基于多目标遗传算法的航空发动机总体性能优化设计

李立君; 尹泽勇; 乔渭阳

基于多目标遗传算法的航空发动机总体性能优化设计

1.
西北工业大学动力与能源学院, 陕西西安 710072
2.
中国航空动力机械研究所, 湖南株洲 412002

基金项目: 国家APTD计划项目

计量
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- 被引次数: 0
出版历程
- 收稿日期: 2005-03-27
- 修回日期: 2005-10-03
- 刊出日期: 2006-02-28

Performance Optimal Design of Aircraft Engine Based on Multi-Objective Genetic Algorithms

1.
School of Power and Engergy, Northwestern Polytechnical University, Xi'an 710072, China
2.
China Aviation Powerplant Research Institute, Zhuzhou 412002, China

摘要

摘要: 采用一种基于Pareto最优解的多目标遗传算法—NSGAⅡ算法,以双轴混合排气式涡轮风扇发动机为算例,集成发动机性能模型、流路尺寸模型和质量模型,以单位推力、耗油率等为目标函数进行了多目标优化设计。计算结果表明:NSGAⅡ算法具有较好的稳健性和鲁棒性;基于NSGAⅡ算法的发动机总体性能优化方法能够获得目标空间内分布均匀的Pareto最优解集,有效克服了发动机总体性能方案设计时人工经验依赖较重的缺点,可为决策者进行目标权衡提供充分依据。
- 航空、航天推进系统 /
- 航空发动机 /
- 多目标优化 /
- 遗传算法 /
- 总体性能设计
Abstract: Multi-objective optimization concepts,linked with a Pareto genetic algorithm-Non-dominated Sorting Genetic Algorithm(NSGA Ⅱ),are applied to the preliminary design phase to automate the conceptual design process.Engine cycle selected for study was a mixed-stream,low-bypass turbofan.The robust analysis codes for the thermodynamic engine cycle,flowpath and weight estimation analyses were integrated to find higher quality design.The results showed that NSGA Ⅱ has better robustness and convergence than general multi-objective optimization methods,and could generate uniformly a Pareto optimal set in the design space.From this set,decision maker can choose the best overall optimum aircraft engine preliminary design.
- aerospace propulsion system /
- aircraft engine /
- multi-objective optimal design /
- genetic algorithm /
- conceptual design process

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参考文献(8)

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