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首页> 外文会议>2012 International Conference on Green Technologies. >Loss minimization of vector controlled induction motor drive using genetic Algorithm
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Loss minimization of vector controlled induction motor drive using genetic Algorithm

机译：基于遗传算法的矢量控制感应电动机驱动器损耗最小化

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摘要

Induction Motors are usually designed for the highest efficiency around their rated load. In most applications, the motor rating matches the worst-case load, but the motor frequently runs below rated conditions. As the load decreases the motor efficiency decreases and a larger percentage of the input power is in the form of losses. The motor efficiency can be improved by operating the motor at optimum flux by controlling the d-axis current in d-q reference frame in vector controlled drives. In this research paper, loss minimization of induction motor based on genetic Algorithm (GA) is proposed. Here the GA is applied to minimize the induction motor losses in order to evaluate the optimal magnetizing current with respect to the torque and speed. The performance of the proposed drive is demonstrated through simulation in MATLAB/SIMULINK environment and compared the same with conventional FOC without minimization. Result shows that there is considerable loss reduction and improvement in efficiency under light load condition using this method.
机译：感应电动机通常设计成在其额定负载附近具有最高效率。在大多数应用中，电动机的额定值与最坏情况下的负载相匹配，但是电动机经常在额定条件下运行。随着负载的减小，电动机效率下降，并且输入功率的较大百分比呈损耗形式。通过控制矢量控制驱动器中d-q参考系中的d轴电流，可以通过以最佳磁通量运行电动机来提高电动机效率。本文提出了一种基于遗传算法的感应电动机损耗最小化算法。在这里，GA用于最小化感应电动机的损耗，以便评估相对于转矩和速度的最佳励磁电流。通过在MATLAB / SIMULINK环境中进行仿真来演示所提出的驱动器的性能，并将其与没有最小化的传统FOC进行比较。结果表明，使用这种方法在轻载条件下具有可观的损耗降低和效率提高。

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