Control Strategy For Aluminum Fluoride Addition Based On Thermal Balance Analysis Of Aluminum Reduction Cell

The reduction of aluminium is an important part of the nonferrous metallurgy industry. As the basis material of nonferrous metals, the aluminium and its processed materials have been widely used in building, electricity, transportation, machinery, national defence and other fields. In recent years, the Al-metallurgical industry of China has obtained rapid development and China is being the world's leading aluminium producer. However, the Al-metallurgical industry is always a kind of industry which consumes a large amount of energy. In all processes of Al-metallurgical industry, the electrolysis occupies 80% - 89% of the total energy consumption. As a result, taking various measures to reduce the energy consumption in aluminium electrolysis is the key to energy saving in the Al-metallurgical industry and is also the main factor which constrains the healthy development of China's Al-metallurgical industry.An effective way to reduce the energy consumption in the aluminium electrolysis process is to lower the electrolysis temperature under the premise of maintaining the heat balance in the aluminium reduction cell. One of the best methods for reducing the electrolysis temperature is to choose suitable additives to form an electrolyte system whose liquidus temperature is low. In all additives adopted now, the aluminium fluoride occupies the largest proportion. Therefore, the aluminium fluoride can influence the electrolyte composition and electrolysis temperature significantly. In this paper, through the analysis on the coupling relationship between the heat balance characteristics of the aluminum reduction cell and the amount of aluminium fluoride addition, the author tries to seek and apply the control strategy which is concerned the appropriate amount of aluminium fluoride addition, and also tries to lower the electrolysis temperature under the condition of maintaining the heat balance in the aluminium reduction cell to achieve the goal of reducing the energy consumption in the aluminium electrolysis process. The main contributions of this dissertation are summarized as follows:(1) On the basis of extensive searching and reading domestic and foreign literatures, various methods about how to analyse the heat balance in the aluminium reduction cell was summarized, and the physical models and numerical models which were used in the aluminium reduction cell's heat transfer analysis were reviewed. Based on the balance of the mass and energy in the aluminium reduction cell, the characteristics relationship between the amount of the excess aluminum fluoride and the electrolysis temperature was explored. The coupled mass and energy balance model in the aluminium reduction cell was established through the law of heat transfer, and a practical expression was given explicitly by appropriate simplifications. Finally, the validity of the model was verified by the on-site tests.(2) A control model for aluminum fluoride addition was put forward based on the regression analysis, which adopts the aluminum fluoride addition as the dependent variable and adopts the electrolysis temperature as the independent variable. Through this model, the amount of the present-day aluminum fluoride addition can be forecasted according to the yesterday's electrolysis temperature. The field tests show that this control strategy for the aluminum fluoride addition is beneficial to stabilize the electrolysis temperature, and it is helpful to enhance the current efficiency and to reduce the electrical energy consumption.(3) The genetic algorithm was applied to control the amount of the aluminum fluoride addition with the daily average cell voltage and the amount of aluminum fluoride added as genetic operation variables. The control target is to minimize the superheat degree of the aluminum electrolyte with the reciprocal of the superheat degree as the sufficiency function. The best value of aluminum fluoride added was gained under different cell voltages. In the modeling process, the elitist strategy was introduced to retain the best individuals to the next generation of the population as much as possible. The field test results show that this control method about the amount of the aluminium fluoride added is better than the conventional method which was used in the industry and it can reduce the degree of overheat markedly.(4) The support vector machine was introduced into the investigation on the control problem of the aluminum fluoride addition. A support vector machine model was established using the electrolysis temperature, the liquidus temperature, the cell voltage as inputs and the aluminium fluoride addition as output. The polynomial function and the radial basis function were adopted as the kernel function respectively. The results showed that the trained support vector machine can predict the optimal amount of the amount of aluminum fluoride added, and the difference in the kernel function has little impact on the performance of the support vector machine.(5) Based on 160kA aluminium reduction cells in a large aluminum company, a decision-making program for the aluminium fluoride addition was developed using the Delphi language. The aluminium fluoride addition control strategies based on regression analysis, genetic algorithm, support vector machine were embedded in the program to adjust the aluminium fluoride addition according to the real-time cell state. Field test results show that the three proposed aluminum fluoride addition control strategies and the corresponding software system are feasible, practical and effective in energy saving.