The main purpose of a tunnel ventilation system is to maintain CO pollutant concentration and visibility index (VI) under an adequate level to provide drivers with a comfortable and safe driving environment. Moreover, it is necessary to minimize power consumption used to operate the ventilation system. To achieve the objectives, fuzzy control (FLC) methods have been usually utilized due to the complex and nonlinear behavior of the system. The membership functions of the FLC consist of the inputs such as the pollutant level inside the tunnel, the pollutant emitted from passing vehicles, and the output such as the number of running jet-fans. Conventional fuzzy control methods rely on simple experiences and trial and error methods. In this paper, the FLC was optimally redesigned using the genetic algorithm (GA), which is a stochastic global search method. In the process of constructing the objective function of GA, two objectives listed above were included: maintaining an adequate level of the pollutants and minimizing power consumption. The results of extensive simulations performed with real data collected from existing tunnel ventilation system are provided in this paper. It was demonstrated that with the developed controller, the pollutant level inside the tunnel was well maintained near the allowable limit and the energy efficiency was improved compared to conventional control schemes.
- Fuzzy logic controller (FLC)
- Real-valued genetic algorithm (GA)
- Tunnel ventilation control
ASJC Scopus subject areas
- Civil and Structural Engineering