炼钢 ›› 2024, Vol. 40 ›› Issue (6): 23-27.

• 转炉及电炉冶炼 • 上一篇    下一篇

电弧炉炼钢动态模型的建立与评价

田博涵,陈兆平   

  1. 宝山钢铁股份有限公司 中央研究院,上海 201900
  • 出版日期:2024-12-05 发布日期:2024-11-29

Establishment and evaluation of dynamic model for electric arc furnace steelmaking

  • Online:2024-12-05 Published:2024-11-29

摘要: 建立数学模型预测电弧炉生产状况与工艺参数以指导其实际生产具有重要的实际意义。基于能量利用效率与冶金反应原理建立了电弧炉炼钢动态模型,包括竞争氧化、能量输入、废钢熔炼和熔池升温、温度求解四个模块,模拟电弧炉炼钢过程。将某钢铁厂电弧炉的典型生产参数及文献中报道的冶炼参数,代入该模型计算验证。结果表明,预测温度和测量温度的误差为-7 ℃,预测C、Si、Mn和P的质量分数误差分别为0.017 %、-0.001 %、0.037 %和-0.000 5 %,其中,展现了电弧炉冶炼终点的“回磷”现象,并论证了留钢操作对电弧炉冶炼的益处。针对实际生产过程多炉次的模拟结果也展示出比较良好的预测结果,证实模型具有良好的可推广性。模型的开发为帮助优化过程、设计操作实践以提高电弧炉的性能和竞争力提供了必要的工具。

关键词: 电弧炉, 动态模型, 能量效率, 竞争性氧化

Abstract: Establishing mathematical models to predict the production status and process parameters of electric arc furnace is of great practical significance to guide production. A dynamic model of electric arc furnace steelmaking was established based on energy efficiency and metallurgical reaction principle, including four moudles: competitive oxidation moudle, energy input moudle, scrap melting and bath heating moudle and temperature solving moudle, to simulate the electric arc furnace steelmaking process. The typical production parameters of an electric arc furnace and the smelting parameters reported in the literatures were substituted into the model for calculation and verification. It was found that the error of simulation temperature and measurement temperature was -7 ℃, the mass fraction error of C, Si ,Mn, and P was 0.017 %、-0.001 %、0.037 %, and -0.000 5 %, respectively. In the meanwhile, the “pick up” of phosphorus could be observed, and the benefits of hot heel on scrap smelting and process performance were demonstrated. The actual production simulation results for multiple heats also showed good prediction results, confirming the good generalizability of the model. The development of this model provides necessary tools to optimize processes and design operational practices to improve the performance and competitiveness of electric arc furnace.

Key words: EAF, dynamic model, energy efficiency, competitive oxidation