SoC estimation using an Extended Kalman filter for UAV applications

Measuring or estimating adequately and accurately the state of charge (SoC) of a Li-Po battery, which powered an UAV during its flight allows to know the limits of the mission that the UAV is developing and to maximize the energy supplied by the battery. In this sense this paper presents a methodology to estimate the state of charge (SoC) of a LiPo battery through an Extended Kalman Filter (EKF) during the flight of an UAV. By considering the mathematical model of the propulsion system of an UAV hexacopter, the power consumption is computed, and the SoC of the battery is estimated. Finally, a strategy based on estimated SoC is presented to predict the End-of-Discharge (EoD) during the development of a mission of and UAV hexacopter. The simulation results show the effectiveness of the proposed method.