基于数据驱动的航站楼碳浓度控制系统设计及应用仿真（英文）

Design and application simulation of the CO_2 control system based on data-driven for airport terminal

碳浓度偏高是导致航站楼内空气质量不佳的主要原因之一,且航站楼内随旅客数量变化碳浓度呈现的非平稳性给其控制带了挑战。为了营造航站楼内良好的空气质量,本文设计基于数据驱动的碳浓度控制系统,该系统根据航站楼内碳浓度、新风量等环境数据组成的信息向量在基础数据库中选取邻元素,通过参数调节器对邻元素的PID参数进行有向学习修正,实现系统PID参数在线优化。利用MATLAB/Simulink平台根据航站楼实际环境建立碳浓度控制系统进行应用仿真,结果表明:该系统通过参数在线优化实现了非平稳碳浓度的良好控制,可保证航站楼内碳浓度低于800ppm,系统稳态误差小于1%,与定风量系统相比节约风量约30%。该系统在为旅客提供良好的空气质量的同时可为航站楼节能设计提供参考。

Excessive CO2 density is one of the main reasons for poor air quality. CO2 density is non-stationary with passengers＇ number changing in terminal,which brings challenge for the CO2 control system. In order to make better air quality,this paper designs a data-driven CO2 control system,which chooses adjacent elements from database and optimizes PID parameters based on CO2 density,fresh air flow and other environmental data by using parameter optimizer. CO2 control system application model is built based on MATLAB/Simulink platform according to terminal environment. Simulation results show that,the system achieves good control effect of the non-stationary CO2 density through parameters optimization online,which ensures that CO2 density in terminal is lower than 800 ppm. System＇s steady-stage error is less than 1%. Compared with constant air volume system,the system saves about 30% fresh air volume,which can provide reference for energy efficiency design of terminal.