Advanced Numerical Models for Electromechanical Actuators

Electromechanical actuators are increasingly being used in aerospace, mainly due to the new design concept, the more electric aircraft (MEA), such as the Boeing 787, which uses electric power to directly operate some actuators, such as the brake system, to feed the hydraulic system, or to power systems that manage the onboard environment, making the aircraft bleed-less. In the most recent airbus aircrafts are used electric actuators for secondary systems, but for primary systems are used hybrid actuators, such as the Electro Hydrostatic Actuators (EHA), which use both electric power and local hydraulic power. Actuators are safety critical components, especially when used for systems of primary importance, and for this reason it is necessary to identify all possible faults associated with it and, if possible, assess the degraded state of the actuator to maintain a high level of safety. Nowadays, electric actuators are used for secondary systems because the failure risks and accumulated reliability experience are absent. The predictive maintenance is the ability to know the remaining useful life of a generic system, based on prognostic methods, in order to plan maintenance before a critical failure. With data-driven prognostic methods there is a need for a high amount of data from sensors to evaluate the performance of the system. These data are collected and run through machine learning algorithms in hopes of detecting correlations and using these to make prognoses of future failures. The purpose of this work is to implement a thermal model within an existing model of Electromechanical Actuator (EMA), provided by Prof. M.D.L. Dalla Vedova and the Eng. G. Quattrocchi, in order to evaluate the thermal effects due to the energy dissipation inside the stator conductors, and the consequent heat flows on the other components of the electric motor, as the resistance of the windings is a function of their temperature. The EMA model provided is based on Permanent Magnet Synchronous Motor (PMSM), which is an AC synchronous motor whose field excitation is provided by permanent magnets, such as the Brushless DC electric motor, and that has a sinusoidal back EMF waveform. Several variables related to the failure modes of servomechanism are implemented within the model, the partial shortage of each phase, a variable that evaluates the static eccentricity, and a variable that evaluates the phase of this imbalance. Once created the thermal model, and compared the system response with the previous model provided, the following step is related to the simulations performed taking into account different operating conditions, varying parameters such as the partial shortage of each phase, so as to sample as much data as possible and use Data driven prognostic methods, in order to evaluate the Remaining Useful Life (RUL) of the actuator