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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.

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.

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.

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.

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 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.

The movement to more-electric architectures during the past decade in military and commercial airborne systems continues to increase the complexity of designing and specifying the electric power system. In particular, the electrical power system (EPS) faces challenges in meeting the highly dynamic power demands of advanced power electronics based loads. This paper explores one approach to addressing these demands by proposing an electrical equivalent of the widely utilized hydraulic accumulator which has successfully been employed in hydraulic power system on aircraft for more than 50 years.