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首页> 外文期刊>Electric Power Components and Systems >Bacterial Foraging Based Optimal Design of Transverse Flux Linear Motor for Thrust Force Improvement
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Bacterial Foraging Based Optimal Design of Transverse Flux Linear Motor for Thrust Force Improvement

机译:基于细菌觅食的横向磁通直线电动机优化推力设计

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This article presents a novel optimal design for a permanent magnet excitation transverse flux linear motor with an inner mover using bacterial foraging optimization. The target is maximizing the motor thrust force, which is the most important quantity in linear electric drives. The stator pole length, air-gap length, winding window width, and stator pole width define the search space for the optimization problem. The response surface methodology is used to build the mathematical model of the motor thrust force in terms of the design variables. It can create an objective function easily, and great computational time is saved. Finite-element computations are used for numerical experiments on the geometrical design variables to determine the coefficients of a second-order analytical model for the response surface methodology. The bacterial foraging optimization technique is used as a searching tool under the constraints of design variables for design optimization of the transverse flux linear motor to improve the motor thrust force. The effectiveness of the proposed bacterial foraging optimization model is then compared with that of both genetic algorithm and particle swarm optimization models. With this proposed bacterial foraging optimization technique, the thrust force of the initially designed transverse flux linear motor can be increased.
机译:本文提出了一种新型的优化设计,该优化设计用于带有内动子的永磁励磁横向磁通直线电动机,并利用细菌觅食进行了优化。目标是使电动机推力最大化,这是线性电动驱动器中最重要的量。定子磁极长度,气隙长度,绕组窗口宽度和定子磁极宽度定义了优化问题的搜索空间。响应面方法用于根据设计变量建立电动机推力的数学模型。它可以轻松创建目标函数,并节省大量计算时间。有限元计算用于几何设计变量的数值实验,以确定响应面方法的二阶分析模型的系数。在设计变量的约束下,将细菌觅食优化技术用作搜索工具,以优化横向磁通线性电动机的设计,以提高电动机推力。然后将所提出的细菌觅食优化模型的有效性与遗传算法和粒子群优化模型的有效性进行比较。利用这种建议的细菌觅食优化技术,可以提高最初设计的横向通量线性电动机的推力。

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