基于BP神经网络的IGBT结温在线估计系统

Yang Yuan, Lei Yunfei, Wen Yang
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引用次数: 3

摘要

IGBT模块在工业中应用广泛。IGBT模块的寿命和可靠性估计是近年来该领域的研究热点。IGBT模块的寿命和可靠性与其结温密切相关。因此,对IGBT结温的预测成为研究的重要内容。提出了一种基于BP神经网络的IGBT结温在线提取系统。该系统在线提取与结温相关的热电参数VCE(SAT)和关断延迟时间,利用BP神经网络算法获得这两个热电参数与结温之间的对应关系,并利用FPGA和stm32实现了该系统。实验结果表明,该系统能准确预测结温,误差小于2℃。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Online Junction Temperature Estimation System for IGBT Based on BP Neural Network
IGBT module is widely used in industry. The life and reliability estimation of IGBT module are the focus of recent research in this field. IGBT module’s life and reliability are closely related to its junction temperature. Therefore, the prediction of IGBT junction temperature becomes essential of research. In this paper, an online IGBT junction temperature extraction system based on BP neural network is presented. The VCE(SAT) and turn-off delay time of thermoelectric parameters related to junction temperature are extracted online by the system, and the corresponding relationship between these two thermoelectric parameters and junction temperature is obtained using BP neural network algorithm, and the system is implemented with FPGA and stm32. Experimental results show that the system can predict junction temperature with the error less than 2 centigrade.
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