With the popularity of electric multi-rotor unmanned aerial vehicles (EMRUAV), the problem of low efficiency of the motor propeller system (MPS) becomes serious especially for EMRUAVs which have multiple working states. To solve this problem, an integrated optimization design method for high-efficiency MPS is proposed using an improved parallel particle swarm optimization and differential evolution (PSODE) hybrid algorithm. First, the brushless motor as well as the variable-speed and the adjustable-pitch propellers is modelled. Then considering the characteristics of the motor and the propeller sufficiently, an integrated optimization method for variable-speed and adjustable-pitch MPS is proposed by utilizing the improved PSODE. Specially, the self-organizing feature map theory is added to substitute the traditional “winner-take-all” method in the interactive study of the improved PSODE. Next, the optimization of a small electric-powered tilt quad rotor (TQR) which has four states: hovering, cruising, transition and maximum speed is carried out. At last, the wind-tunnel experiments are implemented to verify the feasibility and effectiveness of the proposed optimization method. The results indicate that the adjustable-pitch MPS is more suitable for EMRUAVs which have multiple working states, and that the improved PSODE has faster convergence speed and better global search ability than other optimization methods.

中文翻译：

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多状态无人机高效电机螺旋桨系统集成优化设计方法研究

随着电动多旋翼无人机（EMRUAV）的普及，电机螺旋桨系统（MPS）效率低的问题变得严重，特别是对于具有多种工作状态的EMRUAV。针对这一问题，提出了一种采用改进的并行粒子群优化与差分进化（PSODE）混合算法的高效MPS集成优化设计方法。首先，对无刷电机以及变速和可调螺距螺旋桨进行建模。然后充分考虑电机和螺旋桨的特性，利用改进的PSODE提出了变速可调螺距MPS的综合优化方法。特别，在改进PSODE的交互研究中，加入了自组织特征映射理论来替代传统的“赢家通吃”方法。接下来，对具有悬停、巡航、过渡和最大速度四种状态的小型电动倾斜四旋翼（TQR）进行优化。最后通过风洞实验验证了所提优化方法的可行性和有效性。结果表明，可调螺距 MPS 更适用于具有多种工作状态的 EMRUAV，并且改进的 PSODE 比其他优化方法具有更快的收敛速度和更好的全局搜索能力。进行过渡和最大速度。最后通过风洞实验验证了所提优化方法的可行性和有效性。结果表明，可调螺距 MPS 更适用于具有多种工作状态的 EMRUAV，并且改进的 PSODE 比其他优化方法具有更快的收敛速度和更好的全局搜索能力。进行过渡和最大速度。最后通过风洞实验验证了所提优化方法的可行性和有效性。结果表明，可调螺距 MPS 更适用于具有多种工作状态的 EMRUAV，并且改进的 PSODE 比其他优化方法具有更快的收敛速度和更好的全局搜索能力。