Given models of the current and future system behavior, a general approach of model-based prognostics can be employed as a solution to the prediction problem and further for decision making. To be able to predict the future state of the system, it is also required to possess knowledge of the current and future operations of the vehicle.Our research approach is to develop a system level health monitoring safety indicator either to the pilotautopilot for the electric vehicles which runs estimation and prediction algorithms to estimate remaining useful life of the vehicle e.g. SHM can be considered as a promising technology for effective and efficient management of different structures such as bridges, buildings, airplanes 5-7. In order to tackle and solve the prediction problem, it is essential to have awareness of the current state and health of the system, especially since it is necessary to perform condition-based predictions. In case of electric aircrafts, computing remaining flying time is safety-critical, since an aircraft that runs out of power (battery charge) while in the air will eventually lose control leading to catastrophe. It is well known that a key motivation for PHM is to increase aircraft availability by reducing unscheduled removals and downtime, ultimately reducing Direct Maintenance Costs (DMC). Many sensors are required to provide real-time, onboard structural integrity assessments for the. The benefits of applying Prognostics & Health Monitoring (PHM) techniques to Aircraft Maintenance are evaluated using System Dynamics (SD). Prognostics and Health Monitoring: Application to Electric Vehicles As more and more autonomous electric vehicles emerge in our daily operation progressively, a very critical challenge lies in accurate prediction of remaining useful life of the systemssubsystems, specifically the electrical powertrain. System health monitoring is a set of activities undertaken to maintain a system in operable condition and may be limited to an observation of current system states, with maintenance and repair being prompted by these observations.
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