利用遗传算法对电机进行优化设计:确定电机参数的数学装置

F. Ismagilov, V. Vavilov, V. Ayguzina, N. L'vov, Timofey A. L'vovskiy
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引用次数: 0

摘要

本文提出了一种计算电机气隙中磁通密度的数学装置,该装置具有足够的精度,可用于基于遗传算法的电机优化设计方法。数学模型是在柱坐标下建立的。这项工作的新颖和贡献在于解决了在解析形式和柱坐标下分析磁场的问题,而不使用有限元方法和专门的软件包。该方法采用遗传算法,减少了仿真人工成本和工程设计过程的估计时间。实验证明了所建立的数学模型的正确性和较高的精度。分析数据与实验数据的差异小于5%。所开发的数学装置可用于利用遗传算法设计新视角电机。
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Optimal design of electric machines by using genetic algorithms: mathematical apparatus to determine machine parameters
This paper presents a mathematical apparatus that allows calculating the magnetic flux density in the air gap of electrical machines with sufficient accuracy for use in the method of optimal design of electric machines based on genetic algorithms. The mathematical model has been developed in cylindrical coordinates. The novelty and contribution of this work is the solution of the problem of analyzing the magnetic field in an analytical form and in cylindrical coordinates without the use of finite element methods and specialized software packages. The approach described reduces the labor costs in the simulation and estimated time for the engineering design process by using genetic algorithms. The correctness and high accuracy of the developed mathematical model has been confirmed experimentally. The discrepancy between analytical and experimental data is below 5%. The developed mathematical apparatus can be used for the design of new perspective electrical machines by using genetic algorithms.
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