Model-based optimization for vapor compression refrigeration cycle

Lei Zhao, Wenjian Cai, Xudong Ding, Weichung Chang

Research output: Contribution to journalArticleResearchpeer-review

34 Citations (Scopus)


This paper presents a model-based optimization strategy for vapor compression refrigeration cycle. Through analyzing each component characteristics and interactions within the cycle, the optimization problem is formulated as minimizing the total operating cost of the energy consuming devices subject to
the constraints of mechanical limitations, component interactions, environment conditions and cooling load demands. A MGA (modified genetic algorithm) together with a solution strategy for a group of nonlinear equations is proposed to obtain optimal set point under different operating conditions. Simulation studies are conducted to compare the proposed method with traditional one-off control strategy to evaluate its performance. Experiment results of a real practical system are also presented to demonstrate its feasibility
Original languageEnglish
Pages (from-to)392-402
Number of pages11
Publication statusPublished - 2013
Externally publishedYes


  • Vapor compression refrigeration cycle
  • Hybrid components models
  • Global optimization
  • Modified genetic algorithm
  • System simulation and testing

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