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This paper proposes a combined cell voltage acquisition algorithm based on Kalman filtering, which is used to solve the problem of insufficient cell voltage acquisition and high delay in the current aluminum electrolysis process. This algorithm is based on Kalman filtering, and uses the mean square error of the data to represent the Gaussian white noise power of the collected and predicted values. It has strong tracking performance in the state of stable voltage. The voltage acquisition data out of the interval is comply to first-order inertial filtering, to replace the voltage sampling value, and then using the Kalman filtering algorithm to calculate the filtering gain, to ensure that the combined algorithm can filter out the influence of noise when the cell voltage fluctuates greatly, and in the stable process of electrolysis, the convergence of battery voltage can be tracked quickly. The simulation results show that compared with the first-order inertial filter, the improved Kalman filter reduces the root mean square error by 50% when the voltage is stable, and reduces the convergence time by 50% after the electrolytic cell regenerates needle vibration and swing.

The combined algorithm of aluminum-electrolytic cell voltage collection based on Kalman filter