23 September 2011
The base study for the optimal control algorithm of the heat pump system was
investigated. The research object is a heat pump system of the desiccant cooling and vapor
compression hybrid system using solar thermal energy. The severe load change could be
carried to the heat exchangers of the heat pump due to the complexity of this hybrid system.
Therefore the rapid adaptation control of the heat pump is very important for the stable and
reliable operation to the whole system. To study on the refrigeration cycle characteristics, the
heat pump system which consists of the controllable components such as the EEV
(electronic expansion valve) and the variable speed compressor was built. The ANN (artificial
neural network) algorithm was used to relate between the control parameters and the
measured data of the refrigeration cycle. According to the change of rotational frequency of
compressor and the opening of expansion valve, the parameters such as temperatures and
pressures of the refrigeration cycle is changed. In this study, the relation of the control
parameters and the experimentally measured data was found to set the appropriate target
value for the control the heat pump system.