Abstract
This work gives insight in the development and the application of a semi-implicit transient cycle simulation tool. The model consists of subcomponents that are independently validated and coupled in order to shape a fully functional cycle simulation. The methods used comprise empirical models, artificial neural networks or more complicated, transient 1d finite volume formulations for two-phase flow.
The validation of the cycle simulation is carried out using data from a specially equipped domestic freezer. The model is calibrated to one operating point and afterwards tested under varying ambient temperatures and thermostat settings. The agreement compared to measurements is 6.9% mean and 5.5% standard deviation of the total electric energy consumption. Furthermore, parameters like refrigerant distribution, pressure drop, temperature or mass flow rate can be monitored.
The validation of the cycle simulation is carried out using data from a specially equipped domestic freezer. The model is calibrated to one operating point and afterwards tested under varying ambient temperatures and thermostat settings. The agreement compared to measurements is 6.9% mean and 5.5% standard deviation of the total electric energy consumption. Furthermore, parameters like refrigerant distribution, pressure drop, temperature or mass flow rate can be monitored.
Original language | English |
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Pages (from-to) | 28-41 |
Journal | International Journal of Refrigeration |
Volume | 69 |
DOIs | |
Publication status | Published - 2016 |