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Neural network-based control of an intelligent solar Stirling pump

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  • Tavakolpour-Saleh, A.R.
  • Jokar, H.

Abstract

In this paper, an ANN (artificial neural network) control system is applied to a novel solar-powered active LTD (low temperature differential) Stirling pump. First, a mathematical description of the proposed Stirling pump is presented. Then, optimum operating frequencies of the converter corresponding to different operating conditions (i.e. different sink and source temperatures and water heads) are investigated using the proposed mathematical framework. It is found that the proposed complex mathematical scheme has a very slow convergence and thus, is not appropriate for real-time implementation of the model-based controller. Consequently, a NN (neural network) model with a lower complexity is proposed to learn the simulation data obtained from the mathematical model. The designed neural network controller is thus applied to a digital processor to effectively tune the converter frequency so that a maximum output power is acquired. Finally, the performance of the proposed mechatronic system is evaluated experimentally. The experimental results clearly demonstrate the feasibility of pumping water at low temperature difference under variable operating conditions using the proposed intelligent Stirling converter.

Suggested Citation

  • Tavakolpour-Saleh, A.R. & Jokar, H., 2016. "Neural network-based control of an intelligent solar Stirling pump," Energy, Elsevier, vol. 94(C), pages 508-523.
    • Handle: RePEc:eee:energy:v:94:y:2016:i:c:p:508-523
    DOI: 10.1016/j.energy.2015.11.006
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    References listed on IDEAS

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    Cited by:

    1. Tavakolpour-Saleh, A.R. & Zare, SH. & Bahreman, H., 2017. "A novel active free piston Stirling engine: Modeling, development, and experiment," Applied Energy, Elsevier, vol. 199(C), pages 400-415.
    2. Motamedi, Mahmoud & Ahmadi, Rouhollah & Jokar, H., 2018. "A solar pressurizable liquid piston stirling engine: Part 1, mathematical modeling, simulation and validation," Energy, Elsevier, vol. 155(C), pages 796-814.
    3. Zare, Shahryar & Tavakolpour-saleh, A.R. & Aghahosseini, A. & Sangdani, M.H. & Mirshekari, Reza, 2021. "Design and optimization of Stirling engines using soft computing methods: A review," Applied Energy, Elsevier, vol. 283(C).
    4. Zare, Sh. & Tavakolpour-Saleh, A.R., 2016. "Frequency-based design of a free piston Stirling engine using genetic algorithm," Energy, Elsevier, vol. 109(C), pages 466-480.
    5. Tavakolpour-Saleh, A.R. & Zare, Sh. & Omidvar, A., 2016. "Applying perturbation technique to analysis of a free piston Stirling engine possessing nonlinear springs," Applied Energy, Elsevier, vol. 183(C), pages 526-541.
    6. Ahmadi, Rouhollah & Jokar, H. & Motamedi, Mahmoud, 2018. "A solar pressurizable liquid piston stirling engine: Part 2, optimization and development," Energy, Elsevier, vol. 164(C), pages 1200-1215.
    7. Mojtaba Alborzi & Faramarz Sarhaddi & Fatemeh Sobhnamayan, 2019. "Optimization of the thermal lag Stirling engine performance," Energy & Environment, , vol. 30(1), pages 156-175, February.
    8. Jigui Zheng & Jing Chen & Ping Zheng & Hongxing Wu & Chengde Tong, 2017. "Research on Control Strategy of Free-Piston Stirling Power Generating System," Energies, MDPI, vol. 10(10), pages 1-17, October.

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