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MIL-STD-704 defines power quality in terms of transient, steady-state, and frequency-domain metrics that are applicable throughout a military aircraft electric power system. Maintaining power quality in more electric aircraft power systems has become more challenging in recent years due to the increase in load dynamics and power levels in addition to stricter requirements of power system characteristics during a variety of operating conditions. Further, power quality is often difficult to assess directly during experiments and aircraft operation or during data post-processing for the integrated electric power system (including sources, distribution, and loads). While MIL-STD-704 provides guidelines for compliance testing of electric load equipment, it does not provide any instruction on how to assess the power quality of power sources or the integrated power system itself, except the fact that power quality must be satisfied throughout all considered operating conditions.

As the cost and complexity of modern aircraft systems increases, emphasis has been placed on model-based design as a means for reducing development cost and optimizing performance. To facilitate this, an appropriate modeling environment is required that allows developers to rapidly explore a wider design space than can cost effectively be considered through hardware construction and testing. This wide design space can then yield solutions that are far more energy efficient than previous generation designs. In addition, non-intuitive cross-coupled subsystem behavior can also be explored to ensure integrated system stability prior to hardware fabrication and testing. In recent years, optimization of control strategies between coupled subsystems has necessitated the understanding of the integrated system dynamics.

Future aircraft systems are projected to have order of magnitude greater power and thermal demands, along with tighter constraints on the performance of the power and thermal management subsystems. This trend has led to the need for a fully integrated design process where power and thermal systems, and their interactions, are considered simultaneously. To support this new design paradigm, a general framework for codifying and checking specifications and requirements is presented. This framework is domain independent and can be used to translate requirement language into a structured definition that can be quickly queried and applied to simulation and measurement data. It is constructed by generalizing a previously developed power quality analysis framework. The application of this framework is demonstrated through the translation of thermal specifications for airborne electrical equipment, into the SPecification And Requirement Evaluation (SPARE) Tool.

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.

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.

The interdependency between propulsion, power, and thermal subsystems on military aircraft such as the F-35 Joint Strike Fighter (JSF) and F-22 Raptor continues to increase as advanced war-fighting capabilities including solid-state radars, electronic attack, electric actuation, and Directed Energy Weaponry (DEW) expand to meet Air Force needs. Novel analysis and testing methodologies are required to predict these interdependencies and address adverse interactions prior to costly hardware prototyping. As a result, the Air Force Research Laboratory (AFRL) has established a dynamic hardware-in-the-loop (HIL) test-bed wherein transient simulations can be integrated through advanced real-time simulation with prototype hardware for integrated system studies and analysis. This paper details a test-bed configuration where a dynamic simulation of an aircraft turbine engine is utilized to control a dual-head electric drive stand.

Directed Energy weapon (DEW) systems are being developed for both ground and airborne applications. Typically, they consist of microwave or laser powered guns. Both the microwave application and the diode based laser applications require significant amount of power. This power ranges from several hundred kilowatts (kW) for microwave applications to Megawatts (MW) for laser applications. The laser application requires that the full power be available for short duration, typically 5 seconds, which could be repeated several times with short pauses in between. The control of a generator, which delivers Megawatt of the intermittent power greatly differs from the of normal steady state generator control. It poses significant challenges. Application of power (and for this matter its removal) is a transient phenomenon that takes time and its effects ripple through the whole system.

Advancements in electrical, mechanical, and structural design onboard modern more electric aircraft have added significant stress to the electrical systems. An electrical system level analysis tool has been created in MATLAB/Simulink to facilitate rapid system analysis and optimization to meet the growing demands of modern aircraft. An integratated model of segment level models of an electrical system including a generator, electrical accumulator unit, electrical distribution unit and electromechanical actuators has been developed. Included in the model are mission level models of an engine and aircraft to provide relevant boundary conditions. It is anticipated that the tracking of the electrical distribution through numerical integration of these various subsystems will lead to more accurate predictions of the bus power quality. In this paper the tool is used to evaluate two architectures using two different load profiles.

