某涡扇发动机最小油耗模式性能优化算法研究  

Performance Optimization of Turbofan Engine Minimizing Fuel Consumption Mode

作　　者：刘旭东[1] 邓小宝[1] 高扬[1] 

机构地区：[1]中国飞行试验研究院,陕西西安710089

出　　处：《计算机仿真》2009年第12期74-77,共4页Computer Simulation

摘　　要：针对发动机安全性、减少油耗、降低热应力问题,研究某型涡扇发动机非线性数学模型,在满足发动机各部件物理约束条件和推力相等的条件下,采用遗传算法就巡航状态下耗油率最低,对性能指标进行寻优,寻优过程用GAlib类库的遗传算法和涡扇发动机非线性数学模型结合编程实现。在地面及空中巡航状态下分别进行仿真,在推力相等的条件下,地面巡航状态的耗油率在优化后比优化前降低了13.8%,空中巡航状态的耗油率在优化后比优化前降低了9.45%。研究表明:遗传算法适用于像涡扇发动机巡航状态性能寻优这样大规模、高度非线性及无解析表达式的性能优化。Minimizing fuel consumption mode and the physical constraints of a certain turbofan engine were analyzed, and Genetic Algorithm （GA） was applied to improve the engine performance in terms of the performance seeking control （PSC） mode above. The optimization process was realized by the combination of turbofan engine nonlin- ear component level model and GAlib, a C ＋ ＋ library developed by MIT. Specific fuel consumption on ground and in - flight were greatly improved by the performance optimization ： compared to the non - optimized model, specific fuel consumption decreased 13.8% on ground and 9.45% in - flight. The study shows that GA, as an effective global parallel optimization search tool, can be effectively applied to the performance optimization of turbofan engine cruise mode that is large scale, highly nonlinear and without explicitl expression.

关 键 词：涡扇发动机 性能优化 遗传算法 遗传算法类库 最低油耗寻优模式 

分 类 号：V231.3[航空宇航科学与技术—航空宇航推进理论与工程]