摘要
This paper focuses on the distributed parameter modeling of the zinc electrowinning process(ZEWP)to reveal the spatiotemporal distribution of concentration of zinc ions(CZI)and sulfuric acid(CSA)in the electrolyte.Considering the inverse diffusion of such ions in the electrolyte,the dynamic distribution of ions is described by the axial dispersion model.A parameter estimation strategy based on orthogonal approximation has been proposed to estimate the unknown parameters in the process model.Different industrial data sets are used to test the effectiveness of the spatiotemporal distribution model and the proposed parameter estimation approach.The results demonstrate that the analytical model can effectively capture the trends of the electrolysis reaction in time and thus has the potential to implement further optimization and control in the ZEWP.
This paper focuses on the distributed parameter modeling of the zinc electrowinning process（ZEWP）to reveal the spatiotemporal distribution of concentration of zinc ions（CZI）and sulfuric acid（CSA）in the electrolyte.Considering the inverse diffusion of such ions in the electrolyte,the dynamic distribution of ions is described by the axial dispersion model.A parameter estimation strategy based on orthogonal approximation has been proposed to estimate the unknown parameters in the process model.Different industrial data sets are used to test the effectiveness of the spatiotemporal distribution model and the proposed parameter estimation approach.The results demonstrate that the analytical model can effectively capture the trends of the electrolysis reaction in time and thus has the potential to implement further optimization and control in the ZEWP.
基金
Project(61673400)supported by the National Natural Science Foundation of China
Project(2015cx007)supported by the Innovation-driven Plan in Central South University,China
Project(61321003)supported by the Foundation for Innovative Research Groups of the National Natural Science Foundation of China
Projects(61590921,61590923)supported by the Major Program of the National Natural Science Foundation of China
