Experimental assessment of damping and heat transfer coefficients in an active free piston Stirling engine using genetic algorithm

In this work, two critical parameters of an active free piston Stirling engine (AFPSE) namely, the heat transfer and damping coefficients are practically estimated using genetic algorithm (GA). Although, the mentioned parameters play a significant role in the accuracy of data obtained from the mathematical models, they cannot be measured directly. Indeed, there are no specific sensors to measure damping and heat transfer coefficients and it is the main challenge to achieve their practical values. Consequently, this work attempts to present an innovative scheme to estimate such immeasurable parameters based on other measurable variables. First, the modeling approach of the AFPSE is described and the significance of the mentioned parameters is highlighted. Then, two experimental works are conducted to measure gas pressure and power piston displacement at each engine frequency for identifying the immeasurable parameters indirectly. Subsequently, an appropriate objective function based on the error between the experimental and simulation data is defined for each of the identification scheme. Next, the GA is used to achieve the mentioned unknown parameters so as to minimize the proposed objective functions. Finally, the experimental and simulated outcomes clearly affirm the effectiveness of the proposed identification scheme of the considered immeasurable parameters.