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Aircraft power demands continue to increase with the increase in electrical subsystems. These subsystems directly affect the behavior of the power and propulsion systems and can no longer be neglected or assumed linear in system analyses. The complex models designed to integrate new capabilities have a high computational cost. This paper investigates the possibility of using a hardware-in-the-loop (HIL) analysis with real time integration. A representative electrical power system is removed from a turbine engine model simulation and replaced with the appropriate hardware attached to a 350 horsepower drive stand. In order to update the model to proper operating conditions, variables are passed between the hardware and the computer model. Using this method, a significant reduction in runtime is seen, and the turbine engine model is usable in a real time environment. Scaling is also investigated for simulations to be performed that exceed the operating parameters of the drive stand.

As aircraft continue to increase their power and thermal demands, transient operation of the power and propulsion subsystems can no longer be neglected at the aircraft system level. The performance of the whole aircraft must be considered by examining the dynamic interactions between the power, propulsion, and airframe subsystems. Larger loading demands placed on the power and propulsion subsystems result in thrust, speed, and altitude transients that affect the aircraft performance and capability. This results in different operating and control parameters for the engine that can be properly captured only in an integrated system-level test. While it is possible to capture the dynamic interactions between these aircraft subsystems by using simulations alone, the complexity of the resulting system model has a high computational cost.

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.