Application of Fuzzy Logic on Thermal Comfort Control of Mass Rapid Transit Air-Conditioning System

• Main Authors: CHEN BO-REN, 陳柏任
• Other Authors: 張永宗
• Format: Others
• Language: zh-TW
• Published: 2016
• Online Access: http://ndltd.ncl.edu.tw/handle/2npner

碩士 === 國立臺北科技大學 === 冷凍空調工程系所 === 104 === The thesis designed a smart monitoring system regarding passengers’ comfort perceptions when getting in/out of MRT stations, based on the Predicted Mean Vote (PMV) model proposed by Danish scholar P. O. Fanger in 1972, which was used as an indicator for thermal comfort perceptions in an indoor environment. The system was equipped with functions of indoor and outdoor environmental monitoring and smart controls. Through the weather computer within the environmental monitoring system at the control center, the temperature and humidity information from the Taipei Weather Station, of the Taiwans Central Weather Bureau were retrieved. Then, the Temperature-Humidity Index (THI) was calculated by the Digital Direct Control (DDC) and passengers’ clothing parameters were setup. The maximum number of people accessing MRT station can be retrieved through the data computation come from the Automatic Fare Collection (AFC) system. By introducing the obtained data about peak hours into the PMV system at stations and through various sensors to obtain indoor and outdoor environmental conditions, then the MRT stations’ current central air-conditioning mode was eventually calculated based on Fuzzy Logic, in order to control the central air-conditioning system. The system developed in this thesis was able to effectively maintain indoor comfort at the users’ set target values. For the same station to achieve the target indoor temperature under two different outdoor air environments, the PMV Fuzzy Logic system at an average power consumption of 177 kw, in comparison to the LEE system at 180 kw.