Abstract
The finite time thermodynamics is used to perform the thermodynamic analysis of the Stirling heat engine in this paper, and the multi-objective optimization of the heat engine cycle is carried out by Non-dominated Sorting Genetic Algorithm II (NSGA-II). In addition to various heat transfer losses (thermal resistance, regeneration loss and heat leakage), there are also mechanical losses in the cycle. The temperature ratio (x) and volume compression ratio (λ) are taken as the optimization variables, the multi-objective optimization is carried out for four objectives of cycle dimensionless shaft power, braking thermal efficiency, dimensionless efficient power and dimensionless ecological function, and effects of the two variables on the characteristics of the four optimization objectives are analyzed. Three decision-making methods, Linear Programming Techniques for Multidimensional Analysis of Preference (LINMAP), Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) and Shannon Entropy, are used to compare and analyze the optimization results of different combinations of optimization objective. The results show that the deviation indexes of quadru-objective optimization are smaller than those of single-objective optimization results, and it means that comparing with the single-objective optimization, multi-objective optimization can make better balance the four objective functions.
Published Version
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