Zhang, Xiaotian, Hu, Yihua, Zhang, Jingwei et al. (3 more authors) (2024) IGBT Module DPT Efficiency Enhancement via Multimodal Fusion Networks and Graph Convolution Networks. IEEE Transactions on Industrial Electronics. pp. 1-12. ISSN 0278-0046
Abstract
The dynamic electrical characteristics of insulated-gate bipolar transistor (IGBT) are of great significance in practical high-power electrical applications and are usually evaluated through double pulse test (DPT). However, DPTs of IGBTs under various working conditions are time-consuming and laborious. Traditional estimation methods are based on detailed physical parameters and complex formula calculations, making deployment process challenging. This article proposes a novel DPT efficiency enhancement method based on graph convolution network (GCN) and feature fusion technology, which can estimate and supplement switching transient waveforms of all working conditions. Thereby, dynamic electrical characteristics of the IGBT are obtained by estimated waveforms of DPT. This method proposes a multimodal attention fusion network to capture and fuse the features of switching transient waveforms between different positions thereby improving the expressive power and performance of the model. Moreover, this method is novel in that it is the first to utilize GCN to embed DPT data under multiple working conditions into a graph structure, which can use the graph structure information to fuse the features of spatially correlated working conditions data to obtain reliable estimation results. The method has been verified to be effective and accurate on real dataset collected on two batches of IGBTs.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | This is an author-produced version of the published paper. Uploaded in accordance with the University’s Research Publications and Open Access policy. |
Keywords: | Behavioral sciences,Double pulse test (DPT),Employee welfare,Estimation,feature fusion,graph convolutional network (GCN),Insulated gate bipolar transistors,insulated-gate bipolar transistor (IGBT),Integrated circuit modeling,Switches,Transient analysis |
Dates: |
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Institution: | The University of York |
Academic Units: | The University of York > Faculty of Sciences (York) > Electronic Engineering (York) |
Depositing User: | Pure (York) |
Date Deposited: | 30 Jul 2024 16:20 |
Last Modified: | 07 Nov 2024 01:49 |
Published Version: | https://doi.org/10.1109/TIE.2024.3368165 |
Status: | Published online |
Refereed: | Yes |
Identification Number: | 10.1109/TIE.2024.3368165 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:215522 |
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Description: IGBT Module DPT Efficiency Enhancement Via Multimodal Fusion Networks and Graph Convolution Networks
Licence: CC-BY 2.5