A new fluid catalytic cracking (FCC) lumped kinetic modeling method was put forward to improve the prediction accuracy of the FCC kinetic model. This model divided the feedstock into three lumps and the products into six lumps. The parameters of the kinetic model were obtained by combining the fourth‐order Runge‐Kutta integral method and the two‐swarm cooperative particle swarm optimization algorithm. Compared with dividing the feedstock according to the group composition and the distillation range, the average relative error between the experimental data and the calculated values proves the higher fitting accuracy of the new lumped method. The kinetic model established by the method exhibits better adaptability to different feedstock and fewer requirements for feedstock analysis data.

中文翻译：

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催化裂化的集总动力学建模方法

提出了一种新的流化床催化裂化集总动力学模型方法，以提高FCC动力学模型的预测精度。该模型将原料分为三块，产品分为六块。通过结合四阶Runge-Kutta积分方法和两群合作粒子群优化算法获得动力学模型的参数。与根据组组成和蒸馏范围划分原料相比，实验数据和计算值之间的平均相对误差证明了新的集总方法的拟合精度更高。通过该方法建立的动力学模型表现出对不同原料的更好适应性，并且对原料分析数据的需求更少。