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Genetic Algorithm in Torque Optimisation ofudPermanently Split Capacitor Motor

机译:基于遗传算法的转矩优化永久性分离电容器电机

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摘要

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 withudthe output torque as an objective function for optimization.udMotor mathematical model is applied in program developed inudthe C++ language, which performs the optimization usingudGenetic Algorithm (GA). Several input design parameters of the motor are varied simultaneously in the GA program. Theudprogram 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 theudmathematical 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:论文针对转矩优化研究了FMR-35 / 6型永久分裂电容器电动机。为此,以输出扭矩作为优化的目标函数,得出了电动机的数学模型。 ud以C ++语言开发的程序中应用了电动机数学模型,该程序使用 udGenetic Algorithm(GA)进行了优化。在GA程序中,电机的几个输入设计参数会同时变化。 udprogram提供最佳的可变参数集,为此增加了转矩,因此获得了新的电动机优化模型。优化的电动机的输出转矩在额定工作点以及电动机起动期间都会增加。Matlab/ Simulink模型设计用于获得电流,速度和转矩的瞬态特性。将Simulink模型的结果与基于电动机的 udmathematic模型的结果进行比较并进行优化,以验证两个数学模型的准确性。最后,通过使用有限元方法(FEM)确定了不同运行方式下电机模型横截面中的磁通密度及其分布。

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