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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.

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.

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.

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.

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.

Transient operating conditions in electrical systems not only have significant impact on the operating behavior of individual components but indirectly affect system and component reliability and life. Specifically, transient loads can cause additional loss in the electrical conduction path consisting of windings, power electronic devices, distribution wires, etc., particularly when loads introduce high peak vs. average power ratios. The additional loss increases the operating temperatures and thermal cycling in the components, which is known to reduce their life and reliability. Further, mechanical stress caused by dynamic loading, which includes load torque cycling and high peak torque loading, increases material fatigue and thus reduces expected service life, particularly on rotating components (shaft, bearings).

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.

The diverse and complex requirements of next-generation energy optimized aircraft (EOA) demand detailed transient and dynamic model-based design (MBD) to ensure the proper operation of numerous interconnected and interacting subsystems. In support of the U.S. Air Force's Integrated Vehicle Energy Technology (INVENT) program, several software tools have been developed and are in use that aid in the efficient MBD of next-generation EOA. Among these are subsystem model libraries, automated subsystem model verification test scripts, a distributed co-simulation application, and tools for system configuration, EOA mission building, data logging, plotting, post-processing, and visualization, and energy flow analysis. Herein, each of these tools is described. A detailed discussion of each tool's functionality and its benefits with respect to the goal of achieving successful integrated system simulations in support of MBD of EOA is given.

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.

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.

Numerous modern military and commercial vehicles rely on portable, battery-powered sources for electric energy. Due to their highly specialized functions these vehicles are typically custom-designed, produced in limited numbers, and expensive. To mitigate the power system's contribution to these undesirable characteristics, this paper proposes a modular power system architecture consisting of “smart” power battery units (SPUs) that can be readily interconnected in numerous ways to provide distributed and coordinated system power management. The proposed SPUs contain a battery power source and a power electronics converter. They are compatible with multiple battery chemistries (or any energy storage device that can produce a terminal voltage), allowing them to be used with both existing and future energy storage technologies.

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.

The performance of a more-electric aircraft (MEA) power system electrical accumulator unit (EAU) architecture consisting of a 57000 rpm induction machine (IM) coupled to a controllable shaft load and controlled using direct torque control (DTC) is examined through transient modeling and simulation. The simplicity and extremely fast dynamic torque response of DTC make it an attractive choice for this application. Additionally, the key components required for this EAU system may already exist on certain MEA, therefore allowing the benefits of EAU technology in the power system without incurring a significant weight penalty. Simulation results indicate that this architecture is capable of quickly tracking system bus power steps from full regenerative events to peak load events while maintaining the IM's speed within 5% of its nominal value.

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. Hardware-in-the-loop (HIL) is being used to investigate aircraft power systems by using a combination of hardware and simulations. This paper considers three different real-time simulators in the same HIL configuration. A representative electrical power system is removed from a turbine engine simulation and is replaced with the appropriate hardware attached to a 350 horsepower drive stand. Variables are passed between the hardware and the simulation in real-time to update model parameters and to synchronize the hardware with the model.

A primary challenge in performing integrated system simulations is balancing system simulation speeds against the model fidelity of the individual components composing the system model. Traditionally, such integrated system models of the electrical systems on more electric aircraft (MEA) have required drastic simplifications, linearizations, and/or averaging of individual component models. Such reductions in fidelity can take significant effort from component engineers and often cause the integrated system simulation to neglect critical dynamic behaviors, making it difficult for system integrators to identify problems early in the design process. This paper utilizes recent advancements in co-simulation technology (DHS Links) to demonstrate how integrated system models can be created wherein individual component models do not require significant simplification to achieve reasonable integrated model simulation speeds.