With the aim of enhancing both reliability and fatigue life of gasket, this study combines finite element analysis, orthogonal experimental design, dynamically-guided multi-objective optimization, and the non-dominated sorting genetic algorithm with elitist strategy to optimize the geometric parameters of the cylinder gasket. The finite element method was used to analyze the temperature field, thermal-mechanical coupling stress field, and deformation of cylinder gasket. The calculation results were experimentally validated by measured temperature data, and comparison results show that the maximum error between calculated value and experiment value is 7.1%, which is acceptable in engineering problems. Based on above results and orthogonal experiment design method, the effects of five factors, including diameter of combustion chamber circle, diameter of coolant flow hole, length of the insulation zone between third and fourth cylinders, thickness of gasket, and bolt preload, on three indexes: temperature, stress, and deformation of gasket, were examined in depth. Through the variance analysis of the results, three important factors were identified to proceed later calculation. The dynamically guided multi-objective optimization strategy and the non-dominated sorting genetic algorithm were effectively used and combined to determine the optimal geometric parameters of cylinder gasket. Furthermore, calculation results suggest that temperature, stress, and deformation of the optimized cylinder gasket have been improved by 27.88 K, 16.84 MPa, and 0.0542 mm, respectively when compared with the origin object, which shows the excellent performance of gasket optimization and effectiveness of the proposed optimization strategy.

本研究以提高垫片的可靠性和疲劳寿命为目标，结合有限元分析、正交实验设计、动态引导多目标优化以及精英策略的非支配排序遗传算法对垫片几何参数进行优化。气缸垫片。采用有限元方法对气缸垫的温度场、热力耦合应力场和变形进行分析。利用实测温度数据对计算结果进行了实验验证，对比结果表明，计算值与实验值最大误差为7.1%，在工程问题中是可以接受的。基于以上结果，采用正交试验设计方法，研究了燃烧室圆直径、冷却液流通孔直径、第三、第四缸间隔热区长度、垫片厚度、螺栓预紧力等五个因素对三缸发动机的影响。对垫片的温度、应力、变形等指标进行了深入研究。通过对结果进行方差分析，确定了三个重要因素进行后续计算。有效运用并结合动态引导多目标优化策略和非支配排序遗传算法确定气缸垫最优几何参数。此外，计算结果表明，与原始对象相比，优化后的气缸垫的温度、应力和变形分别提高了27.88 K、16.84 MPa和0.0542 mm，这表明垫片优化的优异性能和有效性。所提出的优化策略。