| Summary: | The complexity of aircraft systems is steadily growing, allowing the machine to perform an increasing number of functions; this can result in a multitude of possible failure modes, sometimes difficult to foresee and detect. A prognostic tool to identify the early signs of faults and perform an estimation of Remaining Useful Life (RUL) can allow adaptively scheduling maintenance interventions, reducing the operating costs and increasing safety [1-4]. A first step for the RUL estimation is an accurate Fault Detection & Identification (FDI) to infer the system health status, necessary to determine when the components will no more be able to match their requirements [5]. With a model-based approach, the FDI is a model-matching problem, intended to adjust a parametric Monitor Model (MM) to reproduce the response of the system. The MM shall feature a low computational cost to be executed iteratively on-board; at the same time, it shall be detailed enough to account for a several failure modes [6]. We propose the simplification of an Electromechanical Actuator (EMA) dynamical model [7] for model-based FDI, focusing on the BLDC motor and Power Electronics, which account for most the computational cost of the original high fidelity model.
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