Hydrogen Utilization in Free Piston Engines: A Performance Investigation

Document Type : Research Paper

Authors

Department of Mechanical Engineering, Iranian Research Organization for Science and Technology (IROST)

Abstract

This paper presents a dynamic analysis of a free-piston engine (FPE) using hydrogen gas as the working fluid for the first time. Initially, the governing dynamic equations of the FPE are derived. The performance of the B10-B engine is then evaluated based on the location of the closed-loop poles using five different working fluids: air, argon, nitrogen, helium, and hydrogen. The results indicate that hydrogen gas significantly enhances the engine’s operating frequency, output power, and startup conditions compared to other gases. Additionally, this study examines the impact of varying key parameters of the FPE, such as power and displacer mass, the cross-sectional area of the pistons and the rod connected to the displacer piston, and the displacer piston stiffness on the engine’s dynamics using the phase plane method. The findings reveal that the most optimal engine dynamics occur when hydrogen gas is used as the working fluid. Ultimately, the use of hydrogen as the working fluid leads to improved dynamic instability and increased output power, making it the optimal choice for FPEs, provided safety conditions are met to prevent combustion in the chamber.

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Main Subjects


[1] Shourangiz-Haghighi A, Haghnegahdar MA, Wang L, Mussetta M, Kolios A, Lander M. State of the art in the optimisation of wind turbine performance using CFD. Archives of Computational Methods in Engineering. 2020;27:413–431.
[2] Shourangiz-Haghighi A, Diazd M, Zhang Y, Li J, Yuan Y, Faraji R, et al. Developing more efficient wind turbines: A survey of control challenges and opportunities. IEEE Industrial Electronics Magazine. 2020;14(4):53–64.
[3] Abdali S, Yaghoubi S. Multi-objective optimization of a combined heat and power (CHP) cycle with a solar collector: energy, exergy and economic point of view. Hydrogen, Fuel Cell & Energy Storage. 2024;11(2):95–106.
[4] Kadhim Almohammed AQ, Delshad M, Bachache NK, Fani B, Saghafi H. A new SEPIC-Zeta bidirectional converter with high efficiency for renewable energy systems. Hydrogen, Fuel Cell & Energy Storage. 2024;11(3):142–152.
[5] Xu Y, Li J, Tan Q, Peters AL, Yang C. Global status of recycling waste solar panels: A review. Waste management. 2018;75:450–458.
[6] Perozziello C, Grosu L, Vaglieco BM. Free-piston stirling engine technologies and models: A review. Energies. 2021;14(21):7009.
[7] Zare S, Tavakolpour-Saleh A. Free piston Stirling engines: A review. International Journal of Energy Research. 2020;44(7):5039–5070.
[8] Walker G, Senft JR, Walker G, Senft J. Freepiston Stirling engines. Springer; 1985.
[9] Zare S, Tavakolpour-Saleh A, Hosseininia A, Sangdani MH. Investigating the onset and steady-state conditions of a diaphragm thermoacoustic stirling engine. Proceedings of the Institution of Mechanical Engineers, Part A: Journal of Power and Energy. 2024;238(4):731–760.
[10] Zare S, Tavakolpour-Saleh A. Frequency-based design of a free piston Stirling engine using genetic algorithm. Energy. 2016;109:466–480.
[11] Dashti E, Tabari NG, Zare S, Shabanpour H. An Analytical Investigation of a Thermoacoustic stirling Engine. Arabian Journal for Science and Engineering. 2024;p. 1–18.
[12] Zare S, Tavakolpour-Saleh A, Binazadeh T. Analytical investigation of free piston Stirling engines using practical stability method. Chaos, Solitons & Fractals. 2023;167:113082.
[13] Karabulut H. Dynamic analysis of a free piston Stirling engine working with closed and open thermodynamic cycles. Renewable Energy. 2011;36(6):1704–1709.
[14] Zare S, Tavakolpour-Saleh A, Sangdani M. Investigating limit cycle in a free piston Stirling engine using describing function technique and genetic algorithm. Energy Conversion and Management.2020;210:112706.
[15] Formosa F. Coupled thermodynamic–dynamic semi-analytical model of free piston Stirling engines. Energy Conversion and Management. 2011;52(5):2098–2109.
[16] Tavakolpour-Saleh A, Zare S. An averaging-based Lyapunov technique to design thermal oscillators:
A case study on free piston Stirling engine. Energy. 2019;189:116127.
[17] Mou J, Hong G. Startup mechanism and power distribution of free piston Stirling engine. Energy. 2017;123:655–663.
[18] Ghanbarzadeh S, Mironov SN, Chen TC, Alkaim AF, Surendar A, Thangavelu L. Determination of cell voltage and current efficiency in a chloralkali membrane cell based on machine learning approach. Petroleum Science and Technology. 2024;42(15):1898–1910.
[19] Tangestani E, Ghanbarzadeh S, Garcia JF. Prediction of Catalytic Hydrogen Generation by Water–Gas Shift Reaction Using a Neural Network Approach. Catalysis Letters. 2023;153(3):863–875.
[20] Parsai S, Ahmadi M. A Novel Hierarchical Face Recognition Method Based on the Geometrical Face Features and Convolutional Neural Network with a New Layer Arrangement. In: Information Systems for Intelligent Systems: Proceedings of ISBM 2022. Springer; 2023. p. 151–162.
[21] Parsai S, Ahmadi M. A Low Error Face Recognition System Based on A New Arrangement of Convolutional Neural Network and Data Augmentation. In: TENCON 2022-2022 IEEE Region 10 Conference (TENCON). IEEE; 2022. p. 1–5.
[22] Parsai S, Ahmadi M. New Local Binary Pattern Feature Extractor with Adaptive Threshold for Face Recognition Applications. International Jounal of Artificial Intelligence & Applications. 2022;13.
[23] Zare S, Tavakolpour-Saleh A, Aghahosseini A, Sangdani M, Mirshekari R. Design and optimization of Stirling engines using soft computing methods: a review. Applied Energy. 2021;283:116258.
[24] Zare S, Pourfayaz F, Tavakolpour-Saleh A, Lashaki RA. A design method based on neural network to predict thermoacoustic Stirling engine parameters: Experimental and theoretical assessment. Energy. 2024;309:133113.
[25] Ye W, Wang X, Liu Y. Application of artificial neural network for predicting the dynamic performance of a free piston Stirling engine. Energy. 2020;194:116912.
[26] Zare S, Tavakolpour-Saleh A. Applying particle swarm optimization to study the effect of dominant poles places on performance of a free piston Stirling engine. Arabian Journal for Science and Engineering. 2019;44:5657–5669.