We will provide an automated, highly accurate, extensible, real-time diagnostic and prognostic decision making tool that predicts when military aircraft batteries will fail to meet service requirements. Incipient fault-to-failure progression characteristics will be identified to develop verifiable prognostic models driven by existing parameters and observable diagnostic events in combination with other system state information. We will distinguish between normal battery aging and slow failure modes. Accurate remaining useful life predictions will be facilitated and enhanced by our proven, modular, open architecture that encourages use of multiple prediction and detection models, including physics-of-failure and statistical methods. False alarms will be reduced significantly using our patented mode partitioning technology which recognizes distinct operating states and does not alarm when changing between modes. We will integrate new data management features for accumulating individualized operating performance and stressor time histories automatically and efficiently. Top-tier military aircraft managing contractors and battery vendors will provide feedback. Proven software, system knowledge, and data gained from prior successful PHM USAF SBIR work will enhance and expedite our performance on this Navy project.
Keywords: Prognostics, Diagnostics, Service Life Management, Data Fusion, Autonomic Logistics, Predictive Maintenance, Smart Batteries, Health Monitoring.
