Control Research Of Subway Carriages Air-conditioning Based On Particle Swarm Optimization Algorithm

With our country economic development, rapid growth of urban population, urban traffic congestion increasingly. Subway trains, as a kind of high efficiency, large amount of commuting and comfortable transportation means, has become every big city traffic. Due to the depths of the subway underground is also a stream of people gathered in public places, to create a comfortable environment for subway car has become our aim. Therefore, this project will use subway carriages variable air volume air-conditioning, This system can not only satisfy the requirement of the thermal comfort of passengers, but also can achieve the maximum energy saving.This article is based on the Shenyang subway as the research background, in order to meet the passenger comfort and energy saving for the purpose, to control the subway carriages variable air volume air-conditioning system. In order to better study and exploration of the subway car passenger thermal comfort, This article is based on the PMV-PPD evaluation index and domestic and international standards, as the research object of subway carriages air-conditioning system. And, introduction the composition of subway carriages air-conditioning system and the end of control system in detail.The control process of subway carriages variable air volume air-conditioning is a big inertia?pure time-delay?nonlinear and time-varying complex system, using the traditional control method is difficult to obtain the best control effect. Based on these characteristic, This article focuses on subway car control research of variable air volume air conditioning system and carry out the following research work to achieve a better effect of energy saving and comfortable.First of all, in this paper, the temperature, humidity, carbon dioxide sensor with a comfort level detection unit, single chip in each subway car air conditioning system for the front. Then use multi-sensor detection car information such as temperature, humidity, CO2 concentration to meter. Through in each carriages comfort level fusion detection unit for car air comfort parameters.Second, apply the Fuzzy theory to the design of PID controller, while the Fuzzy-PID control compared with the traditional PID control has significant control effect, Fuzzy-PID control still exist many problems, such as:lack of controller modeling of systematization and difficult to determine the membership function parameters. In order to get better control effect, this paper puts forward Fuzzy-PID control was optimized by using Particle Swarm Optimization algorithm, to car air comfort as a subway car variable air volume air conditioning system control object, design a good control and energy saving effect of control system.Finally, establishment of subway carriages air-conditioning system mathematical model, and using MATLAB software simulation, the simulation results show that the optimized system of Particle Swarm Algorithm, not only shorten the adjusting time but also stable performance is quite good.