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<doi>0480-cd</doi>
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<article-title>A Lumped Parameter High Fidelity EMA Model for Model-Based Prognostics</article-title>
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<author>Pier Carlo Berri<sup>a</sup>, Matteo D.L. Dalla Vedova<sup>b</sup> and Paolo Maggiore<sup>c</sup></author>

<aff>Dept.of Mechanical &amp; Aerospace Engineering, Politecnico di Torino, Italy</aff>

<email><a href="mailto:pier.berri@polito.it"><sup>a</sup>pier.berri@polito.it</a></email>

<email><a href="mailto:matteo.dallavedova@polito.it"><sup>b</sup>matteo.dallavedova@polito.it</a></email>

<email><a href="mailto:paolo.maggiore@polito.it"><sup>c</sup>paolo.maggiore@polito.it</a></email>

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<title>ABSTRACT</title>
<p>The last advancements in the field of brushless electrical machines are boosting the use of electromechanical actuators (EMAs) in place of more traditional hydraulic and pneumatic powered flight control systems. However, the use of relatively new technology on safety critical applications imposes to adopt highly accurate and reliable monitoring strategies for risk reduction. In this context, Prognostics and Health Management (PHM) are an emerging field aiming to dynamically estimate the remaining useful life of systems. The authors propose a detailed dynamical model of a flight control EMA, intended as a simulated test bench for Fault Detection and Identification (FDI) algorithms. The model shall be able to accurately simulate the EMA dynamical response in presence of multiple electrical and mechanical failure modes, in the whole flight envelope of the aircraft. We adopt a lumped parameter description of the EMA architecture. This allows achieving a high simulation accuracy while avoiding the computational cost usually associated to finite element electromagnetic and mechanical coupled formulations. We assess the model in different operating conditions in terms of load profile, speed and angle of attack, in presence of multiple failures and in combination of a very simple aerodynamic model for the evaluation of aerodynamic loads.</p>
<p><italic>Keywords: </italic>Model-Based Prognostics, Electromechanical Actuator, Dynamical Model, System Health Monitoring.</p>
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