摘要
对某型涡扇发动机的最大非加力寻优模式进行分析,在满足该发动机各部件的物理约束条件下,采用遗传算法对其进行性能寻优,提高其最大剩余推力值。寻优过程由基于GA lib类库的遗传算法和该涡扇发动机非线性数学模型结合编程实现。在此基础上,对遗传算法的主要运行参数进行分析和优化。在地面状态下进行仿真,其剩余推力值与设计点相比提高了4.84%。研究结果表明:遗传算法作为一种有效的全局并行优化搜索工具,适合于像涡扇发动机最大非加力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问题;通过对遗传算法运行参数的优化,能有效的提高寻优速度并减小计算量,提高运算效率。
Non-augmented maximum thrust modes and the physical constraints of the certain turbofan engine are analyzed, and Genetic Algorithm （GA） is applied to improve the engine performance in terms of the performance seeking control （PSC） mode above. The optimization process was realized on the combination of turbofan engine nonlinear component level model and GAlib, a C＋＋library developed by MIT. The net thrust at ground design point is greatly improved by the performance optimization： compared to the non-optimized model, the net thrust increased 4.84%. Furthermore, the parameters of GA are optimized. The results indicate the optimization could accelerate converge speed and save computing cost.
出处
《航空计算技术》
2006年第6期54-58,共5页
Aeronautical Computing Technique
关键词
涡扇发动机
最大推力模式
性能优化
遗传算法
GALIB
GA参数优化
turbofan engine
maximum thrust mode
performance optimization
genetic algorithms
GAlib
GA parameter optimization
