Experimental Analysis of a Genetic-Fuzzy Inverter DX VAV A/C System for Automatically Ventilated Buildings

Abstract In recent years, the quest has been focused on energy efficient building design. To achieve this in terms of high efficiency air conditioning schemes for hot climate cooling, the combination of variable refrigerant volume (VRV) with variable air volume (VAV) systems have become popular. In this paper, attention is focused on achieving good thermal comfort and indoor air quality (IAQ) combined with energy savings by using multi-zone VAV air conditioning (A/C) that incorporates a genetic based fuzzy logic controller (FLC). Experimental analysis based on a combined demand controlled ventilation (DCV) with economizer cycle (EC) was performed on an inverter driven multi-zone direct expansion (DX) VAV A/C system integrated with a fuzzy logic controller and optimized by a genetic algorithm (GA). The opening of the VAV box damper was controlled using the fuzzy logic controller. Based on the test results, the proposed fuzzy logic operated system maintained supply air temperature close to 13°C and an occupant zone at a consistent temperature of around 24 °C. In DCV mode, the concentration of CO2 was maintained between 950 ppm and 1040 ppm while, when the system was operated under a combined DCV-EC ventilation scheme, the CO2 concentration was maintained at between 350 ppm and 970 ppm. The experimental results suggested that CO2 concentration obtained experimentally was well within the permissible limit for the varying load conditions. Under the combined DCV-EC mode of ventilation, using a fuzzy-genetic algorithm, the maximum power obtained for the supply air fan and variable speed compressor was 415 W and 3.4 kW respectively. The compressor was totally turned OFF during the economizer cycle thus contributing to total power savings. The energy savings potential of the proposed fuzzy controlled multi-zone DX VAV A/C system yielded 70% and 89% under DCV and combined DCV economizer cycle ventilation modes respectively when compared with a constant air volume (CAV) A/C system operated under the DCV technique. The test results suggested that it was feasible for this fuzzy control methodology, integrated with the developed genetic algorithm, to provide a proper control of IAQ, thermal comfort and energy conservation.