Publication | Open Access
Online Prediction of Battery Discharge and Estimation of Parasitic Loads for an Electric Aircraft
28
Citations
15
References
2014
Year
Vehicle BatteriesEngineeringUncertainty ModelingReliability EngineeringProbabilistic ForecastingUncertainty QuantificationManagementSystems EngineeringModeling And SimulationAircraft BatteriesAircraft Design ProcessStatisticsOnline PredictionElectrical EngineeringUncertainty ManagementAerospace Electric PowerPredictive AnalyticsForecastingEnergy PredictionBattery DischargeAerospace EngineeringElectric AircraftBattery ConfigurationAircraft Flight Plan
Predicting whether or not vehicle batteries contain sufficient charge to support operations over the remainder of a given flight plan is critical for electric aircraft. This paper describes an approach for identifying upper and lower uncertainty bounds on predictions that aircraft batteries will continue to meet output power and voltage requirements over the remainder of a flight plan. Battery discharge prediction is considered here in terms of the following components; (i) online battery state of charge estimation; (ii) prediction of future battery power demand as a function of an aircraft flight plan; (iii) online estimation of additional parasitic battery loads; and finally, (iv) estimation of flight plan safety. Substantial uncertainty is considered to be an irremovable part of the battery discharge prediction problem. However, highconfidence estimates of flight plan safety or lack of safety are shown to be generated from even highly uncertain prognostic predictions.
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