Journal
ENERGY
Volume 272, Issue -, Pages -Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.energy.2023.127030
Keywords
Dynamic modeling; Air-source heat pump; Non-uniform frost formation; Reverse-cycle defrosting
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Frost accumulation on evaporator coil surfaces can greatly affect the performance of air-source heat pump systems. This paper presents a dynamic modeling framework that can simulate the behavior of ASHP systems during frost and defrost cycles, and experimental validations show that the model accurately captures the cycling behaviors and is reliable.
Frost accumulation on evaporator coil surfaces can significantly degrade the performance of air-source heat pump (ASHP) systems in winter operations. The continued buildup of frost eventually necessitates a defrosting mode to remove the accumulated frost and return the system to its normal operating characteristics. A simulation tool capable of capturing the system dynamics with continuous mode-switching between heating and defrosting operation is extremely useful in the development and evaluation of improved control designs. However, first-principles simulation of a reverse-cycle defrost imposes a variety of numerical challenges includ-ing mode switching and flow reversal. This paper presents a comprehensive dynamic modeling framework that could overcome the challenges and experimental validations for ASHPs under cycling of frosting and defrosting operations. A complete first-principles ASHP cycle model is described where frost formation and melting models are integrated into a finite volume evaporator model to characterize the cycle behavior with non-uniform frost formation and melting. Comparisons of simulation results against experimental data collected from a residential heat pump unit indicate that the developed model is able to accurately capture the cycling behaviors of the ASHP system between heating and defrosting operations. In addition, no state event occurred during the simulation despite the presence of mode switching and flow reversal, strongly supporting the reliability of the proposed modeling approaches.
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