The trend of moving towards model-based design and analysis of new and upgraded aircraft platforms requires integrated component and subsystem models. To support integrated system trades and design studies, these models must satisfy modeling and performance guidelines regarding interfaces, implementation, verification, and validation. As part of the Air Force Research Laboratory's (AFRL) Integrated Vehicle and Energy Technology (INVENT) Program, standardized modeling and performance guidelines have been established and documented in the Modeling Requirement and Implementation Plan (MRIP). Although these guidelines address interfaces and suggested implementation approaches, system integration challenges remain with respect to computational stability and predicted performance over the entire operating region for a given component. This paper discusses standardized model evaluation tools aimed to address these challenges at a component/subsystem level prior to system integration.

Model based design is a standard practice within the aerospace industry. However, the accuracies of these models are only as good as the parameters used to define them and as a result a great deal of effort is spent on model tuning and parameter identification. This process can be very challenging and with the growing complexity and size of these models, manual tuning is often ineffective. Many methods for automated parameter tuning exist. However, for aircraft systems this often leads to large parameter search problems since frequency based identification and direct gradient search schemes are generally not suitable. Furthermore, the cost of experimentation often limits one to sparse data sets which adds an additional layer of difficulty. As a result, these search problems can be highly sensitive to the definition of the model fitness function, the choice of algorithm, and the criteria for convergence.

Advanced tactical aircraft and their propulsion systems produce an order of magnitude more heat than legacy designs and offer fewer viable heat rejection opportunities. The current approach uses aircraft fuel as a primary heat sink which is either cooled by ram air and returned to the aircraft, or rejected off the aircraft when burned by the engine. Traditionally, aircraft have been limited in mission capability by the design performance and the available fuel quantity; however, potential thermal limitations have presented a new mission challenge. Joker and bingo range notifications based on fuel quantity remaining are common on modern fighters to ensure the pilot has the foresight to complete a mission segment and return to base before running out of fuel. Now, pilots may need to consider the possibility of a similar thermal joker/bingo concept until alternative LO heat rejection methods are discovered that remove limitations.

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.

Future Air Force intelligence, surveillance, and reconnaissance (ISR) platforms, such as high-altitude Uninhabited Aerial Vehicles (UAV), may drastically change the requirements of aircraft power systems. For example, there are potential interactions between large pulsed-power payloads and the turbine engine that could compromise the operation of the power system within certain flight envelopes. Until now, the development of large-scale, multi-disciplinary (propulsion, electrical, mechanical, hydraulic, thermal, etc.) simulations to investigate such interactions has been prohibitive due to the size of the system and the computational power required. Moreover, the subsystem simulations that are developed separately often are written in different commercial-off-the-shelf simulation programs.

In this paper, a MATLAB-Simulink based general co-simulation approach is presented which supports multi-resolution simulation of distributed models in an integrated architecture. This approach was applied to simulating aircraft thermal performance in our Vehicle Systems Model Integration (VSMI) framework. A representative advanced aircraft thermal management system consisting of an engine, engine fuel thermal management system, aircraft fuel thermal management system and a power and thermal management system was used to evaluate the advantages and tradeoffs in using a co-simulation approach to system integration modeling. For a system constituting of multiple interacting sub-systems, an integrated model architecture can rapidly, and cost effectively address technology insertions and system evaluations. Utilizing standalone sub-system models with table-based boundary conditions often fails to effectively capture dynamic subsystem interactions that occurs in an integrated system.

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.

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.

Advancement in modern aircraft with the development of more dynamic and efficient technologies has led to these technologies increasingly operated near or at their operation limits. More comprehensive analysis methods based on high-fidelity models co-simulated in an integrated environment are needed to support the full utilization of these advanced technologies. Furthermore, the additional information provided by these new analyses needs to be correlated with updates to traditional metrics and specifications. One such case is the thermal limit requirement that sets the upper bound on a thermal system temperature. Traditionally, this bound is defined based on steady-state conditions. However, advanced thermal management systems experience dynamic events where the temperature is not static and may violate steady-state requirements for brief periods of time.