision logic to determine which of three control mechanisms to use so that thermal comfort can be provided while minimizing the use of consumables. Accuracy and performance of the strategies are evaluated using simulations, highlighting their advantages and limitations.