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To support research and analysis requirements in the development of future hybrid-electric drive systems, a flexible and efficient means of predicting the dynamic performance of large-scale multi-disciplinary systems prior to hardware trials is crucial. With the development of Distributed Heterogeneous Simulation (DHS), the technology now exists to enable this type of investigation. Previously, DHS was shown to allow the interconnection of component simulations running on a single computer or networked computers and developed using any combination of a variety of commercial-off-the-shelf software packages. The US Army is interested in using the Simplorer software product from Ansoft Corporation to model various subsystems that are incorporated with such vehicle system simulations. In this paper, the DHS technique is expanded to support the Simplorer software package; thus, allowing subsystem models developed using this tool to be interconnected to form a dynamic system simulation.

This paper describes a coupled-circuit physical-variable modeling of multiphase induction motors. The presented modeling interface makes it straightforward to implement an induction machine with arbitrary number of phases and/or phase groups on the stator and the rotor. The 3-, 6-, and 9-phase motors are simulated and compared. It is shown that machines with higher number of phases have less severe torque pulsation and the stator current increase following a loss of one phase. For the 9-phase machine, several studies involving loss of multiple phases are also presented, wherein the relative location of the faulted phases is shown to have a significant impact on redistribution of currents and resulting electromagnetic torque. The proposed models can be used to represent induction motors and generators for transient studies involving multiple faults, system-level reconfiguration, and survivability.

In this paper, a parametric average-value modeling approach is applied to a high-frequency six-phase aircraft generation subsystem. This approach utilizes a detailed switch-level model of the system to numerically establish the averaged dynamic relationships between the ac inputs of the rectifier and the dc-link outputs. A comparison between the average-value and detailed models is presented, wherein, the average-value model is shown to accurately portray both the large-signal time-domain transients and the small-signal frequency-domain characteristics. Since the discontinuous switching events are not present in the average-value model, significant gains can be realized in the computational performance. For the study system, the developed average-value simulation executed more than two orders of magnitude faster than the detailed simulation.

Average-value models are commonly used in the design and analysis of power electronic-based systems as a method of portraying the overall system dynamics while neglecting discontinuities that arise from switching. Although numerous averaging methodologies have been developed to eliminate discontinuities, they are typically limited to specific circuits operating in specific modes. Therefore, substantial analytical effort is generally required to select an appropriate averaging technique and develop the corresponding average-value model that is valid for a given converter. To reduce this effort, an automated averaging technique is set forth in which an averaged model is established via coupling with a detailed simulation of the system.

An allocation algorithm for optimally assigning the various subsystem simulations, within a distributed heterogeneous simulation, to a specific set of computational resources has been developed. This algorithm uses a cost function that approximates the simulation execution time for each of the subsystems based upon the model complexity and the performance parameters of the available computer resources. The cost function is then evaluated to determine the optimal allocation that ensures the overall simulation execution time is minimized. In this paper, the allocation algorithm is applied to a large-scale power-electronic-based aircraft electrical power system. This study system is comprised of ten component simulations that together are modeled by 85 state variables and include 74 switching devices. Both optimal and sub-optimal allocations are considered and the predicted simulation run times are verified experimentally.