基于粒子群优化算法的相变换热器动态仿真研究  

Research on Dynamic Simulation of Phase Change Heat Exchanger Based on Particle Swarm Optimization Algorithm

作　　者：王晓霞 麻宏强 宋兴鹏 WANG Xiaoxia;MA Hongqiang;SONG Xingpeng(School of Equipment Engineering,Shanxi Vocational University of Engineering and Technology,Taiyuan,Shanxi 030600,China;School of Civil Engineering and Architecture,East China Jiaotong University,Nanchang,Jiangxi 330013,China;School of Civil Engineering,Lanzhou University of Technology,Lanzhou,Gansu 730050,China)

机构地区：[1]山西工程科技职业大学设备工程学院,山西太原030600 [2]华东交通大学土木建筑学院,江西南昌330013 [3]兰州理工大学土木工程学院,甘肃兰州730050

出　　处：《西安石油大学学报（自然科学版）》2022年第4期120-126,共7页Journal of Xi’an Shiyou University（Natural Science Edition）

基　　金：甘肃省自然科学基金(1606RJZA059);“十三五”重大科技攻关项目“高含硫气藏安全高效开发技术”(2016ZX05017-004);中国石化“十条龙”集团公司专项(P18062-6)。

摘　　要：为了实现烟气余热回收系统中相变换热器的性能优化,采用理论及实验建模方法建立相变烟气换热器动态数学模型,对其进行仿真研究。结果表明:模型受到换热器横截面积、换热器壳程长度、烟气流过换热器时的速度、管程溶液进口流量、烟气密度、烟气比热、管程内和管程进口溶液比热等参数的影响;根据烟气余热回收系统的动态响应实验数据,基于系统辨识理论和过程传递函数模型的辨识方法,辨识得到相变换热器三阶动态数学模型,使用实验数据验证辨识模型的准确性,其模型仿真和实验结果的最大相对误差不超过±1.5%;仿真结果显示基于粒子群优化算法的PID控制器参数整定方法有较好的控制性能和跟踪性能,其单位阶跃响应的上升时间和调节时间分别为1.18 s和1.34 s,具有良好的快速性和稳定性。In order to optimize the performance of the phase change heat exchanger for flue gas waste heat recovery,the dynamic mathematical model of the phase change heat exchanger was established based on theoretical and experimental methods,and the heat exchanger was simulated and analyzed.The results show that the model is affected by the parameters such as the cross-sectional area of the heat exchanger,the length of the heat exchanger'shell side,the velocity of the flue gas flowing through the heat exchanger,the flow rate of the liquid in the pipe,the density of the flue gas,the specific heat of the flue gas,the specific heat of liquid in tube and at tube inlet.According to the dynamic response experimental data of flue gas waste heat phase change recovery system,the third-order dynamic mathematical model of phase change heat exchanger is identified based on the system identification theory and the process transfer function model.The accuracy of the identification model is verified by using the experimental data,and the maximum relative error between simulation result and experimental result is not more than 1.5%.Finally,the simulation result shows that the PID controller parameter tuning method based on particle swarm optimization algorithm has better control performance and tracking performance,and its rise time and setting time of unit step response are 1.18 s and 1.34 s.It has good rapidity and stability.

关 键 词：相变换热器 动态数学模型 系统辨识 粒子群优化算法 

分 类 号：TE974.7[石油与天然气工程—石油机械设备] TK172[动力工程及工程热物理—热能工程]