Optimization of critical system outputs of the Stirling cycle using Taguchi-based grey relational analysis

Abstract

This study investigated the Stirling cycle's thermodynamic parameters using the Taguchi and Taguchi-based grey relational analysis methods. The Taguchi analysis identified the most crucial parameters for each objective (net work output, thermal efficiency, second law efficiency, charge pressure, irreversibility, entropy production), quantifying their contribution ratios. Subsequently, the grey relational analysis method was performed as multi-objective optimization to achieve all objectives simultaneously. In single-objective optimizations, it is found that the importance of parameters varies according to the objects, and there is not a single pattern. By applying the Taguchi method to grey relational analysis, it is found that the impact ratios of minimum temperature (19.82%), maximum temperature (19.40%), charge pressure (19.44%), expansion volume (21.57%), and compression volume (19.78%) on all objectives were found. In addition, best and worst-case scenarios were obtained for single-objective and multi-objective optimizations. Based on Taguchi-based grey relational analysis, the best parameter set that satisfies all objectives includes 450 K minimum temperature, 1300 K maximum temperature, 5000 Pa charge pressure, 0.001 m³ expansion volume, and 0.15 m³ compression volume. The grey relational analysis method achieved a parameter set that improved energy while maintaining acceptable net work output.