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基于不确定性的旋翼转速优化直升机参数设计 被引量:5

Parameter design of helicopter with optimum speed rotor based on uncertainty optimization
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摘要 为了提高旋翼转速优化直升机总体参数设计质量,基于不确定性多学科设计优化方法,对旋翼转速优化直升机的参数设计进行了研究。首先对最优旋翼转速的不确定性进行分析与建模,同时也考虑了直升机加工制造、材料老化引起的不确定性因素,对比发现最优旋翼转速是旋翼转速优化直升机设计中的主要不确定性因素;然后在协同优化框架下,分别建立了直升机飞行性能、直升机重量、飞行稳定性与变转速涡轴发动机性能计算模型;最后以续航性能为系统学科,悬停性能、飞行稳定性分别作为子学科,进行多学科的不确定性优化设计,得到了3种不确定性优化设计方案。通过对比分析可以发现:第2种方案为旋翼转速优化直升机的最佳参数设计方案,该方案满足悬停需用功率低于350kW,飞行稳定性指数小于0.8等约束条件的概率不低于95.46%,并且直升机的最大航时期望值也较大。 In order to improve the quality of design schemes of helicopter with optimum speed rotor, this paper studies thedesign method of helicopter with optimum speed rotor, based on uncertainty multidisciplinary design optimization. First ofall, the uncertainty factors of helicopter parameters are analyzed and modeled from optimal rotor speed, processing errorand material deterioration, and it shows that the optimal rotor speed is the main uncertainty factor in the design of helicopterwith optimum speed rotor. And then under the collaborative optimization framework, the models of helicopter flight perform-ance, helicopter weight, flight stability, and the performance of turboshaft engine with variable rotor speed are established.Finally, the design of helicopter with optimum speed rotor based on uncertainty multidisciplinary optimization is investigated,which is based on two subsystem design tasks, i.e., hovering performance and flight stability, and one system level designtask about helicopter endurance. Optimization results show that the second scheme for the helicopter with the optimum speedrotor is the best one; its probability of satisfying the constraints of required power being less than 350 kW in hover and indexof flight stability being less than 0.8, is not less than 95.46%, and expectation of endurance is also bigger.
出处 《航空学报》 EI CAS CSCD 北大核心 2016年第7期2170-2179,共10页 Acta Aeronautica et Astronautica Sinica
基金 中央高校基本科研业务费专项资金 江苏省普通高校研究生科研创新计划(CXLX13_164)~~
关键词 旋翼转速优化 直升机总体参数 不确定性 多学科优化 航时 optimum speed rotor helicopter preliminary parameters uncertainty multidisciplinary optimization endur-ance
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