摘要
以某落地扇风叶为研究对象,建立风叶参数化模型,搭建多学科优化设计平台,以风扇风量和扭矩分别为目标开展单目标优化,优化设计变量为翼型安装角、翼型弦长、叶片弯度和叶片积叠线弯度及掠度。采用粒子群优化算法进行寻优,分别得到了不同指标下最优的扇叶配置,并确定了扇叶关键设计参数对扇叶气动性能的设计权重以及影响规律。对风量和扭矩影响最大的都是翼型安装角和弦长,随着翼型安装角和弦长的增大,风量增大,扭矩也增大。
Based on a fan blade,a parameterized model of the blade was established and a multi-disciplinary optimization design platform was built.Single-objective optimization was carried out with the air volume and torque of the fan as the goals.The optimized design variables are the airfoil installation angle,airfoil chord length,blade camber and blade stacking line camber and sweep.The particle swarm optimization algorithm is used to optimize,and the optimal fan blade configuration under different indicators is obtained.The design weight and influence law of the key design parameters of the fan blade are determined.The airfoil installation angle and chord length have the greatest influence on air volume and torque.As the airfoil installation angle and chord length increase,the air volume increases and the torque also increases.
作者
雷国茂
陈飞帆
许志华
李田
LEI Guo-mao;CHEN Fei-fan;XU Zhi-hua;LI Tian(GD Midea Consumer Electric MFG.Co.,Ltd.,Guangdong Foshan 528000,China;State Key Laboratory of Traction Power,Southwest Jiaotong University,Sichuan Chengdu 610031,China)
出处
《机械设计与制造》
北大核心
2024年第2期250-254,共5页
Machinery Design & Manufacture
基金
高速列车仿生表面微结构气动优化设计及机理研究(51605397)。
关键词
风叶
参数化模型
粒子群优化算法
设计权重
Blade
Parameterized Model
Particle Swarm Optimization Algorithm
Design Weight
