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Space-vector pulse-width modulation of a Z-source six-phase inverter with neural network classification

机译:具有神经网络分类的Z源六相逆变器的空间矢量脉宽调制

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In this study, a space-vector pulse-width modulation (SVPWM) method is presented for a Z-source six-phase inverter using the neural network (NN) classification. The Z-source inverter is a new generation of inverters with buck and boost features. Using an L-C network placed between the power supply and the switches, this modulation method can result in unique features which are not achieved through traditional inverters. NN classification can help in reducing the complexity of calculations for the SVPWM method in a six-phase inverter. NN classification reduces the required computational efforts and makes it possible to increase switching frequency. In addition, the method results in a smaller system in terms of hardware and software, and generates more precise pulses. The modulation method presented in this study uses the minimum number of switching vectors. Here, 14 switching vectors are employed instead of 64. In fact, only large vectors in a plane are selected. Moreover, an additional vector, called 'shoot through', is considered for creating buck and boost features in the six-phase Z-source inverters. Therefore using 15 switching vectors, it is possible to achieve minimum switching in the six-phase Z-source inverters with buck and boost capabilities. Practical and simulation results for this type of inverter connected to a six-phase induction motor are also presented.
机译:在这项研究中,提出了一种使用神经网络(NN)分类的Z源六相逆变器空间矢量脉宽调制(SVPWM)方法。 Z源逆变器是具有降压和升压功能的新一代逆变器。通过在电源和开关之间放置一个L-C网络,这种调制方法可以产生独特的功能,而这些功能是传统逆变器无法实现的。 NN分类可以帮助降低六相逆变器中SVPWM方法的计算复杂性。 NN分类减少了所需的计算工作量,并有可能增加开关频率。另外,该方法在硬件和软件方面导致较小的系统,并产生更精确的脉冲。本研究中提出的调制方法使用最少数量的开关矢量。在此,使用14个切换向量代替64个。实际上,仅选择平面中的大向量。此外,考虑使用一个称为“穿通”的附加矢量来在六相Z源逆变器中创建降压和升压功能。因此,使用15个开关矢量,可以在具有降压和升压功能的六相Z源逆变器中实现最小的开关。还介绍了与六相感应电动机连接的这种类型逆变器的实际和仿真结果。

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