A potent numerical model coupled with multi-objective NSGA-II algorithm for the optimal design of Stirling engine. (15th May 2022)

• Record Type: Journal Article
• Authors: Ahmed, Fawad; Zhu, Shunmin; Yu, Guoyao; Luo, Ercang
• Is Part Of: Energy. Volume 247(2022)
• Publication Date: 2022-05-15
• Subjects: Stirling engine -- Modeling -- Multi-objective optimization -- NSGA-II -- GPU-3 -- Design; Power resources -- Periodicals; Power (Mechanics) -- Periodicals; Energy consumption -- Periodicals; 333.7905
• DOI: 10.1016/j.energy.2022.123468
• Languages: English
• ISSNs: 0360-5442

Abstract

Abstract: In this article, a novel numerical model of the Stirling engine encompassing a potent loss mechanism coupled with the NSGA-II algorithm is proposed. Multi-objective optimization of GPU-3 Stirling engine was performed using a class of genetic algorithms, namely NSGA-II, with five decision variables to minimize the losses and increase the power output and efficiency of the GPU-3 engine. Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and Combinative Distance-based Assessment (CODAS) decision-making approaches were used to obtain the optimum solution from Pareto optimal space. Furthermore, the optimization results were compared with the experimental results of the GPU-3 Stirling engine. Results from the multi-objective optimization effort indicate that output power increases by approx. 500 W and efficiency enhances by approx. 5%, whereas losses decrease by 516 W. Later, to demonstrate the model's design capability, the developed model and optimization approach, i.e. (NSGA-II), is utilized to develop an optimal design of a beta-type free piston Stirling engine (FPSE) with an indicated power of 10 kW. After optimizing a combination of twelve operating and geometric parameters, the Stirling engine that yields a net power output of about 7.95 kW with a thermal efficiency of about 30% is developed. This work presents a novel and powerful numerical method for the optimal design of Stirling engine. Highlights: Numerical model of the Stirling engine encompassing a loss mechanism is proposed. NSGA-II algorithm is utilized for the optimization of the GPU-3 Stirling engine. TOPSIS & CODAS decision-making approach is used to obtain the optimum solution. Model coupled with NSGA-II is utilized to obtain an optimal design of a 10 kW FPSE.