使用ANN控制器设计和实施通用转换器
K Suresh1, E Parimalasundar2, A Arunraja1
1Department of EEE(1), Department of ECE (3), Christ University, Bangalore, India.
Scientific reports
|January 28, 2025
概括
本研究介绍了一个人工神经网络 (ANN) 控制的通用转换器,展示了高效和自适应的功率转换. 该ANN控制器确保稳定的输出和高效率在各种模式,满足现代电力系统的需求.
科学领域:
- 电气工程 电气工程
- 电力电子 电力电子 电力电子
- 人工智能的人工智能
背景情况:
- 现代电力系统需要多功能和高效的电力转换解决方案.
- 传统的转换器在不同的操作条件下经常面临适应性和效率的限制.
研究的目的:
- 详细介绍由人工神经网络 (ANN) 控制的通用转换器的硬件实现.
- 评估ANN控制器在管理多种操作模式和确保电源质量的性能.
主要方法:
- 使用绝缘门双极晶体管 (IGBT),电感器和电容器的硬件实现.
- 通过数字信号处理器 (DSP) 执行预训练的ANN算法来进行脉冲宽度调制 (PWM) 信号生成的控制.
- 基于实时反的动态模式选择,用于五种操作模式:整流器,逆变器提升,直流-直流,直流-直流提升和交流电压控制.
主要成果:
- 在调整器和逆变器模式下,ANN控制器保持总波扭曲 (THD) 在5%以下.
- 在DC-DC模式下实现了94-96%的整体效率.
- 证明了自适应控制,提高了功率转换质量,并减少了开关损失.
结论:
- 由ANN控制的通用转换器有效地满足了现代电力系统的需求.
- 该系统提供了多功能和适应性控制,以实现高效的功率转换.
- 该ANN控制器显著提高了电源质量和运营效率.
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