Sample Data for Training the ANN Model of the ANNVR Control

Citation Author(s):
Xiaojun
Deng
Noven
Lee
Junxiang
Yang
Yajie
Jiang
Yun
Yang
Submitted by:
Xiaojun Deng
Last updated:
Sun, 03/30/2025 - 08:07
DOI:
10.21227/ghzw-nq82
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Abstract 

This is the sample data from a switched-capacitor single-input multiple-output (SC-SIMO) converter, which can be utilized to train an artificial neural network (ANN) model. In the dataset, the current references IL3ref, IL2ref, IL1ref, and IL0ref are recorded and applied to the switched-capacitor single-input multiple-output (SC-SIMO) converter, and the introduced inductor currents IL3, IL2, IL1, and IL0 are recorded. During the ANN training process, the inductor currents are considered as the inductor currents references, which are the four inputs of the ANN model. Besides, the recorded IL3ref, IL2ref, and IL1ref are used as the three outputs (IL3vref, IL2vref, and IL1vref) of the ANN model, which are also called as the virtual references (VRs). 

Instructions: 

In the dataset, the current references IL3ref, IL2ref, IL1ref, and IL0ref are recorded and applied to a switched-capacitor single-input multiple-output (SC-SIMO) converter, and the introduced inductor currents IL3, IL2, IL1, and IL0 are recorded. During the training process of the artificial neural network (ANN) model, the inductor currents are considered as the inductor currents references, which are the four inputs of the ANN model. Besides, the recorded IL3ref, IL2ref, and IL1ref are used as the three outputs (IL3vref, IL2vref, and IL1vref) of the ANN model, which are also called as the virtual references (VRs).