Multi-objective design optimisation of a rotary compressor

摘要

This paper presents a design optimisation of a rolling piston compressor using a multi-objective optimisation technique that employs a genetic and evolutionary algorithm. The procedures begin with a pool of compressor designs called population, that were generated pseudo-randomly based on the preset constraints, to arrive at a set of optimum trade-off solutions from the various multiple objective functions set that allows the designer to choose the optimum design that best suits their needs. The optimum solutions allow designers to choose the design that best suited their needs. The cases under examination attempts to optimise combinations of some 9 objective functions namely the COP, refrigerating capacity, motor input power, friction power, indicated work, discharge valve loss, suction valve loss, compressor overall size and machine cost. There are 18 design variables of the compressor that are allowed to vary during the optimisation process and these are bounded by the 23 preset constraints. The results show an effective employment of the multi-objective optimisation technique in compressor design.