Design Parameter Optimization of Refrigeration System using Univariate Dynamic Encoding Algorithm for Searches

This paper proposes a method to find a parameter that minimizes the average compressor power for R134a cycle using a univariate dynamic encoding algorithm for searches. optimizing modeling parameters for the refrigeration cycle is difficult because it has several parameters to conFigure such as the sizes of the compressor, the evaporator, the condenser, the cooler fan, and the internal heat exchange. The univariate dynamic encoding algorithm is a searching algorithm for the optimum point under a multivariate system variable with constraints to solve the aforementioned difficulty. The parameters are assigned to the simulation model and the compressor power is logged, then a univariate dynamic encoding algorithm for searches is applied to find the minimum point of the compressor power, corresponding to the modeling parameters. The refrigeration modeling parameters are optimized by the proposed method with the modeled specifications. The optimization results ensure the average compressor power of 28. 65W with system parameters related to the condenser, and evaporator.