Development of a novel hybrid frost detection and defrost system for refrigeration systems and its applications

The repetitive collection of biological samples and their preservation for analyses at a later stage is a key aspect of biomedical research. Millions of samples collected every day around the world may degrade if proper storage conditions are not provided. Therefore, it is imperative to have a storage facility that is efficient enough to preserve the integrity of these samples over time. Refrigeration systems play a crucial role in delaying the degradation process of samples by maintaining suitable thermal conditions in storage facilities. However, the unremitting operation of the refrigeration system and the presence of moisture inside the storage facility may result in frosting on the surface of the evaporator. The frosting is a phenomenon most detrimental to the performance of refrigeration systems, as it directly affects the heat transfer process inside the refrigerator cabin. The workload on the compressor increases many folds under frosting conditions and the refrigerator struggles to maintain the desired temperature. Consequently, the energy consumption and the probability of stored samples degradation over time increases. The commercial refrigeration systems use a blind and periodic defrosting cycle without any quantification of frost, which leads to lower efficiencies. Therefore, there is a need for an intelligent system that not only detects the presence of frost but also takes countermeasures to defrost the evaporator on-demand, without affecting the quality of stored samples. In the first part of this research study, a hybrid frost detection – defrosting system (HFDDS) is developed that is comprised of a novel photo-capacitive sensing technique and a dual-purpose additively manufacturable sensor and defrosting heater. The HFDDS can detect the formation of frost, measures the thickness of frost from 1.3 to 8 mm with a 5% margin of error, and triggers a defrosting response once a critical frost thickness is attained. The HFDDS is targeted to provide a defrosting on-demand instead of the inefficient blind and periodic defrosting for the refrigeration systems. In the second part of this research study, a novel real-time thickness of the frost-based defrost-on demand technique is presented for refrigeration systems. The hybrid frost detection and defrost system developed in the first part, is employed to quantify the thickness of frost in real-time and to defrost the evaporator using a 12 W heater. The effect of the thickness of the frost-based defrost threshold on the energy consumption of the refrigerator is evaluated. The defrost threshold of 6 mm yields the maximum energy conservation of 10% as compared to the default blind and periodic defrost strategy of the test refrigerator. In the third part of this research study, a novel, frost feedback-based distributed defrosting approach to minimize the defrost desynchronization is proposed. The evaporator is divided into three regions based on the frost distribution pattern. Each of these regions was equipped with an additively manufactured low-powered defrost heater controlled by an optical frost feedback sensor. The frost feedback-based distributed approach proved to be effective in eliminating the defrosting desynchronization. The frost feedback enables the system to terminate defrosting as soon as the frost in the discretized region melts, which reduced the defrost energy significantly. The distributed approach minimizes the rise in the cabin temperature during defrosting and therefore, leads to the reduction of energy spent in the subsequent recovery cycle. The results of the frost feedback-based distributed approach were compared to the default temperature-based strategy using a single defrost heater. The frost feedback-based operation of the three distributed defrost heaters at 6 W each demonstrated maximum overall energy conservation of 18.9% as compared to the default temperature-based strategy.