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Genetic algorithm in torque optimisation of permanently split capacitor motor

机译:永久分离电容器电动机扭矩优化的遗传算法

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Paper investigates permanently split capacitor motor of type FMR-35/6, with respect to torque optimization. For this purpose, mathematical model of the motor is derived with the output torque as an objective function for optimization. Motor mathematical model is applied in program developed in the C++ language, which performs the optimization using Genetic Algorithm (GA). Several input design parameters of the motor are varied simultaneously in the GA program. The program gives the best set of varied parameters for which the torque is increased, and consequently a new optimized model of the motor is obtained. Output torque of the optimized motor is increased at rated operating point as well as during motor start. Matlab/Simulink models are designed for obtaining the transient characteristics of the currents, speed and torque. The results from the Simulink models are compared with the results from the mathematical models of the motor-basic and optimized, in order accuracy of the both mathematical models to be verified. Finally, magnetic flux density and its distribution in the cross-section of the motor models are determined for different operating regimes by using Finite Element Method (FEM).
机译:纸张研究了FMR-35/6型型扭矩优化的永久分开电容器电机。为此目的,电动机的数学模型与输出扭矩导出,作为用于优化的目标函数。电机数学模型应用于C ++语言开发的程序中,使用遗传算法(GA)进行优化。在GA程序中,电机的几个输入设计参数同时变化。该程序给出了最佳的各种参数集,因此扭矩增加,因此获得了新的电动机的优化模型。优化电机的输出扭矩在额定工作点以及电机启动时增加。 MATLAB / SIMULINK型号设计用于获得电流,速度和扭矩的瞬态特性。将Simulink模型的结果与来自电机基本模型和优化的结果的结果进行了比较,以便验证的两种数学模型的精度。最后,通过使用有限元方法(FEM)来确定不同的操作制度的电动机模型的横截面中的磁通密度及其分布。

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