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Thirumal, P., Amirthagadeswaran, K.S., Jayabal, S.. (1394). FUZZY RULE BASED PREDICTION OF IAQ CHARACTERISTICS IN AIR CONDITIONED CAR. , 39(M2), 437-450. doi: 10.22099/ijstm.2015.3251
P. Thirumal; K.S. Amirthagadeswaran; S. Jayabal. "FUZZY RULE BASED PREDICTION OF IAQ CHARACTERISTICS IN AIR CONDITIONED CAR". , 39, M2, 1394, 437-450. doi: 10.22099/ijstm.2015.3251
Thirumal, P., Amirthagadeswaran, K.S., Jayabal, S.. (1394). 'FUZZY RULE BASED PREDICTION OF IAQ CHARACTERISTICS IN AIR CONDITIONED CAR', , 39(M2), pp. 437-450. doi: 10.22099/ijstm.2015.3251
Thirumal, P., Amirthagadeswaran, K.S., Jayabal, S.. FUZZY RULE BASED PREDICTION OF IAQ CHARACTERISTICS IN AIR CONDITIONED CAR. , 1394; 39(M2): 437-450. doi: 10.22099/ijstm.2015.3251

FUZZY RULE BASED PREDICTION OF IAQ CHARACTERISTICS IN AIR CONDITIONED CAR

Iranian Journal of Science and Technology Transactions of Mechanical Engineering
مقاله 12، دوره 39، M2، دی 2015، صفحه 437-450    اصل مقاله (1.36 M)
نوع مقاله: Research Paper
شناسه دیجیتال (DOI): 10.22099/ijstm.2015.3251
نویسندگان
P. Thirumal* 1؛ K.S. Amirthagadeswaran2؛ S. Jayabal3
1Dept. of Mechanical Engineering, Government College of Engineering, Bargur, India
2Dept. of Mechanical Engineering, Government College of Technology, Coimbatore, India
3Dept. of Mechanical Engineering, A.C. College of Engineering Technology, Karaikudi, India
چکیده
Air conditioning is widely applied for the improvement of standard of living in human life. This present investigation focused on the prediction of indoor air quality characteristics of air conditioned car using fuzzy logic algorithm. The conditioned space was selected and the experiments were planned as per design of experiments to study the effect of human load, fresh air supply and air velocity on the human comfort conditions. The mathematical models were developed to predict the comfort conditions, namely temperature, CO2 level and relative humidity over a specified range of input conditions. Carbon dioxide exhalation rate differs person to person based on their body weight and burning rate of calories, etc. Fuzzy logic predicted the intermediate response of IAQ parameters for varying input conditions in this present investigation. The proposed multi response fuzzy model predicted better results comparing with nonlinear regression models. The absolute error percentage of fuzzy model for carbon dioxide level, temperature and relative humidity is 2.05%, 3.81 % & 2.24 % respectively.
کلیدواژه‌ها
Indoor air quality؛ temperature؛ Relative humidity؛ carbon dioxide؛ Fuzzy Logic
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