Enhanced-efficiency operating variables selection for vapor compression refrigeration cycle system |
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| Affiliation: | 1. School of Mechanical Engineering, Purdue University, West Lafayette, IN 47907, USA;2. Department of Mechanical and Information Engineering, University of Seoul, 163 Seoulsiripdae-ro, Dongdaemun-gu, Seoul 02504, Republic of Korea;3. Interdisciplinary Major of Maritime AI Convergence, Department of Mechanical Engineering, Korea Maritime & Ocean University, 727 Taejong-ro, Yeongdo-gu, Busan 49112, Republic of Korea |
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| Abstract: | In this paper, a novel enhanced-efficiency selection of operating variables based on self-optimizing control (SOC) method for the vapor compression refrigeration cycle (VCC) system is proposed. An objective function is proposed to maximize the energy efficiency of the VCC system while meeting with the demand of indoor thermal comfort. With the detailed analysis of operating variables, three unconstrained degrees of freedom are selected among all the candidate operating variables. Then two SOC methods are applied to determine the optimal individual controlled variables (CVs) and measurement combinations as CVs. The model predictive control (MPC) method based controllers and PID controllers are designed for different sets of CVs, and the experimental results indicate that the proposed selection of CVs can achieve a good trade-off between optimal (or near optimal) stable operation and enhanced-efficiency of the synthesized control structure. |
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| Keywords: | Vapor compression refrigeration cycle Operating variables Self-optimizing control Model predictive control Energy efficiency |
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