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Power-Optimized Sinusoidal Piston Motion and Its Performance Gain for an Alpha-Type Stirling Engine with Limited Regeneration

Author

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  • Mathias Scheunert

    (Institut für Physik, Technische Universität Chemnitz, 09107 Chemnitz, Germany)

  • Robin Masser

    (Institut für Physik, Technische Universität Chemnitz, 09107 Chemnitz, Germany)

  • Abdellah Khodja

    (Institut für Physik, Technische Universität Chemnitz, 09107 Chemnitz, Germany)

  • Raphael Paul

    (Institut für Physik, Technische Universität Chemnitz, 09107 Chemnitz, Germany)

  • Karsten Schwalbe

    (Institut für Physik, Technische Universität Chemnitz, 09107 Chemnitz, Germany)

  • Andreas Fischer

    (Institut für Physik, Technische Universität Chemnitz, 09107 Chemnitz, Germany)

  • Karl Heinz Hoffmann

    (Institut für Physik, Technische Universität Chemnitz, 09107 Chemnitz, Germany)

Abstract

The recuperation of otherwise lost waste heat provides a formidable way to decrease the primary energy consumption of many technical systems. A possible route to achieve that goal is through the use of Stirling engines, which have shown to be reliable and efficient devices. One can increase their performance by optimizing the piston motion. Here, it is investigated to which extent the cycle averaged power output can be increased by using a special class of adjustable sinusoidal motions (the AS class). In particular the influence of the regeneration effectiveness on the piston motion is examined. It turns out that with the optimized piston motion one can achieve performance gains for the power output of up to 50% depending on the loss mechanisms involved. A remarkable result is that the power output does not depend strongly on the limitations of the regenerator, in fact—depending on the loss terms—the influence of the regenerator practically vanishes.

Suggested Citation

  • Mathias Scheunert & Robin Masser & Abdellah Khodja & Raphael Paul & Karsten Schwalbe & Andreas Fischer & Karl Heinz Hoffmann, 2020. "Power-Optimized Sinusoidal Piston Motion and Its Performance Gain for an Alpha-Type Stirling Engine with Limited Regeneration," Energies, MDPI, vol. 13(17), pages 1-19, September.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:17:p:4564-:d:408264
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    References listed on IDEAS

    as
    1. 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.
    2. Hooshang, M. & Askari Moghadam, R. & Alizadeh Nia, S. & Masouleh, M. Tale, 2015. "Optimization of Stirling engine design parameters using neural networks," Renewable Energy, Elsevier, vol. 74(C), pages 855-866.
    3. Timoumi, Youssef & Tlili, Iskander & Ben Nasrallah, Sassi, 2008. "Performance optimization of Stirling engines," Renewable Energy, Elsevier, vol. 33(9), pages 2134-2144.
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    Cited by:

    1. Xu, Haoran & Chen, Lingen & Ge, Yanlin & Feng, Huijun, 2022. "Multi-objective optimization of Stirling heat engine with various heat and mechanical losses," Energy, Elsevier, vol. 256(C).
    2. Abdellah Khodja & Raphael Paul & Andreas Fischer & Karl Heinz Hoffmann, 2021. "Optimized Cooling Power of a Vuilleumier Refrigerator with Limited Regeneration," Energies, MDPI, vol. 14(24), pages 1-21, December.
    3. Shuangshuang Shi & Yanlin Ge & Lingen Chen & Huijun Feng, 2021. "Performance Optimizations with Single-, Bi-, Tri-, and Quadru-Objective for Irreversible Atkinson Cycle with Nonlinear Variation of Working Fluid’s Specific Heat," Energies, MDPI, vol. 14(14), pages 1-23, July.
    4. Chen, Lingen & Xia, Shaojun, 2023. "Maximum work configuration for irreversible finite-heat-capacity source engines by applying averaged-optimal-control theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 617(C).
    5. Pengchao Zang & Lingen Chen & Yanlin Ge, 2022. "Maximizing Efficient Power for an Irreversible Porous Medium Cycle with Nonlinear Variation of Working Fluid’s Specific Heat," Energies, MDPI, vol. 15(19), pages 1-12, September.
    6. Yajuan Wang & Jun’an Zhang & Zhiwei Lu & Jiayu Liu & Bo Liu & Hao Dong, 2022. "Analytical Solution of Heat Transfer Performance of Grid Regenerator in Inverse Stirling Cycle," Energies, MDPI, vol. 15(19), pages 1-25, September.
    7. Raphael Paul & Karl Heinz Hoffmann, 2021. "A Class of Reduced-Order Regenerator Models," Energies, MDPI, vol. 14(21), pages 1-25, November.

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