Precise Pre-Close Wind Volume Calculation for Aluminum Electrolysis Based on Unscented Kalman and Average Filters

To improve the accuracy of calculating the aluminum electrolysis pre-close wind volume, this study focused on optimizing the two main factors that influence its magnitude: the aluminum output speed and the pre-close wind volume coefficient. First, the Unscented Kalman Filter (UKF) algorithm was used to estimate the aluminum output speed, and its application in real production was verified through simulation experiments. The results demonstrate that UKF provides more accurate speed estimates when handling the non-linear dynamic system of aluminum electrolysis. When there was a sudden change in speed, the UKF achieved a relative error of only 0.0373%, significantly lower than the 2.52% error of the traditional Kalman Filter (KF). At the same time, the UKF exhibited a shorter runtime in the simulation. Additionally, this research introduces a self-correction mechanism for the pre-close wind volume coefficient for the first time. By dynamically adjusting the parameter based on aluminum output deviations and applying the Average Filter (AF) to improve the compensation accuracy, the pre-close wind volume coefficient can be precisely calculated. The combination of these methods significantly enhances the accuracy and robustness of pre-close wind volume calculations, providing solid theoretical foundations and the technical support needed to achieve high-precision aluminum output control.