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 R²_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.

从第一原理建立了稳态电积模型，以预测铜的产量，电流效率和单位能耗。引入的电化学反应包括铜还原，水氧化以及铁作为杂质的循环还原和氧化。本文详细介绍了此模型的参数拟合方法，该方法涉及将模型校准为台式规模的电积数据。使用析因实验设计，其中改变了电解质的组成和电流密度。每个电化学反应都需要参数来表示速率，并包括电流损耗参数以说明杂散电流，其他硬件损耗和副反应。台式实验的平均电流损耗为0.145 A（占总电流的1-5％）。^2个_ADJ的0.864为铜还原值，为0.739水氧化，0.724为还原铁和0.661对铁氧化。预测模型和实验数据之间的平均相对误差为：电流效率为3.2％，比能耗为3.0％，镀铜速率为7.0％。结果证明了该模型预测系统的性能的能力，在该系统中，已经特别应用了参数拟合方法。这些参数可以按原样用于操作员培训和用作决策工具。工厂之间的行业数据差异很大，因此，如果模型用于性能预测，则需要专门针对系统配置唯一参数。