Cross-River Tunnel Ventilation Control Model And Ventilation Control Strategies Research

Tunnel, as a special traffic infrastructure, its safety and energy efficiency operation has been paid more and more attention. Due to the nonlinear characteristics of control object, as well as weather condition, tunnel traffic and vehicles, it is difficult to control tunnel ventilation in terms of air quality and to keep the number on-line jet fans as little as possible.The background of this thesis is Wuhan the Long River Cross-River Tunnel Ventilation Control project. Ventilation models are developed in terms of dynamic traffic volume and ventilation strategy is presented based on contaminant concentration and future ventilation needs. Various ventilation methods are discussed and the necessity to use feed-forwards traffic forecast ventilation control is put forward. Autoregressive Moving Average (ARMA) process is implemented to forecast traffic volume. Fuzzy intelligent control strategy is developed to address the problem that tradition control methods could hardly response to cross-river tunnel contaminant in time. To avoid complicated mathematical models, real-time traffic volume is forecasted and corresponding fuzzy ventilation strategy is implemented according to real traffic information and tunnel running data, as well as full consideration of the influence from natural wind and traffic vehicle ventilation. It is proved that fuzzy logic is very helpful tool to avoid the lack of well-developed ventilation model and solve the nonlinear effect and big time inertia caused by large tunnel space. Proper fuzzy logic, which is determined by difference between control goal and real concentration and future contaminant forecast, is used to control jet fans on/off, and thus can satisfy ventilation needs and, at the same time, save energy.First of all, this thesis has stated the importance of feed-forward forecast in tunnel ventilation control. The ARMA model which serves to tunnel traffic volume forecast is built. Furthermore, the proper ways to process parameters in the traffic volume forecast model are introduced and the algorithm to find model scale is also presented. The steps to optimize real-time forecast model parameters based on on-line traffic volume are demonstrated And, Akaike ACI Method is introduced and used in this research to determine appropriate model scale for tunnel traffic. Moreover, model parameters and Green functions are calculated and forecast results are demonstrated and compared with real traffic conditions.Tunnel Ventilation project calculation is the fundament of tunnel ventilation control. Tunnel ventilation fuzzy logic control is designed and developed based on tunnel traffic forecast and tunnel ventilation calculation. Tunnel ventilation system can compare the real-time contaminant measurement with designed carbon monoxide concentration and, by using tunnel ventilation functions in traffic volume forecast, future contaminant change can be calculated and predicted. Thus, contaminant difference and its change rate are used as main inputs of fuzzy logic control which will modulate the number of jet fans serving for ventilation. The basic principle of fuzzy logic control is to decrease the number of running jet fans when carbon monoxide concentration is lower than controlled goal and contaminant will decrease according to forecast; while increase the number of running jet fans when carbon monoxide concentration is higher than controlled goal and contaminant will increase according to forecast.To consider natural wind and traffic ventilation caused by vehicle movement, a wind-speed modified fuzzy logic strategy is developed. Win-speed, as another input, modifies previous fuzzy logic developed based on controlled error and forecast. The major aim is to increase fan number to compensate inadequate ventilation effect because of low wind speed.Tunnel fuzzy logic ventilation control strategies are implemented on tunnel ventilation control system. In iCentroView central management computer, strategies is realized which drive fans to achieve ventilation needs. This method can be used as general guide and demonstration for urban tunnel ventilation control - a more and more common project in civil and control engineering.