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A potent numerical model coupled with multi-objective NSGA-II algorithm for the optimal design of Stirling engine

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  • Ahmed, Fawad
  • Zhu, Shunmin
  • Yu, Guoyao
  • Luo, Ercang

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.

Suggested Citation

  • Ahmed, Fawad & Zhu, Shunmin & Yu, Guoyao & Luo, Ercang, 2022. "A potent numerical model coupled with multi-objective NSGA-II algorithm for the optimal design of Stirling engine," Energy, Elsevier, vol. 247(C).
    • Handle: RePEc:eee:energy:v:247:y:2022:i:c:s0360544222003711
    DOI: 10.1016/j.energy.2022.123468
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    References listed on IDEAS

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    1. Babaelahi, Mojtaba & Sayyaadi, Hoseyn, 2015. "A new thermal model based on polytropic numerical simulation of Stirling engines," Applied Energy, Elsevier, vol. 141(C), pages 143-159.
    2. Babaelahi, Mojtaba & Sayyaadi, Hoseyn, 2014. "Simple-II: A new numerical thermal model for predicting thermal performance of Stirling engines," Energy, Elsevier, vol. 69(C), pages 873-890.
    3. Timoumi, Youssef & Tlili, Iskander & Ben Nasrallah, Sassi, 2008. "Design and performance optimization of GPU-3 Stirling engines," Energy, Elsevier, vol. 33(7), pages 1100-1114.
    4. Mehdi KESHAVARZ GHORABAEE & Edmundas Kazimieras ZAVADSKAS & Zenonas TURSKIS & Jurgita ANTUCHEVICIENE, 2016. "A New Combinative Distance-Based Assessment(Codas) Method For Multi-Criteria Decision-Making," ECONOMIC COMPUTATION AND ECONOMIC CYBERNETICS STUDIES AND RESEARCH, Faculty of Economic Cybernetics, Statistics and Informatics, vol. 50(3), pages 25-44.
    5. Wang, Kai & Sanders, Seth R. & Dubey, Swapnil & Choo, Fook Hoong & Duan, Fei, 2016. "Stirling cycle engines for recovering low and moderate temperature heat: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 62(C), pages 89-108.
    6. Xiao, Gang & Qiu, Hao & Wang, Kai & Wang, Jintao, 2021. "Working mechanism and characteristics of gas parcels in the Stirling cycle," Energy, Elsevier, vol. 229(C).
    7. Ni, Mingjiang & Shi, Bingwei & Xiao, Gang & Peng, Hao & Sultan, Umair & Wang, Shurong & Luo, Zhongyang & Cen, Kefa, 2016. "Improved Simple Analytical Model and experimental study of a 100W β-type Stirling engine," Applied Energy, Elsevier, vol. 169(C), pages 768-787.
    8. Timoumi, Youssef & Tlili, Iskander & Ben Nasrallah, Sassi, 2008. "Performance optimization of Stirling engines," Renewable Energy, Elsevier, vol. 33(9), pages 2134-2144.
    9. de la Bat, B.J.G. & Dobson, R.T. & Harms, T.M. & Bell, A.J., 2020. "Simulation, manufacture and experimental validation of a novel single-acting free-piston Stirling engine electric generator," Applied Energy, Elsevier, vol. 263(C).
    10. Wang, Kai & Dubey, Swapnil & Choo, Fook Hoong & Duan, Fei, 2016. "A transient one-dimensional numerical model for kinetic Stirling engine," Applied Energy, Elsevier, vol. 183(C), pages 775-790.
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    Cited by:

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    3. Shang, Jingyi & Gao, Jinfeng & Jiang, Xin & Liu, Mingguang & Liu, Dunnan, 2023. "Optimal configuration of hybrid energy systems considering power to hydrogen and electricity-price prediction: A two-stage multi-objective bi-level framework," Energy, Elsevier, vol. 263(PF).

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