SBIR-STTR Award

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.

Keywords:
Reliability, Prognostics, Mtbf, Design, System, Bayesian, Model, Failure Rate

Ridgetop will develop an innovative Robustness Assessment for Design (RAD) tool for aircraft electrical power systems (EPS) to meet system safety, reliability, maintainability, and energy optimization requirements in each design stage by calculating system-level robustness. The design employs flow graph models for components at different hierarchies. The measurement of robustness takes into account the topology of the interconnected components, the degradation of the components from aging, and the environmental effects from field reliability data. In addition, factors associated with the following data are taken into account: ?X Real field data ?X Empirical data ?X Thermal and power data ?X System weight and failure modes and effects analysis (FMEA). The data are measured in multi-level hierarchical systems starting from the component level, and moving to the PWB level, the module level, up to the system level. The models can be connected in series, in parallel, and in combinations of both to conduct extensive ¡§what-if¡¨ analyses that optimize the design for overall system robustness improvement. The result of this SBIR program is a more accurate and modern alternative that maximizes system effectiveness, provides a reduction of energy consumption, and increases system robustness through more accurate estimates than those using conventional mean time between failures (MTBF)-type reliability calculations.

Benefit:
The anticipated benefits that Ridgetop¡¦s technology offers are electrical power systems¡¦ lifecycle improvement and continue level of performance in environment variations while optimizing energy. The main markets that will benefit from Ridgetop¡¦s technology are the commercial aircraft, commercial aircraft maintenance, repair and overhaul (MRO), and potentially the automotive markets. In the military industry, the markets that will be benefited from this technology are the aerospace and defense and the unmanned aerial vehicles markets. This tool supports the demands for more reliable, robust, and energy optimized designs of electrical power systems. The competitive advantage of this technology over other electronic design automation (EDA) tools available in the market is its ability to provide more accurate estimates of systems-levels robustness over conventional mean time between failures (MTBF)-types of reliability calculations, which are largely based on parts population methods. Higher reliability, increased robustness for a variety of platforms, and energy efficiencies are the principal benefits that this tool offers.

Keywords:
Robustness, Reliability, Mtbf, Design Tool, Electrical Power System, Model-Based, Energy Reduction, System Weight