Dissertation > Industrial Technology > Building Science > Housing construction equipment > Air-conditioning, heating, ventilation,and its equipment > Air-conditioning

Study on Intelligent TCI & IAQ-Based Air-Conditioning Control

Author DaiChaoHua
Tutor YuNanYang
School Southwest Jiaotong University
Course Heating for the gas ventilation and air conditioning engineering
Keywords Thermal Comfort Index Indoor air quality predicted mean vote Intelligent PMV Predictor CO2-Based Demand-Controlled Ventilation Fuzzy Control Inverter Air-Conditioner Computer Simulation
Type Master's thesis
Year 2004
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People typically spend over 80 percent of their time indoors where,however,is far from health and comfort in terms of thermal comfort index(TCI)and indoor air quality(IAQ).The idea of using predicted mean vote(PMV), indicating human thermal comfort, and carbon dioxide(CO2) concentration, indicating occupancy and indoor air quality(IAQ), as control inputs to develop control strategies for a residence is proposed by varying inverter air-conditioner compressor frequencies, evaporator fan speeds, fresh air valve positions(or fresh air fan speeds), and the desk fan speeds respectively with PMV within a range from 0 to 0.5 and CO2 under lOOOppm. Computer simulations of thermal comfort and indoor air quality in a standard air-conditioned office compartment is conducted by modeling air conditioner system. At the same time, the analysis of energy consumption is carried out with CI control compared with the conventional temperature and relative humidity control and CO2-based DCV compared with the target per-person ventilation rates. In addition, the development of intelligent ANN-based PMV predictor are presented.The conclusions can be drawn from the research as follows:a. It is reliable to predict PMV by the use of Neural Network.b.The target per-person ventilation rates of the minimum up to 30 steres per person per hour of the flow rate of fresh air in accordance with "Indoor Air Quality Standard" can assure CO2 under 1000ppm. However, CO2-based demand-controlled ventilation (CO2-based DCV) systems can keep an acceptable indoor air quality with a CO2 setpoint of 1000ppm, and energy can be conserved in the indoor spaces where CO2 is suitableto reflect IAQ porformence. Fortunately, CO2-based DCV consumes 5% less than the strategy which acquires the flow rate by multiplying actual occupants by 30m3 per person per hour, and up to 17% less than the one which achieves the flow rate by multiplying 12 occupants by 30m3 per person per hour. Interestedly,the conventional set-point control algorithms comply with the same rule.c. Thermal comfort can be maintained even with the conventional temperature and humidity control only if air-conditioner type, control strategy, and control algorithms are considered reasonably. The performace of the strategy concerning temperature and relative humidity simultaneously is inferior to the one concerning only temperature because of cross-coupling,and the later keeps precision around 0. 1C.d.Intelligent CI control,with PMV within a range from 0 to 0.5,can provide superior performance over conventional set-point control in terms of human comfort and energy utilization.The former consumes less energy,over 17% less,compared with the conventional temperature and humidity control algorithms,and still achieves an overall saving of 2%~4% than the conventional set-point temperature control.

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