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Adaptive Input Voltage Prediction Method Based on ANN for Bidirectional DC-DC Converter

机译:基于双向DC-DC转换器ANN的自适应输入电压预测方法

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For industrial applications, Bidirectional DC-DC converters (BDCs) are used in recent years. And also their efficiency results are improved to apply different control methods. ANN algorithms is one of the new control topic in literature. This paper attempts to improve the dynamic performance of bidirectional dc-dc converter. And it deals with a novel control scheme related with an adaptive input voltage control by using ANN algorithms based on SOM. Firstly, adaptive input voltages are classified by ANN algorithms (SOM, SVM, FF) and the best suitable and proposed ANN algorithm is SOM which is selected for this controller. The best efficiency case is selected in this algorithm. Then, the voltage values are predicted. This voltage values are used in simulation models. Thus, the proposed system works both effective and high efficiency. Theoretical analysis and simulation results obtained from an actual industrial network model in PSCAD verify the viability and effectiveness of the proposed Bidirectional DC-DC Converter (BDC).
机译:对于工业应用,近年来使用双向DC-DC转换器(BDC)。并且还改善了它们的效率结果以应用不同的控制方法。 ANN算法是文献中的新控制主题之一。本文试图提高双向DC-DC转换器的动态性能。并且它涉及一种与基于SOM的ANN算法使用ANN算法相关的新型控制方案。首先,自适应输入电压由ANN算法(SOM,SVM,FF)和最佳合适的ANN算法是SOM,它被选择为该控制器。在该算法中选择了最佳效率案例。然后,预测电压值。该电压值用于仿真模型。因此,所提出的系统既有效又高效率。 PSCAD中实际工业网模型获得的理论分析和仿真结果验证了所提出的双向DC-DC转换器(BDC)的可行性和有效性。

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