Modelling and Simulation of the Electric Arc Furnace Processes

Market demands on steel quality, price and production times dictate an introduction of technological innovations regarding the electric arc furnace (EAF) steelmaking.A developing field with significant potential is related to the advanced software support of the EAF operation, combining monitoring and proper control of the EAF.Such systems include process models, capable of continuous estimation of the unmeasured process values, such as chemical compositions and temperatures of the steel, slag and gas.The paper briefly presents the features of all developed EAF models, which are used together with the measured EAF data to estimate the unmeasured process values.The models are mainly implemented using non-linear, time-variant ordinary differential equations.The parameterization of the models was performed using the available EAF data, such as temperatures, steel and slag compositions, melting programs etc.The validation results that were performed using measured EAF data indicate high levels of estimation accuracy of all crucial steel-recycling values and processes.The accuracy of the presented models is in the range of +/-15 K for steel temperature and +/-10 % for steel composition.Thus, accuracy of the models allows them to be used in broader software environments, such as soft sensors for process monitoring, optimization and operator decision support.