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Preliminary investigations of nonlinear modeling of aircraft synchronous generators using neural networks are presented. Aircraft synchronous generators with high power density tend operate at current-levels proportional to the magnetic saturation region of the machine's material. The nonlinear model accounts for magnetic saturation of the generator, which causes the winding flux linkages and inductances to vary as a function of current. Finite element method software is used to perform a parametric sweep of direct, quadrature, and field currents to extract the respective flux linkages. This data is used to train a neural network which yields current as a function of flux linkage. The neural network is implemented in a Simulink synchronous generator model and simulation results are compared with a previously developed linear model. Results show that the nonlinear neural network model can more accurately describe the responsiveness and performance of the synchronous generator.

Modern military engines desire both the fuel efficiency of high-bypass turbofans and the high specific thrust of a low-bypass turbofan. Using traditional engine architectures, performance and efficiency are in conflict, so an engine is usually designed to best meet requirements for its primary mission. While the concept of a variable cycle engine is not new, recent advances in engine architecture technology suggest that adding a second bypass stream to a traditional turbofan can provide significant benefits. This “third stream” (the core flow being the primary stream and the inner bypass being the second stream) airflow can be independently modulated so that engine airflow demand can be matched with the available inlet flow at a variety of operating points, thereby reducing spillage drag. Additionally, the third stream air provides a valuable heat sink for cooling turbine cooling air or dissipating other aircraft heat loads.

Next generation aircraft will require more electrical power, more thermal cooling, and better versatility. To attain these improvements, technologies will need to be integrated and optimized at a system-level. The complexity of these integrated systems will require considerable analysis. In order to characterize and understand the implications of highly-integrated aircraft systems, the effects of pulsed-power, highly-transient loads, and the technologies that drive system-stability and behavior, an approach will be taken utilizing integrated modeling and simulation with hardware-in-the-loop (HIL). Such experiments can save time and cost and increase the general understanding of electrical and thermal phenomena as it pertains to aircraft systems before completing an integrated ground demonstration. As a first step toward completing an integrated analysis, a dynamometer “drive stand” was characterized to assess its performance.