基于粒子群算法的内燃机曲轴轴承优化设计  

Optimization Design of Crankshaft Bearing of Internal Combustion Engine Based on Particle Swarm Algorithm

作　　者：孙军[1] 符永红[1] 桂长林[1] 邓玫[1] 

机构地区：[1]合肥工业大学机械与汽车工程学院,安徽合肥230009

出　　处：《内燃机》2008年第2期13-15,43,共4页Internal Combustion Engines

基　　金：国家自然科学基金资助项目(50575065)

摘　　要：基于曲轴轴承润滑分析建立的轴承性能数据库,采用插值方法,获取不同结构尺寸轴承的润滑性能,应用粒子群算法,以轴承摩擦功耗为目标,对内燃机曲轴轴承进行优化设计。通过N485柴油机曲轴轴承的实例优化表明,此方法是切实可行的。In this paper, based on the database of bearing performances established by lubrication analysis of crankshaft bearing, the lubrication performances of bearing with different parameters were gotten by interpolation. Then, crankshaft bearing was optimized to get minimum friction power loss by using particle swarm algorithm. Crankshaft bearings of N485 diesel were taken for an example of optimization. The result shows that above method is practical and rational.

关 键 词：内燃机 曲轴轴承 摩擦功耗 优化设计 粒子群算法 

分 类 号：TK402[动力工程及工程热物理—动力机械及工程]