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An IPTMS hardware facility has been established in the laboratories of the Aerospace Systems Directorate of the Air Force Research Laboratory (AFRL) at Wright-Paterson Air Force Base (WPAFB). This hardware capability was established to analyze the transient behavior of a high power Electrical Power System (EPS) coupled virtually to a Thermal Management System (TMS) under fast dynamic loading conditions. The system incorporates the use of dynamic electrical load, engine emulation, energy storage, and emulated thermal loads operated to investigate dynamics under step load conditions. Hardware architecture and control options for the IPTMS are discussed. This paper summarizes the IPTMS laboratory demonstration system, its capabilities, and preliminary test results.

In this research, excitation strategies for a salient-pole wound rotor synchronous machine are explored using a magnetic equivalent circuit model that includes core loss. It is shown that the excitation obtained is considerably different than would be obtained using traditional qd-based models. However, through evaluation of the resulting ‘optimal’ excitation, a relatively straightforward field-oriented type control is developed that is consistent with a desire for efficiency yet control simplicity. Validation is achieved through hardware experiment. The usefulness/applicability of the simplified control to variable speed applications is then considered.

As technology for both military and civilian aviation systems mature into a new era, techniques to test and evaluate these systems have become of great interest. To achieve a general understanding as well as save time and cost, the use of computer modeling and simulation for component, subsystem or integrated system testing has become a central part of technology development programs. However, the evolving complexity of the systems being modeled leads to a tremendous increase in the complexity of the developed models. To gain confidence in these models there is a need to evaluate the risk in using those models for decision making. Statistical model validation techniques are used to assess the risk of using a given model in decision making exercises. In this paper, we formulate a transient model validation challenge problem for an air cycle machine (ACM) and present a hardware test bench used to generate experimental data relevant to the model.