Performance optimization of a free piston stirling engine using multi-section regenerators based on the response surface methodology

Pengfan Chen, Geyu Zhong, Yafeng Niu and Yingwen Liu

Energy, 2022, vol. 261, issue PB

Abstract: In this paper, a TD-Sage model of a beta-type free piston Stirling engine (β-FPSE) is put forward, which combines thermodynamic-dynamic model with the Sage model. Considering the inhomogeneous distribution of thermal penetration depth, multi-section wire mesh regenerators are proposed to enhance the performance of the FPSE based on the response surface methodology (RSM) and desirability approach. The quadratic regression models of power and efficiency are derived based on the analysis of variance, and the maximum deviation between prediction values from RSM model and actual values from Sage model is less than 5%. The interactive effects of the factors are analyzed and the available energy loss (AE loss) analysis is presented to interpret the mechanism of improvement. The optimal design parameters of two- and three-section regenerators are obtained. Moreover, the maximum output power is obtained when the AE loss of the regenerator is minimized. Compared with the optimal single-section regenerator, the optimal two-section regenerator that consists of meshes with mesh number of 60# (50%) and 80# (50%) improves the power and efficiency by approximately 3.6% and 5.8% respectively. The optimal three-section regenerator that consists of meshes with mesh numbers of 60# (43%), 80# (25%), and 90# (32%) improves the power and efficiency by approximately 4.1% and 6.7%, respectively.

Keywords: Free piston stirling engine; Multi-section regenerator; Response surface methodology; Optimization (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:261:y:2022:i:pb:s0360544222021107

DOI: 10.1016/j.energy.2022.125221

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