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Title: Modelling and optimisation of a free piston stirling engine for micro-CHP applications
Author: Sowale, Ayodeji
ISNI:       0000 0004 6060 5343
Awarding Body: Northumbria University
Current Institution: Northumbria University
Date of Award: 2015
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This study is carried out to investigate the solar thermal energy conversion for generating power. This form of renewable energy can be utilised for power production deploying the free piston Stirling engines, which convert thermal energy into mechanical energy. Such systems have an advantage of production of work using low and high temperature differences in the cycle which could be created by different sources of heat including solar energy, combustion of a fuel, geothermal energy, nuclear energy or waste heat. The thermodynamic analysis of the free piston Stirling engine have been carried out and implemented in past studies with different methods of approach with various difficulties exhibited. In the present study isothermal, ideal adiabatic and Quasi steady flow models have been produced and used for investigation of the engine performance. The approach in this study deals with simultaneous mathematical modelling of thermodynamic processes and pistons dynamics. The steady state operation of the engine depends on the values of damping coefficients, spring stiffness and pressure drop within the heat exchangers during the engine’s operation, which is also a result of the energy transfer in each engine’s component. In order to design effective high performance engines it is necessary to develop such advanced mathematical models to perform the analysis of the engine’s operation and to predict its performance satisfactorily. The aim of this study was to develop several levels of mathematical models of free piston Stirling engines and to evaluate their accuracy using experimental and theoretical results available in published sources. The validation of the developed free piston Stirling engine models demonstrates a good agreement between the numerical results and experimental data. The validated model then was used for optimisation of the engine, deploying Genetic Algorithm approach with the purpose to determine its optimal design parameters. The developed optimisation procedure provides a noticeable improvement in the engine’s performance in terms of power output and efficiency.
Supervisor: Mahkamov, Khamid Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: H300 Mechanical Engineering