电力电子变流器两相冷却系统的神经网络增强控制

IF 3.3 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC
G. Di Nezio;N. E. Lima Baschera;A. Lidozzi;M. di Benedetto;L. Saraceno;F. Ortenzi;L. Solero;Giuseppe Zummo
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引用次数: 0

摘要

本文讨论了一种整合式电源变流器两相冷却系统的控制结构和实现方法。设计并搭建了一个合适的实验平台,对应用于先进多变量TPC系统的基于神经网络的控制结构进行了性能评估实验。与传统的冷却方法相比,拟议的安排允许以非常低的冷却液流速更大程度地提取热量,即使使用标准的工业级散热器也是如此。该技术可用于下一代电力电子转换器。在许多情况下,这种冷却系统的可控性仍然是一个开放的问题,所提出的方法试图提出一种可行的方法,可以在工业级控制板上实施。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Neural Network Enhanced Control of Two-Phase Cooling Systems for Power Electronics Converters
The article deals with the control structure and implementation of a fully integrated two-phase cooling (TPC) system for power converters. A suitable testbed has been properly designed and built to perform the experimental campaign for the performance evaluation of the neural network-based control structure applied to an advanced multivariable TPC system. With respect to traditional cooling approaches, the proposed arrangement allows a greater extraction of the heat at a very low flow rate of the cooling fluid, even with standard industrial-grade heat-sinks. The technology could be implemented for the next generation of power electronics converters. The controllability of such a cooling system is still an open issue in many cases, and the proposed approach tries to suggest a feasible approach, which could be implemented on an industrial grade control board.
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CiteScore
13.50
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