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Future more electric aircraft (MEA) architectures that improve electrical power system's (EPS's) source and load utilization will require advance stability analysis capabilities. Systems are becoming more complex with bidirectional flows from power regeneration, multiple sources per channel and higher peak to average power ratios. Unknown load profiles with large transients complicate common stability analysis techniques. Advancements in analysis are critical for providing useful feedback to the system integrator and designers of multi-source, multi-load power systems. Overall, a framework for evaluating stability with large displacement events has been developed. Within this framework, voltage transient bounds are obtained by identifying the worst case load profile. The results can be used by system designers or integrators to provide specifications or limits to suppliers. Subsystem suppliers can test and evaluate their design prior to integration and hardware development.

Analyzing and maintaining power quality in an electrical power system (EPS) is essential to ensure that power generation, distribution, and loads function as expected within their designated operating regimes. Standards such as MIL-STD-704 and associated documents provide the framework for power quality metrics that need to be satisfied under varying operating conditions. However, analyzing these power quality metrics within a fully integrated EPS based solely on measurements of relevant signals is a different challenge that requires a separate framework containing rules for data acquisition, metric calculations, and applicability of metrics in certain operating conditions/modes. Many EPS employed throughout industry and government feature various alternating-current (ac) power systems.

Electrical and mechanical failures (such as bearing, winding and rotating-diode failures) combine to cause premature failures of the generators, which become a flight safety issue forcing the crew to land as soon as practical. Currently, diagnostic / prognostic technologies are not implemented for aircraft generators where repairs are time-consuming and costly. This paper presents the development of feature extraction and diagnostic algorithms to 1) differentiate between these failure modes and normal aircraft operational modes; and 2) determine the degree of damage of a generator. Electrical signature analysis (ESA) based time-domain features were developed to distinguish between healthy and degraded generators while taking into account their operating conditions. Frequency-domain based ESA techniques are used to identify the degraded components within the generators.

More electric aircraft (MEA) architectures have increased in complexity leading to a demand for evaluating the dynamic stability of their advanced electrical power systems (EPS). The system interactions found therein are amplified due to the increasingly integrated subsystems and on-demand power requirements of the EPS. Specifically, dynamic electrical loads with high peak-to-average power ratings as well as regenerative power capabilities have created a major challenge in design, control, and integration of the EPS and its components. Therefore, there exists a need to develop a theoretical framework that is feasible and useful for the specification and analysis of the stability of complex, multi-source, multi-load, reconfigurable EPS applicable to modern architectures. This paper will review linear and nonlinear system stability analysis approaches applicable to a scalable representative EPS architecture with a focus on system stability evaluation during large-displacement events.

The electrical and mechanical failures (such as bearing and winding failures) combine to cause premature failures of the generators, which become a flight safety issue forcing the crew to land as soon as practical. Currently, diagnostic / prognostic technologies are not implemented for aircraft generators where repairs are time consuming and its costs are high. This paper presents the development of feature extraction and diagnostic algorithms to ultimately 1) differentiate between these failure modes and normal aircraft operational modes; and 2) determine the degree of damage of a generator. Electrical signature analysis based features were developed to distinguish between healthy and degraded generators while taking into account their operating conditions. The diagnostic algorithms were developed to have a high fault / high-hour detection rate along with a low false alarm rate.

An onboard Acoustic Wiring Diagnostic System to monitor the health of aircraft wiring is under development by Innovative Dynamics Inc. The AWDS incorporates passive acoustic sensors to monitor wire chafing. The system operates continuously in-flight so that intermittent wiring fault conditions can be detected as they happen. Trend analysis data can be logged to enable pro-active maintenance prior to catastrophic failure. A key advantage of the in-situ system is to perform the inspection without removing or disconnecting the wiring. Acoustic signatures of representative aircraft wiring have been characterized under simulated damage conditions. Flight ready hardware and software have been developed and flight testing is underway on an H-53 helicopter. This paper will present the wire diagnostic approach, the AWDS flight instrumentation, and some representative lab test results.

The electrical and mechanical failures (such as bearing and winding failures) combine to cause premature failures of the generators, which become a flight safety issue forcing the crew to land as soon as practical. Currently, diagnostic / prognostic technologies are not implemented for aircraft generators where repairs are time consuming and its costs are high. This paper presents the development of several algorithms to differentiate between these failure modes and normal aircraft operational modes, determine the degree of damage and remaining life of a generator. P-3 generator data (vibrations & phase voltages/currents) were collected for a seeded bearing failure involving lubrication defects in main bearing system. The results show that the frequency domain analysis of the generator's phase voltage can be used to detect its general health and impending bearing failures.

Fuel cells have been under considerable interest for both commercial and military aviation applications for power generation needed for advanced computational and communication systems on board aircraft, as well as for other power requirements needed both while in flight and on the ground. However, in order to power the fuel cells, hydrogen must be generated at some point, the ideal source being the logistic fuels such as JP-5 or JP-8 that is already used for propulsion. This process is not trivial, as several potential issues can arise from processing logistic fuel, the two primary concerns being the effect of sulfur within the fuel on the processing and fuel cell components, and the longevity issues resulting from coke formation during fuel processing. In the first part of this paper, we look as work that we have performed that addresses some of these issues for the steam reforming of JP-5 to produce pure hydrogen for fuel cell use.

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.