| Summary: | How the performance of the heat pump dishwasher in drying process is changed under different parameters is explored in the study. An unsupervised data mining framework of “data pre-processing - association rule mining - knowledge interpretation” is established to study the energy-saving operation strategy and achieve the goal of reducing the power consumption in the drying process of the dishwasher. The Apriori algorithm is used to mine the overall set of items to obtain three key factors, namely refrigerant charge, ambient temperature, and air supply method, and the influence of these factors on the overall drying performance is further investigated. The research results show that the heat pump system provides sufficient heat to ensure the drying performance of the system, but too much heat cannot effectively improve the drying performance. The air supply method is the key factor in improving the drying performance of the dishwasher, and alternating the upper and lower air supply can achieve the best drying effect. Therefore, to meet the minimum heat requirement of dishwasher drying, the system’s energy efficiency can be improved by adjusting the air supply method and other factors to achieve energy-saving operation.
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