Electro-Mechanical Actuators (EMA) have attracted growing attention with their increasing\nincorporation in More Electric Aircraft. The performance degradation assessment of EMA needs to be\nstudied, in which EMA motor voltage is an essential parameter, to ensure its reliability and safety of\nEMA. However, deviation exists between motor voltage monitoring data and real motor voltage due\nto electromagnetic interference. To reduce the deviation, EMA motor voltage estimation generally\nrequires an accurate voltage state equation which is difficult to obtain due to the complexity of EMA.\nTo address this problem, a Feature-aided Kalman Filter (FAKF) method is proposed, in which the\nstate equation is substituted by a physical model of current and voltage. Consequently, voltage state\ndata can be obtained through current monitoring data and a currentâ??voltage model. Furthermore,\nvoltage estimation can be implemented by utilizing voltage state data and voltage monitoring data.\nTo validate the effectiveness of the FAKF-based estimation method, experiments have been conducted\nbased on the published data set from NASAâ??s Flyable Electro-Mechanical Actuator (FLEA) test stand.\nThe experiment results demonstrate that the proposed method has good performance in EMA motor\nvoltage estimation.
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