Design and Performance Evaluation of an Autonomous Air-Conditioner Cleaning System for Energy-Efficient Moisture Removal and Microbial Suppression
Source abstract
Abstract
An automated air-conditioner cleaning system was developed as a retrofit solution for conventional split-type units to reduce residual moisture in the evaporator section and suppress post-shutdown microbial accumulation. The system was integrated with an 18,000 BTU h−1 air-conditioner and implemented using an Arduino-based closed-loop control platform with temperature and relative humidity monitoring. After shutdown, the indoor fan was operated under low-, medium-, or high-speed conditions to remove retained moisture from the cooling coil. System performance was evaluated in an 18 m3 test room through measurements of electrical consumption, operating cost, relative humidity, and microbial contamination in room air and on the evaporator coil before and after system installation. Low-speed operation showed the lowest current demand, power consumption, and electricity cost, with corresponding values of 0.36 ± 0.01 A, 79.2 ± 0.8 W, and 0.47 THB per 150 min. Post-shutdown humidity reduction was achieved under all tested conditions, while the high-speed mode provided the fastest drying response, reducing relative humidity to approximately 60% within 120 min. In the room air, the greatest reduction in airborne fungi after shutdown was observed at low speed, whereas the greatest reduction in airborne bacteria was observed at medium speed. On the evaporator coil, the strongest bacterial suppression was obtained at low speed, where the bacterial count after 24 h decreased from 633.33 ± 34.27 CFUs before installation to below the detection limit after installation. These results indicate that the proposed system reduced moisture retention and microbial contamination with minimal energy consumption.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Indoor Air Quality and Microbial Exposure · Hygrothermal properties of building materials · Food Safety and Hygiene
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Industrial Education, Faculty of Education, Srinakharinwirot University, Bangkok 10110, Thailand
Department of Curriculum and Instruction, Faculty of Education, Srinakharinwirot University, Bangkok 10110, Thailand
Department of Electrical Engineering, Faculty of Engineering, Srinakharinwirot University, Nakhon Nayok 26120, Thailand
Funding
Faculty of Education, Srinakharinwirot University
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