Abstract:
The aim of this work is to optimize the design
and performance of solar powered γ Stirling engine based
on genetic algorithm (GA). A second-order mathematical
model which includes thermal losses coupled with genetic
algorithm GA has been developed and used to find the best
values for different design variables. The physical
geometry of the γ Stirling engine has been used as an
objective variable in the genetic algorithm GA to
determine the optimal parameters. The design geometry of
the heat exchanger was considered to be the objective
variable. The heater slots height, heater effective length,
cooler slots height, cooler effective length, re-generator foil
unrolled length and re-generator effective length are
assumed to be the objective variables. Also, three different
types of working fluids have been used in the model
simulation to investigate the effect of the different working
fluid on the engine performance. The comparison between
the results obtained from the simulation by using the
original parameters and the results from the optimized
parameters when the engine was powered by solar energy;
the higher temperature was 923 K applied to the working
fluid when the air, helium, and hydrogen were used as
working fluid. The engine power increases from 140.58
watts to 228.54 watts, and it is enhanced by approximately
50%, when the heating temperature is 923 K and the air is
used as working fluid. The result showed that the working
temperature is one of the most important parameters;
because the output power increases by increasing of the hot side temperature.
Description:
International Journal of Advanced Engineering and Management
Vol. 3, No. 4, pp. 109-1 19, 2018
