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首页> 外文期刊>Industrial Electronics, IEEE Transactions on >Particle Swarm Design Optimization of Transverse Flux Linear Motor for Weight Reduction and Improvement of Thrust Force
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Particle Swarm Design Optimization of Transverse Flux Linear Motor for Weight Reduction and Improvement of Thrust Force

机译：横向磁通直线电机的粒子群优化设计以减轻重量和提高推力

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摘要

Particle swarm optimization (PSO) is a computational intelligence-based technique that is not largely affected by the size and nonlinearity of the problem and can converge to the optimal solution in many problems where most analytical methods fail to converge. The PSO algorithm is applied to the design optimization problem of a permanent-magnet type transverse flux linear motor (TFLM). The objective of the optimization is to reduce the motor weight while maximizing the thrust force as well as minimizing the detent force of the motor. The stator pole length, the air gap length, the winding window width, and the stator pole width define the search space for the optimization problem. Response surface methodology (RSM) is well adapted to obtain an analytical model of the motor weight, detent force, and thrust force. The RSM enables objective functions to be easily created and a great computational time to be saved. Finite element computations are used for numerical experiments on geometrical design variables in order to determine the coefficients of a second-order analytical model for the RSM. The finite element analysis based model is verified by experimental results. The effectiveness of the proposed PSO model is then compared with that of the conventional optimization models and genetic algorithms model. With this proposed PSO technique, the weight of the initially designed TFLM and its detent force can be reduced, as well as its thrust force can be increased.
机译：粒子群优化（PSO）是一种基于计算智能的技术，在很大程度上不受问题的大小和非线性影响，可以在大多数分析方法无法收敛的许多问题中收敛至最优解。 PSO算法被应用于永磁型横向磁通直线电动机（TFLM）的设计优化问题。优化的目的是在最大推力的同时减小电动机的重量，同时使电动机的制动力最小。定子磁极长度，气隙长度，绕组窗口宽度和定子磁极宽度确定了优化问题的搜索空间。响应表面方法（RSM）非常适合获得电动机重量，制动力和推力的分析模型。 RSM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，以便确定RSM的二阶分析模型的系数。实验结果验证了基于有限元分析的模型。然后将所提出的PSO模型的有效性与常规优化模型和遗传算法模型的有效性进行比较。使用这种提议的PSO技术，可以减轻最初设计的TFLM的重量及其制动力，并可以增加其推力。

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