基于改进遗传算法的三相感应电机参数估计算法

Parameters Estimation Algorithm of TIM Based on Improved Genetic Algorithm

为了降低三相感应电机的参数测量成本,提出了一种基于改进遗传算法的三相感应电机参数估计算法。首先,建立了广义的三相感应电机动态模型,并建立了电机电流与速度的状态空间模型;其次,对遗传算法进行了改进,设计了基于改进遗传算法的函数逼近器,通过最小二乘算法实现曲线的拟合;最终,模型输出三相感应电机的多个关键参数。实验结果表明,该算法能够有效地估计出三相感应电机的7个关键参数,并且实现了较低的估计误差。

In order to reduce the measure cost of the three-phase induction moto(rTIM)parameters,a parameters estimation algorithm of TIM based on the improved genetic algorithm was proposed. Firstly,a generalized dynamic model of TIM was constructed,and the station space model of the current and the speed of the three-phase induction motor were constructed. Then,the genetic algorithm was improved,and a function approximator based on the improved genetic algorithm was designed,the curve fitting was realized by the least squares technique. Lastly,several important parameters of TIM was output by the model. The experimental results show that the proposed algorithm can estimate 7 important parameters of TIM effectively,at the same time,it realizes a low estimation error.