Enhancing Gamma Stirling Engine Performance through Genetic Algorithm Technique

Abstract

The Stirling engine, invented in 1816, was initially lacking comprehensive scientific understanding, which only surfaced after a considerable 50-year period. In the present era, impressive strides have been made in enhancing the performance of Stirling engines by implementing thermodynamic cycles. Despite these advancements, there remains untapped potential for further improvements by applying soft computing methods. To address this, the focal point of this research paper centres around optimizing the Stirling engine, specifically focusing on a gamma-type double-piston Stirling engine and leveraging genetic algorithms to achieve the desired enhancements. The results from this analysis are meticulously compared with experimental data, validating the approach’s efficacy. Additionally, this paper explores the potential impact of utilizing cryogenic fluids as coolants on the Stirling engine’s performance.

Keywords

• Stirling engine
• thermodynamics
• power
• efficiency
• genetic algorithm