Power System Robustness Assessment Tool for All-Electric Aircraft

ABSTRACT: An innovative electrical power system (EPS) Robustness design tool will be created for calculating system-level Robustness in aircraft. The design employs flowgraph models for components at different levels of hierarchy including power sources, electronic circuit breakers, and electromechanical actuator (EMA) loads, which can be connected together. The components accept real measured data, including degradation effects, to produce a system-level Robustness RB(t) metric. The models can be connected in in series, parallel, and combinations of both to conduct extensive"what-if"analyses to optimize the design for overall system reliability improvements. The model parameters are drawn from consensus inputs, then adjusted with composite degradation factor (DF) information obtained from prognostic and diagnostic data on fielded units. Using Bayesian Network methods, this information is used to calibrate the model through a series of updates drawn from actual degradation data, field database information, or HALT testing results. Each model in the EPS contributes to the overall system Robustness and this is handled using an extension of Bayesian Network analysis. The result of this SBIR Program will be a much more accurate and modern alternative to determining system reliability in the presence of LRU degradation from actual environmental effects (heat, radiation, vibration) and wear patterns. BENEFIT: The metric of Robustness goes far beyond standards-based MTBF reliability prediction tools and offers far more relevant information on the performance of the system to perform its intended tasks. This information is useful in the improvement in reliability of all-electric aircraft designs, and supporting life cycle cost reductions by identifying best candidates for design improvements that improve robustness. With this SBIR program, Ridgetop will leverage its prior innovations in signature-based prognostics to address the realistic assessment of robustness of aircraft power systems. The result will be a deterministic analysis tool that allows the importing of field data from airborne power systems to provide well-calibrated models that can be employed in"what if"analyses to improve reliable performance of these complex systems.