With increased autonomy being an integral part of un- manned aerial system (UAS), during flight a vehicle needs to have an accurate estimation of its state of health and capabilities to perform and achieve mission success with utmost safety. Batteries are of key importance in electric-propulsion aircraft and are its most pertinent re- source. It is important to know the state of charge of the battery not only because the health state is directly re- lated to the flight profiles flown by the vehicle, but also because the state of charge of the vehicle and its opera- tional condition must be estimated after each flight.
In this work a methodology is presented to generate pre- dictions for flight plans that experience anomalies, or un- expected system failure in due to a parasitic load in a specified stage of the flight that must return to its starting point of origin. We begin by describing the procedures by which a sequence of steps will be carried out to expo- nentially weigh the impact of different stages of a flight towards thermal strain on the capacitance Cmax of the battery during each flight.
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prognostics, functional analysis, Fourier series, mean square error, statistical analysis
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