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自适应粒子群优化的高压共轨燃油喷嘴多学科优化设计 被引量:12

Multidisciplinary Design Optimization for Fuel Nozzle of High Pressure Common-Rail Injection System Based on Self-Adaptive Particle Swarm Optimization Algorithm
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摘要 为了确保高压共轨燃油喷嘴整体性能提高,以高压共轨燃油喷嘴雾化性能、压力损失为目标函数建立了多学科设计优化模型,并充分考虑各学科之间的耦合效应,采用自适应粒子群优化算法进行了多学科设计优化。结果表明:雾化性能提高了36.77%,压力损失下降了11.27%,整体性能提高了16.60%。 In order to improve the whole performance of fuel nozzle of high pressure common-rail injec tion system, a multidisciplinary design optimization(MDO) model was set up based on objective functions such as atomization performance and pressure loss performance of fuel nozzle. Taking coupled effects among every subject into account, the MDO of fuel nozzle was conducted by using self-adaptive particle swarm optimization algorithm. The result indicates that the atomization performance of fuel nozzle improves by 36.77%, the pressure loss performance reduces by 11.27 %, the whole performance improves by 16.60 %.
出处 《内燃机工程》 EI CAS CSCD 北大核心 2009年第5期63-67,共5页 Chinese Internal Combustion Engine Engineering
基金 国家"985工程"--高效低排放发动机先进设计制造技术创新平台资助
关键词 内燃机 高压共轨 喷嘴 自适应粒子群 多学科优化设计 IC engine high pressure common-rail nozzle self-adaptive particle swarm multidisciplinary design optimization(MDO)
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参考文献12

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二级参考文献14

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