改进的粒子群算法在翼型优化设计中的应用

建立了多目标风力机翼型型线优化模型，并采用改进的粒子群优化算法对多目标风力机翼型型线进行优化，设计出4种不同厚度的性能较好的风力机翼型。对CQUA18和CQUA21两种新翼型的气动特性与相同厚度典型的风力机翼型进行对比分析，结果表明，该翼型具有良好的气动特性，对翼型的前缘粗糙度不敏感，在主要攻角范围内，光滑和粗糙条件下，新翼型的升力系数和升阻比都要高，其气动特性具有显著的提高。

Airfoil design using improved particle swarm optimization

Based on the theory of standard particle swarm optimization (PSO), an improved particle swarm optimization algorithm is presented, and it has a better optimized performance than standard PSO. A multi-objective wind turbine airfoil shape optimization model is established and 4 kinds of different thick wind turbine airfoils with better performance are designed by using the improved PSO algorithm. The aerodynamic performance of the CQU-A18 and CQU-A21 airfoils are analyzed in detail compared with the commonly used wind turbine airfoil with the same thickness. The results show that the new airfoils show very good aerodynamic characteristics, and they are found to be very insensitive to leading edge roughness. The new airfoils exhibit the higher lift coefficient and larger lift/drag ratio in both smooth condition and rough condition at the main angle of attacks. The performances of the new airfoils show a significant improvement compared with the typical airfoils.