| 摘要: |
| 收敛性是航空发动机非线性数学模型的重要指标。现有发动机平衡方程迭代解法还不能保证模型大范围收敛。以某涡扇发动机为对象,采用遗传算法求解发动机非线性数学模型,将模型中的发动机平衡方程求解转换为极小值优化问题,建立了遗传算法计算模型,重点分析了采用遗传算法求解的适应度函数设计方法。数值仿真结果表明,与牛顿-拉夫逊解法相比,采用遗传算法方法可实现模型大范围收敛。 |
| 关键词: 航空发动机 非线性 数学模型 遗传算法+ 平衡方程 收敛 |
| DOI： |
| 分类号:V235.13 |
| 基金项目:航空推进技术验证(APTD)计划项目(APTD 0901 13);西北工业大学"英才培养计划"基金资助。 |
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| Application of genetic algorithm in aeroengine nonlinear mathematical models |
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SU San-mai, LIAN Xiao-chun
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Dept.of Aeroengine Engineering, Northwestern Polytechnical Univ.,Xi’an 710072, China
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| Abstract: |
| Convergence is one of the most important issues in aeroengine nonlinear mathematical models. Current aeroengine balance equations solutions are not always effective in entire envelope. Genetic algorithm(GA) is applied on a turbofan engine performance model. Solving aeroengine balance equations is converted to a GA minimum optimization problem , and the solution method, especially the GA fitness function design,is introduced in detail. Comparison with Newton-Raphson,simulation results show that the model convergence is improved with application of GA in aeroengine nonlinear mathematical models. |
| Key words: Aircraft engine Nonlinearity Mathematical model Genetic algorithm~+ Equilibrium equation Convergence |
