Propeller speed estimation for unmanned aerial vehicles using Kalman filtering

Abstract

This paper presents an online propeller speed estimation system for a multirotor unmanned aerial vehicle (UAV) equipped with brushless DC (BLDC) motors and powered by a lithium-polymer battery pack. Propeller speed estimation is based on battery drain current measurement extended with averaged state-space model of brushless DC motor utilised within a Kalman filter-based state estimator. Based on the BLDC motor and propeller physical parameters and utilising corresponding mathematical model, the estimation system is implemented within the flight computer on board the UAV. The proposed propeller speed estimation algorithm is verified experimentally for a wide range of propeller operating regimes, which has shown that the proposed method is able to provide efficient estimation of UAV propeller speed.