Dynamic, Adaptive Life Models for Drive Train Clutches

ALPHATECH proposes, in conjunction with our partners, Rolls-Royce North America, a novel approach to the on-line prognostic modeling of drivetrain clutch systems, combining dynamic modeling of the clutch transients with physics-of-failure based hazard modeling. In particular, our effort is focused towards the F35B LiftFan clutch, to which our models and techniques will be applied. We extend our oxidation wear model for Carbon-Carbon composites developed under Phase I, and refine this to the LiftFan Clutch application. The goal is to predict clutch problems before they impact vehicle performance, enabling the vision of autonomic logistics through precision sensing and prognosis. The model extends existing LiftFan clutch loading models to address the transient engagement dynamics, and incorporates several physics-of-failure models to address different types of component failures. Further, our physical modeling approach addresses the unique features of this clutch, which has extremely high power density and transient loads. This, combined with the ability to fuse existing anomaly-detection technology, has the potential to provide high-accuracy predictions of future life.