Search Results

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 term Integrated Vehicle Health Management (IVHM) describes a set of capabilities that enable sustainable and safe operation of components and subsystems within aerospace platforms. However, very little guidance exists for the systems engineering aspects of design with IVHM in mind. It is probably because of this that designers have to use knowledge picked up exclusively by experience rather than by established process. This motivated a group of leading IVHM practitioners within the aerospace industry under the aegis of SAE's HM-1 technical committee to author a document that hopes to give working engineers and program managers clear guidance on all the elements of IVHM that they need to consider before designing a system. This proposed recommended practice (ARP6883 [1]) will describe all the steps of requirements generation and management as it applies to IVHM systems, and demonstrate these with a “real-world” example related to designing a landing gear system.

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.

Currently the U. S. Department of Defense (DoD) exclusively uses potassium acetate (KAc)-based runway deicing fluids (RDFs) to deice and anti-ice military runways and taxiways. Commercial airports predominantly use KAc, but some also use RDFs composed of KAc plus propylene glycol (PG) or urea plus PG. Conventional RDFs have environmental concerns due to toxicity as well as material compatibility problems such as corrosion of aircraft carbon brake-pad components, cadmium-plated landing gear, and airfield lighting fixtures. Under the Strategic Environmental Research and Development Program (SERDP), Battelle tested a series of patented - bio-based RDFs to address these issues. Tests showed that the Battelle RDFs met the mandatory Aerospace Material Specification (AMS) 1435 requirements. These new RDFs have reduced ecotoxicity compared to currently used RDFs and are compliant with all other environmental requirements.

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.

Validation is a critical component of model-based design (MBD). Without it, regardless of the level of model verification, neither the accuracy nor the domain of applicability of the models is known. Thus, it is risky to base design decisions on the predictions of unvalidated models. The Integrated Vehicle Energy Technology (INVENT) program is planning a series of hardware experiments that will be used to validate a large set of unit-, subsystem-, and system-level models. Although validating such a large number of interacting models is a large task, it provides an excellent opportunity to test the limits of MBD.

Movement toward more-electric architectures in military and commercial airborne systems has led to electrical power systems (EPSs) with complex power flow dynamics and advanced technologies specifically designed to improve power quality in the system. As such, there is a need for tools that can quickly analyze the impact of technology insertion on the system-level dynamic transient and spectral power quality and assess tradeoffs between impact on power quality versus weight and volume. Traditionally, this type of system level analysis is performed through computationally intensive time-domain simulations involving high fidelity models or left until the hardware fabrication and integration stage. In order to provide a more rapid analysis prior to hardware development and integration, stochastic equivalent circuit analysis is developed that can provide power quality assessment directly in the frequency domain.

A sudden short-circuit (SSC) laboratory test of an electric machine is a commonly used procedure to estimate model parameters that accurately represent the dynamic response of the machine. While the graphical interpretation of the short-circuit current is often discussed in great detail, the numerical methods used to determine the solution for the machine parameter estimation is a challenging proposition. In this paper, the authors present an integral regression technique to fit the characteristic equation of the short-circuit current to a curve that is composed of exponential decays that trail off to an unknown steady-state value in the presence of noise. The proposed estimation method is applied to laboratory data from an aerospace synchronous machine.

This paper introduces a method for conducting experimental hardware-in-the-loop (xHIL), in which behavioral-level models are coupled with an advanced power emulator (APE) to emulate an electrical load on a power generation system. The emulator is commanded by behavioral-level models running on an advanced real-time simulator that has the capability to leverage Central Processing Units (CPUs) and field programmable gate arrays (FPGA) to meet strict real-time execution requirements. The paper will be broken down into four topics: 1) the development of a solution to target behavioral-level models to an advanced, real-time simulation device, 2) the development of a high-bandwidth, high-power emulation capability, 3) the integration of the real-time simulation device and the APE, and 4) the application of the emulation system (simulator and emulator) in an xHIL experiment.