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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.

The combination of increasing performance demands, increasing system complexity, and the need for reduced program development schedule and budget costs in the aerospace industry is driving engineers to increasingly rely upon modeling, simulation, and analysis (MS&A) in the platform development cycle. One approach to ensuring that such integrated system simulations remain computationally tractable is co-simulation utilizing technology found in commercially available packages, such as PC Krause and Associates, Inc.'s (PCKA's) Distributed Heterogeneous Simulation (DHS) / FastSim software. In such co-simulation environments, dynamic models are executed in independent model spaces, with coupling between subsystems achieved by exchanging a minimal set of required data typically found at subsystem boundaries.

Two recent enhancements to Distributed Heterogeneous Simulation (DHS) are variable communication rates and higher-order predictors. Variable communication automatically controls the communication interval between any two subsystems in an attempt to achieve a desired accuracy during transient periods and maximize speed during steady-state periods. Higher-order predictors can better estimate the values of exchanged variables between data exchange instances, which can improve accuracy and possibly require fewer exchanges. A comparison between a single-computer simulation of an aircraft electric power system and an equivalent three-computer DHS show that the variable communication technique enables more accuracy and higher speed distributed simulations than fixed-step communication. In addition, higher-order predictors are shown to increase accuracy in some cases.

Design of modern aircraft relies heavily on modeling and simulation for reducing cost and improving performance. However, the complexity of aircraft architectures requires accurate modeling of dynamic components across many subsystems. Integrated power and thermal modeling necessitates dynamic simulations of liquid, air, and two-phase fluids within vapor cycle system components, air cycle machine and propulsion components, hydraulic components, and more while heat generation of many on-board electrical components must also be precisely calculated as well. Integration of these highly complex subsystems may result in simulations which are too computationally expensive for quickly modeling extensive variations of aircraft architecture, or will require simulations with reduced accuracy in order to provide computationally inexpensive models.