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Beta Type Stirling Engine. Schmidt and Finite Physical Dimensions Thermodynamics Methods Faced to Experiments.
Cătălina Dobre1, Lavinia Grosu2, Monica Costea1
1Department of Engineering Thermodynamics, Engines, Thermal and Refrigeration Equipments, University Politehnica of Bucharest, Splaiul Independenței 313, 060042 Bucharest, Romania.
This study models Stirling engine performance using two thermodynamic approaches, Finite Physical Dimension Thermodynamics (FPDT) and the imperfectly regenerated Schmidt model. Both models effectively predict engine behavior and energy losses, validated by experimental data.
Area of Science:
- Thermodynamics
- Mechanical Engineering
- Energy Systems
Background:
- Stirling engines offer a promising alternative for energy conversion.
- Accurate thermodynamic modeling is crucial for optimizing Stirling engine design and performance.
- Existing models often require complex calculations or lack practical engineering parameters.
Purpose of the Study:
- To develop and validate two simplified analytical models for a beta-type Stirling engine cycle.
- To assess the ability of these models to predict engine behavior and energy losses.
- To express energy exchanges using practical engineering parameters for design applications.
Main Methods:
- Application of the Finite Physical Dimension Thermodynamics (FPDT) method.
- Development of a 0D model using the imperfectly regenerated Schmidt model.
- Experimental testing of a beta-type Stirling engine for validation.
- Kinematic-thermodynamic coupling for evaluating energy processes based on crankshaft angle.
Main Results:
- Both models successfully indicate Stirling engine behavior, accounting for heat exchanger irreversibility and imperfect regeneration.
- Energy loss contributions were determined and compared between the two models and experimental results.
- Theoretical predictions showed good agreement with experimental data, particularly regarding the effect of engine speed on power and efficiency.
Conclusions:
- Simplified thermodynamic models can effectively predict Stirling engine performance.
- The study highlights the importance of considering irreversibility and regeneration in Stirling engine analysis.
- Practical engineering parameters are crucial for translating theoretical models into real-world applications.
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