Development of a control algorithm employing data generated by a white box mathematical model

The optimization of vapor compression refrigeration systems to improve their energetic efficiency has become an important goal of the field of thermal engineering. To this end, a refrigeration capacity control that operates through the continuous adjustment of the compressor speed and the opening of the expansion valve has been utilized. To develop the algorithm responsible for these adjustments, it is necessary to gather information about the refrigeration system's dynamics. This information is generally obtained from experimental data, which is not always available. This study presents the development of a concentric tube evaporator mathematical model. After being validated with experimental data, this mathematical model was utilized to generate the information on the system dynamics that is necessary to project an adaptive multivariable controller. The obtained results showed that the proposed model can be used to describe refrigeration machine dynamics and that this information can be used in the controller design.

► The model was validated in steady-state and dynamic conditions using experimental data.
► A variable maximum error was utilized to address the problem caused by the change in the heat transfer coefficient.
► The heat transfer coefficient of the liquid deficient region was estimated using a third-order polynomial.
► A full multivariable adaptive controller was developed using the data generated by the proposed model.