Torque ripple suppression of crop harvester based on unscented Kalman filter under vibration reduction and noise reduction

In order to reduce the fluctuation of the motor stator current waveform and the torque fluctuation coefficient of the motor, this paper proposes a torque ripple suppression method of crop harvesters based on unscented Kalman filter (UKF). Firstly, this article analyses the working principle of the motor in depth by constructing mathematical models of voltage, torque, and motion equations. Secondly, the key step is to use the unscented Kalman filter technique to process the signals of the nonlinear dynamic model. Unscented Kalman filter approximates the probability distribution of nonlinear functions by selecting a set of Sigma points, effectively estimating the system state without introducing linearisation errors. The experimental results show that this method not only makes the stator winding current present a standard sine waveform with a fluctuation range controlled within [–15 A, 15 A], but also reduces the maximum torque fluctuation coefficient to 0.0141.