Exergy Analysis and Optimization of an Alpha Type Stirling Engine Using the Implicit Filtering Algorithm

Abstract

This paper presents the exergy analysis and optimization of the Stirling engine, which has enormous potential for use in the renewable energy industry as it is quiet, efficient, and can operate with a variety of different heat sources and, therefore, has multi-fuel capabilities. This work aims to present a method that can be used by a Stirling engine designer to quickly and efficiently find near-optimal or optimal Stirling engine geometry and operating conditions. The model applies the exergy analysis methodology to the ideal-adiabatic Stirling engine model. In the past, this analysis technique has only been applied to highly idealized Stirling cycle models and this study shows its use in the realm of Stirling cycle optimization when applied to a more complex model. The implicit filtering optimization algorithm is used to optimize the engine as it quickly and efficiently computes the optimal geometry and operating frequency that gives maximum net-work output at a fixed energy input. A numerical example of a 1,000 cm 3 engine is presented, where the geometry and operating frequency of the engine are optimized for four different regenerator mesh types, varying heater inlet temperature and a fixed energy input of 15 kW. The WN200 mesh is seen to perform best of the four mesh types analyzed, giving the greatest network output and efficiency. The optimal values of several different engine parameters are presented in the work. It is shown that the net-work output and efficiency increase with increasing heater inlet temperature. The optimal dead-volume ratio, swept volume ratio, operating frequency, and phase angle are all shown to decrease with increasing heater inlet temperature. In terms of the heat exchanger geometry, the heater and cooler tubes are seen to decrease in size and the cooler and heater effectiveness is seen to decrease with increasing heater temperature, whereas the regenerator is seen to increase in size and effectiveness. In terms of the regenerator mesh type, it was found that the WN200 mesh gave a shorter regenerator with greater cross-sectional flow area which gave a smaller pressure drop.

The effects of different channel geometries in the displacer cylinder, working fluids, and engine speed on the energy and exergy performance characteristics of a β-type Stirling engine with a slider-crank drive mechanism

“…The entropy balance for the engine used in the research is given in equation (9). 29 Here, the entropy generated is S gen , the entropy entering the system is S in , and the entropy leaving the system is S out .…”

“…As is seen, the highest exergy loss occurred in the receiver, followed by the condenser and Stirling engine, respectively. Wills and Bello-Ochende 29 carried out numerical analyses for four regenerator network structures and different heater temperatures in an alpha-type Stirling engine with a constant energy input of 15 kW and a cylinder volume of 1000 cm 3 . Accordingly, they determined that the phase angle, operating frequency, optimum dead volume ratio, and swept volume ratio parameters decreased depending on the increased heater temperature.…”

An Endoreversible Model for the Regenerators of Vuilleumier Refrigerators

“…Conventional modeling approaches for regenerators may be roughly divided into two categories. The first category encompasses models that describe the regenerator in an integral manner, using a characteristic quantity referred to as regenerator effectiveness [3][4][5][6][7][8][9]. The regenerator effectiveness may be modeled based on analytic solutions of an idealized regenerator or empirical correlations.…”

A Class of Reduced-Order Regenerator Models

“…This characteristic quantity, in turn, was used to define the outflow temperatures of the working gas on both sides of the regenerator. Since such models result in very low computational effort, they have been used continuously and developed further, especially in applications where low computational effort is a key requirement [11][12][13][14].…”