Research on deconvolution methods for thermal network of power devices
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 calc...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | zho |
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Editorial Department of Electric Drive for Locomotives
2023-09-01
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| Series: | 机车电传动 |
| Subjects: | |
| Online Access: | http://edl.csrzic.com/thesisDetails#10.13890/j.issn.1000-128X.2023.05.013 |
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| _version_ | 1849323435675615232 |
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| author | DENG Erping YANG Ying WANG Yanhao CHANG Guiqin HUANG Yongzhang DING Lijian |
| author_facet | DENG Erping YANG Ying WANG Yanhao CHANG Guiqin HUANG Yongzhang DING Lijian |
| author_sort | DENG Erping |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-b79f415ee6f9433a8a55a4fbb67f93ca |
| institution | Kabale University |
| issn | 1000-128X |
| language | zho |
| publishDate | 2023-09-01 |
| publisher | Editorial Department of Electric Drive for Locomotives |
| record_format | Article |
| series | 机车电传动 |
| spelling | doaj-art-b79f415ee6f9433a8a55a4fbb67f93ca2025-08-20T03:49:03ZzhoEditorial Department of Electric Drive for Locomotives机车电传动1000-128X2023-09-0111912942839395Research on deconvolution methods for thermal network of power devicesDENG ErpingYANG YingWANG YanhaoCHANG GuiqinHUANG YongzhangDING LijianThe 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.http://edl.csrzic.com/thesisDetails#10.13890/j.issn.1000-128X.2023.05.013power devicesstructure function methodthermal network modeldeconvolutionBayesian calculation methodFourier calculation method |
| spellingShingle | DENG Erping YANG Ying WANG Yanhao CHANG Guiqin HUANG Yongzhang DING Lijian Research on deconvolution methods for thermal network of power devices 机车电传动 power devices structure function method thermal network model deconvolution Bayesian calculation method Fourier calculation method |
| title | Research on deconvolution methods for thermal network of power devices |
| title_full | Research on deconvolution methods for thermal network of power devices |
| title_fullStr | Research on deconvolution methods for thermal network of power devices |
| title_full_unstemmed | Research on deconvolution methods for thermal network of power devices |
| title_short | Research on deconvolution methods for thermal network of power devices |
| title_sort | research on deconvolution methods for thermal network of power devices |
| topic | power devices structure function method thermal network model deconvolution Bayesian calculation method Fourier calculation method |
| url | http://edl.csrzic.com/thesisDetails#10.13890/j.issn.1000-128X.2023.05.013 |
| work_keys_str_mv | AT dengerping researchondeconvolutionmethodsforthermalnetworkofpowerdevices AT yangying researchondeconvolutionmethodsforthermalnetworkofpowerdevices AT wangyanhao researchondeconvolutionmethodsforthermalnetworkofpowerdevices AT changguiqin researchondeconvolutionmethodsforthermalnetworkofpowerdevices AT huangyongzhang researchondeconvolutionmethodsforthermalnetworkofpowerdevices AT dinglijian researchondeconvolutionmethodsforthermalnetworkofpowerdevices |