Abstract: In certain harsh operating conditions,a significant amount of frost may be accumulated in frost-free refrigerators. Using conventional defrost control logic makes it difficult to completely remove the frost,which can cause the fan to stop and result in an increase in the refrigerator compartment temperature,thereby affecting cooling performance. To address this issue,based on conventional defrost logic and combined with experimental measured data,a fan defrost control method based on fuzzy logic and adaptive control is proposed. Fan operation parameters are collected and analyzed with this method and the a fan fault prediction model can be established. According to the prediction results,the conditions for entering and exiting defrost are adjusted dynamically,enabling intelligent management and maintenance of the fan. According to experimental,under high-temperature and high-humidity harsh conditions the refrigeration efficiency of refrigerators can be improved significantly compared with conventional defrost control methods. The defrost energy consumption of the tested samples are reduced by around 10%,and predicted product lifespan is extended by 30%.

Key words: Fan, defrost, fault detection, optimization control