Investigating an approach to parameter fitting for the development of a semi-empirical electrowinning model. (1st July 2021)

• Record Type: Journal Article
• Authors: Tucker, M.; Dorfling, C.; Tadie, M.
• Is Part Of: Minerals engineering. Volume 168(2021)
• Publication Date: 2021-07-01
• Subjects: Copper electrowinning -- Steady state model -- Parameter fitting -- Electrowinning performance; Mines and mineral resources -- Periodicals; Ressources minérales -- Périodiques; Mines and mineral resources; Periodicals; Electronic journals; 622
• DOI: 10.1016/j.mineng.2021.106937
• Languages: English
• ISSNs: 0892-6875

Abstract

Highlights: A steady state copper electrowinning model was developed and parameters fit. A parameter fitting approach including a plant current loss parameter is presented. High model performance gives relative deviations of 7% for copper plating rate. The relative deviation for current efficiency was 3.2% with 3% for specific energy consumption. Model is proposed to be a useful tool for operator training. Abstract: A steady state electrowinning model was developed from first principles to predict copper yield, current efficiency and specific energy consumption. The electrochemical reactions incorporated were copper reduction, water oxidation and the cyclic reduction and oxidation of iron as impurity. This paper details a parameter fitting approach for this model which involves calibration of the model to bench-scale electrowinning data. A factorial experimental design, in which the electrolyte composition and current density were varied, was used. Each electrochemical reaction required parameters for rate expressions, and a current loss parameter was included to account for stray currents, other hardware losses and side reactions. Average current loss for the bench-scale experiments was 0.145 A (1–5% of total current). The kinetics parameters fit relatively well to the experimental data, with R 2 adj values of 0.864 for copper reduction, 0.739 for water oxidation, 0.724 for iron reduction and 0.661 for iron oxidation. The average relative errors between the predictive model and experimental data were 3.2% for current efficiency, 3.0% for specific energy consumption and 7.0% for copper plating rate. The results demonstrate the ability of the model to predict performance of a system in which the parameter fitting approach has been specifically applied. The parameters could be used as is for operator training and as a decision making tool. Industrial data varies substantially between plants, and therefore unique parameters would need to be fit specifically for a system should the model be used for performance prediction.