Conference Year



Ice maker, transient simulation


Automatic commercial ice making machines that produce a batch of cube ice at regular intervals are known as “cubers”. Such machines are commonly used in food service, food preservation, hotel, and health service industries.  Machines are typically rated for the weight of ice produced over a 24 hour period at ambient air temperatures of 90°F and water inlet temperature of 70°F. These cubers typically utilize an air-cooled, vapor-compression cycle to freeze circulating water flowing over an evaporator grid. Once a sufficient amount ice is formed, a valve switches to enable a harvest mode, where the compressor’s discharge gas is routed into the evaporator, thereby releasing ice into a storage bin. The U.S. Department of Energy has set a target of reducing energy usage by 10 – 15% by 2018.  Engineering models are not publicly available to assist designers in achieving the new energy regulations. This paper presents an engineering simulation model that addresses this need. This model simulates the transient operation of a cuber ice machine based on fundamental principles and generalized correlations. The model calculates time-varying changes in the system properties and aggregates performance results as a function of machine capacity and environmental conditons.  Rapid “what if” analyses can be readily completed, enabling engineers to quickly evaluate the impact of a variety of system design options, including the size of the air-cooled heat exchanger, finned surfaces, air / water flow rate, ambient air and inlet water temperature, compressor capacity and/or efficiency for freeze and harvest cycles, refrigerants, suction/liquid line heat exchanger and thermal expansion valve properties. Simulation results from the model were compared with the experimental data of a fully instrumented, standard 500 lb capacity ice machine, operating under various ambient air and water inlet temperatures. Key aggregate measures of the ice machine’s performance are: (1) cycle time (duration of freeze plus harvest cycles), (2) Energy input per 100 lb of ice, and (3) Energy usage during 24 hours. For these measures, the model’s accuarcy is within 5% for a variety of operating conditions.Â