Particle Filter Based Prognostic Approach for Automotive Motor

Motors subjected to degradation due to prolonged loading conditions in an industry needs maintenence on the regular basis. The continuous use of electric motors in the present-day transmission systems in an automotive vehicle increases the dependency of the product. The ability to detect the onset of failure of such electric motors certifies an efficient, comfortable and a safe mode of transport. Predictive maintenance is one area which is gaining significant interest that complies in the process of early detection of failure for systems. The paper discusses the role of Particle filter (PF) approach in the process that helps estimating the remaining useful life (RUL) in an automotive application. The present work aims at utilizing real time data to simplify pertinent indicators alongside the trends that depict the health of an automotive system thus, aiming towards superior accuracy results.