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Optimizing Surplus Harmonics Distribution in PWM

机译:优化PWM中的剩余谐波分布

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摘要

The goal of optimal pulse-width modulation (PWM) is to select the switching instances in such a way that a waveform with a particular characteristic is obtained and a certain criterion is minimized. The conventional method to solve the optimal PWM problem would usually lead to large content of surplus harmonics immediately following the eliminated frequency band, which may increase the filter loss and reduce the efficiency and performance of the whole controller. Meanwhile, it may increase the probability of resonance between line impedance and filter components. To overcome the shortcomings of conventional PWM methods, in this paper, we propose an algorithm for pushing the first crest of the surplus harmonics backward, ameliorating the amplitude frequency spectrum distribution of the output waveform, and thus reducing the impact of surplus harmonics. The problem is first formulated as a constrained optimization problem and then a Quantum-inspired Evolutionary Algorithm (QEA) algorithm is applied to solve it. Other than Newton-like methods, the enhanced QEA does not need good initial values for solving the optimal PWM problem and is not stuck in local optimum. The simulation results indicate that the algorithm is robust and scalable for a variety of application requirements.
机译:最佳脉冲宽度调制(PWM)的目的是选择开关实例,以便获得具有特定特性的波形并最小化特定标准。解决最佳PWM问题的常规方法通常会导致在消除频段之后立即产生大量的多余谐波,这可能会增加滤波器损耗并降低整个控制器的效率和性能。同时,这可能会增加线路阻抗和滤波器组件之间发生谐振的可能性。为了克服常规PWM方法的缺点,本文提出了一种将剩余谐波的第一波峰向后推,改善输出波形的幅度频谱分布,从而减少剩余谐波的影响的算法。首先将该问题表述为约束优化问题,然后应用量子启发式进化算法(QEA)求解该问题。除类牛顿法外,增强型QEA不需要良好的初始值即可解决最优PWM问题,并且不会陷入局部最优状态。仿真结果表明,该算法对于各种应用需求均具有鲁棒性和可扩展性。

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