首页> 外文期刊>IEEE Transactions on Power Electronics >Neuro-Computing Vector Classification SVM Schemes to Integrate the Overmodulation Region in Neutral Point Clamped (NPC) Converters
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Neuro-Computing Vector Classification SVM Schemes to Integrate the Overmodulation Region in Neutral Point Clamped (NPC) Converters

机译:集成中性点钳位(NPC)转换器中过调制区域的神经计算矢量分类SVM方案

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Three-level neutral point clamped (NPC) voltage source converters have recently emerged as important alternatives to conventional two-level converter topologies in high-power medium-voltage energy conversion applications, particularly in high performance ac motor drive systems. An all-inclusive modulation strategy for NPC converters should have the capability of extending the operating range of the converter into the overmodulation region with a smooth and linear transition characteristic. An overmodulation switching strategy based on the space vector classification technique for three-level NPC converters is introduced in this paper. The proposed overmodulation modes, make possible continuous control of the output voltage up to the maximum possible with a smooth linear transition characteristic, and minimum distortions. A theoretical basis for the vector classification space vector modulation technique in the overmodulation region is presented, and the proposed overmodulation schemes are validated by analysis, simulation and experimentation on a 2-KVA three-level NPC converter laboratory prototype
机译:在高功率中压能量转换应用中,特别是在高性能交流电动机驱动系统中,三电平中性点钳位(NPC)电压源转换器已成为传统两电平转换器拓扑的重要替代品。 NPC转换器的全包调制策略应具有将转换器的工作范围扩展到具有平滑和线性过渡特性的过调制区域的能力。介绍了一种基于空间矢量分类技术的三电平NPC变换器的过调制切换策略。所提出的过调制模式可以通过平滑的线性过渡特性和最小的失真来连续控制输出电压,使其达到最大可能。提出了在过调制区域进行矢量分类空间矢量调制技术的理论基础,并通过对2-KVA三电平NPC变换器实验室原型的分析,仿真和实验验证了所提出的过调制方案。

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