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Maximum Knowledge Gain through Minimum Number of Experiments: Optimal Experimental Design for Model Evaluation of Heat Pump Compressors
Air-to-water heat pumps with natural refrigerants are subject to dynamic boundary conditions. Thus, many disturbance variables influence heat pump control and lead to uncontrollable operation. The expansion valve control is essential for the compressor's efficiency and operational reliability. On the one hand, a sufficient degree of superheat is necessary to prevent two-phase refrigerant from entering the compressor. On the other hand, a high superheat leads to a high compressor outlet temperature, thus reducing system efficiency. Therefore, the optimal trade-off between efficiency and reliability must be found. This work presents an experimentally validated superheat control for refrigerant cycles that uses the minimum stable superheat and is robust against dynamic changes. For this purpose, we use an operating point-dependent superheat setpoint by determining experimentally the lowest stable superheat at different operating points. A regression model based on optimal experiment design allows multiple input control to consider all disturbance variables. Since unstable operating points lead to uncontrolled oscillations, we use a Fourier transformation for detection and prevention. The experimental validation of the concept underlines the robustness against dynamic influences. The efficiency of the considered system is increased by up to 18 % in specific operating points compared to constant superheat.
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