功率器件热网络模型的快速反卷积算法研究

邓二平; 杨颖; 王延浩; 常桂钦; 黄永章; 丁立健

doi:10.13890/j.issn.1000-128X.2023.05.013

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功率器件热网络模型的快速反卷积算法研究

可靠性技术 | 更新时间：2023-10-12

- 功率器件热网络模型的快速反卷积算法研究
- Research on deconvolution methods for thermal network of power devices
- 机车电传动 2023年第5期页码：119-129
- 作者机构：
  
  1.合肥工业大学电气与自动化工程学院，安徽合肥 230009
  2.新能源电力系统国家重点实验室(华北电力大学)，北京昌平 102206
  3.株洲中车时代半导体有限公司，湖南株洲;412001
- 作者简介：
  
  邓二平（1989—），男，博士，教授，博士生导师，主要从事功率半导体器件方面的研究； E-mail: erping.deng@hfut.edu.cn
- 基金信息：
  
  国家自然科学基金资助项目(52007061);新能源电力系统国家重点实验室自主研究课题(LAPS202202)
- DOI：10.13890/j.issn.1000-128X.2023.05.013
  中图分类号：
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邓二平, 杨颖, 王延浩, 等. 功率器件热网络模型的快速反卷积算法研究[J]. 机车电传动, 2023,(5):119-129.

DENG Erping, YANG Ying, WANG Yanhao, et al. Research on deconvolution methods for thermal network of power devices[J]. Electric Drive for Locomotives, 2023,(5):119-129.
邓二平, 杨颖, 王延浩, 等. 功率器件热网络模型的快速反卷积算法研究[J]. 机车电传动, 2023,(5):119-129. DOI： 10.13890/j.issn.1000-128X.2023.05.013.

DENG Erping, YANG Ying, WANG Yanhao, et al. Research on deconvolution methods for thermal network of power devices[J]. Electric Drive for Locomotives, 2023,(5):119-129. DOI： 10.13890/j.issn.1000-128X.2023.05.013.

摘要

采用结构函数法是获得功率器件Cauer热网络模型的重要手段，然而在其反卷积步骤中，不同的计算方法对结果存在较大影响，影响了热网络模型的准确性。各算法的根本机理、不同算法对噪声的放大效果以及算法的合理选取方法等十分重要，且目前亟待解决。文章通过研究结构函数法中反卷积这一核心环节，对3种反卷积计算方法从算法输入、算法核心、误差分析这3个方面进行理论分析，从迭代次数、计算时间、采样频率、算法准确性、算法选择、实际应用这6个方面进行数据分析。针对3种方法计算特点分别总结了其适合的数据特点，为不同类型输入数据选择合适热网络模型的快速计算方法提供了参考和指导。

Abstract

The structure function method is critical for obtaining Cauer thermal network models for power devices. However, in its deconvolution step, different calculation methods have a large impact on the results, which affects the accuracy of the thermal network model. The underlying mechanism of each calculation method, the amplification effect of different calculation methods on noise, and the reasonable selection of calculation methods are very important and need to be solved urgently at present. In this paper, by studying the core aspect of deconvolution in the structure function method, the theoretical analysis of three deconvolution calculation methods was carried out from three aspects: calculation method input, calculation method core, and error analysis; data analysis was carried out from six aspects: number of iterations, calculation time, sampling frequency, accuracy of calculation methods, selection of calculation methods and practical application. The suitable data characteristics were also summarized for each of the three methods according to their calculation characteristics, which provide reference and guidance for selecting appropriate fast calculation methods of thermal network models for different types of input data.

关键词

功率器件结构函数法热网络模型反卷积贝叶斯算法傅里叶算法

Keywords

power devicesstructure function methodthermal network modeldeconvolutionBayesian calculation methodFourier calculation method

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