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Analytical closed-form model for predicting the power and efficiency of Stirling engines based on a comprehensive numerical model and the genetic programming

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  • Babaelahi, Mojtaba
  • Sayyaadi, Hoseyn

Abstract

High accuracy and simplicity in use are two important required features of thermal models of Stirling engines. A new numerical second-order thermal model was presented through the improvement of our previous modified-PSVL model in order to have an elevated accuracy. The modified-PSVL model was modified by considering a non-isothermal model for heater and cooler. Then, the model called as CPMS-Comprehensive Polytropic Model of Stirling engine, was used to simulate the GPU-3 Stirling engine, and the obtained results were compared with those of the previous thermal models as well as the experimental data. For the sack of the simplicity, the combination of the CPMS model and genetic programming was employed to generate analytical closed-form correlation. In this regards, a comprehensive data bank of results of the CPMS was constructed and exported to the GP tool and analytical expressions of the power, efficiency, and polytropic indexes were obtained. It was shown that the analytical correlations not only had the same accuracy as the CPMS model, but also, it can be simply used without difficulties of numerical models. The CPMS and its out coming analytical expressions, predicted the power and efficiency of the GPU-3 Stirling with +1.13% and +0.45 (as difference), respectively.

Suggested Citation

  • Babaelahi, Mojtaba & Sayyaadi, Hoseyn, 2016. "Analytical closed-form model for predicting the power and efficiency of Stirling engines based on a comprehensive numerical model and the genetic programming," Energy, Elsevier, vol. 98(C), pages 324-339.
    • Handle: RePEc:eee:energy:v:98:y:2016:i:c:p:324-339
    DOI: 10.1016/j.energy.2016.01.031
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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.
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    Cited by:

    1. Sayyaadi, Hoseyn & Ghorbani, Ghadir, 2018. "Conceptual design and optimization of a small-scale dual power-desalination system based on the Stirling prime-mover," Applied Energy, Elsevier, vol. 223(C), pages 457-471.
    2. Dong-Jun Kim & Yeongchae Park & Tae Young Kim & Kyuho Sim, 2022. "Design Optimization of Tubular Heat Exchangers for a Free-Piston Stirling Engine Based on Improved Quasi-Steady Flow Thermodynamic Model Predictions," Energies, MDPI, vol. 15(9), pages 1-20, May.
    3. Babaelahi, Mojtaba & Mofidipour, Ehsan & Rafat, Ehsan, 2019. "Design, dynamic analysis and control-based exergetic optimization for solar-driven Kalina power plant," Energy, Elsevier, vol. 187(C).
    4. 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).
    5. Karabulut, Halit & Okur, Melih & Halis, Serdar & Altin, Murat, 2019. "Thermodynamic, dynamic and flow friction analysis of a Stirling engine with Scotch yoke piston driving mechanism," Energy, Elsevier, vol. 168(C), pages 169-181.
    6. Qiu, Hao & Wang, Kai & Yu, Peifeng & Ni, Mingjiang & Xiao, Gang, 2021. "A third-order numerical model and transient characterization of a β-type Stirling engine," Energy, Elsevier, vol. 222(C).
    7. Babaelahi, Mojtaba & Mofidipour, Ehsan & Rafat, Ehsan, 2020. "Combined Energy-Exergy-Control (CEEC) analysis and multi-objective optimization of parabolic trough solar collector powered steam power plant," Energy, Elsevier, vol. 201(C).

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