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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.

Experimental Hardware-in-the-loop (xHIL) testing utilizing signal and/or power emulation imposes a hard real-time requirement on models of emulated subsystems, directly limiting their fidelity to what can be achieved in real-time on the available computational resources. Most real-time simulators are CPU-based, for which the overhead of an instruction-set architecture imposes a lower limit on the simulation step size, resulting in limited model bandwidth. For power-electronic systems with high-frequency switching, this limit often necessitates using average-value models, significantly reducing fidelity, in order to meet the real-time requirement. An alternative approach emerging recently is to use FPGAs as the computational platform, which, although offering orders-of-magnitudes faster execution due to their parallel architecture, they are more difficult to program and their limited fabric space bounds the size of models that can be simulated.

This paper introduces a method for conducting experimental hardware-in-the-loop (xHIL), in which behavioral-level models are coupled with an advanced power emulator (APE) to emulate an electrical load on a power generation system. The emulator is commanded by behavioral-level models running on an advanced real-time simulator that has the capability to leverage Central Processing Units (CPUs) and field programmable gate arrays (FPGA) to meet strict real-time execution requirements. The paper will be broken down into four topics: 1) the development of a solution to target behavioral-level models to an advanced, real-time simulation device, 2) the development of a high-bandwidth, high-power emulation capability, 3) the integration of the real-time simulation device and the APE, and 4) the application of the emulation system (simulator and emulator) in an xHIL experiment.