The Stirling cooler is a potential substitute for the vapor compression refrigeration system in a moderate-temperature zone. An isothermal model of a Stirling cooler based on finite time thermodynamics is established. The expressions of input power, cooling capacity, and coefficient of performance (COP) are derived. The input power, cooling capacity, and COP of the Stirling cooler are optimized simultaneously using the particle swarm optimization (PSO) algorithm. The performance of the multi-objective particle swarm optimization (MOPSO) algorithm is tested by four benchmark functions. The technique for order preference by similarity to an ideal solution (TOPSIS) is used to obtain the global optimal solution. According to the global optimal solution, the Stirling cooler obtains the performance with an input power of 106.5 W, a cooling capacity of 266.7 W, and a COP of 2.5. Compared with the results obtained by the single-objective optimization of cooling capacity, the COP increases by 42.0%, and the input power decreases by 59.3%. Finally, a sensitivity analysis of heat exchangers on the cooling capacity is carried out. The result shows that the cooling capacity is more sensitive to the hot-side heat exchanger in the optimal design point.

斯特林冷却器是中温区蒸汽压缩制冷系统的潜在替代品。建立了基于有限时间热力学的斯特林冷却器等温模型。推导了输入功率、制冷量和性能系数（COP）的表达式。斯特林冷却器的输入功率、冷却能力和 COP 使用粒子群优化 (PSO) 算法同时进行优化。多目标粒子群优化（MOPSO）算法的性能通过四个基准函数进行测试。采用与理想解相似度排序的技术（TOPSIS）来获得全局最优解。根据全局最优解，斯特林冷却器在输入功率为 106.5 W 时获得性能，冷却能力为 266.7 W，COP 为 2.5。与制冷量单目标优化得到的结果相比，COP提高了42.0%，输入功率降低了59.3%。最后，进行了热交换器对冷却能力的敏感性分析。结果表明，在最优设计点，冷量对热端换热器更为敏感。