Development of a Dynamic Semi-empirical Model for Simulation of Copper Electrowinning Processes

Abstract

Dynamic process models present an opportunity to investigate optimization and control strategies for the energy-intensive copper electrowinning process. In this paper, a dynamic semi-empirical model of the copper electrowinning process was developed to predict the copper yield, current efficiency, and specific energy consumption. The model uses input variables readily measured in industrial tankhouses and incorporates the ability to induce step or pulse disturbances in the electrolyte composition or flow rate. Dynamic bench-scale electrowinning data were used to show how the model may be calibrated and validated for use in predicting electrowinning performance. Overall, the performance of the developed dynamic model lends credence to the application thereof for operator training, process monitoring, and early fault detection. The model also represents a further step towards investigating advanced control strategies for the electrowinning process.