| Title | Digital twin based monitoring and control for DC-DC converters |
| Author | |
| Corresponding Author | Dai，Xiaoran; Hu，Wenshan |
| Publication Years | 2023-12-01
|
| DOI | |
| Source Title | |
| EISSN | 2041-1723
|
| Volume | 14Issue:1 |
| Abstract | The monitoring and control of DC-DC converters have become key issues since DC-DC converters are gradually playing increasingly crucial roles in power electronics applications such as electric vehicles and renewable energy systems. As an emerging and transforming technology, the digital twin, which is a dynamic virtual replica of a physical system, can potentially provide solutions for the monitoring and control of DC-DC converters. This work discusses the design and implementation of the digital twin DC-DC converter in detail. The key features of the physical and twin systems are outlined, and the control architecture is provided. To verify the effectiveness of the proposed digital twin method, four possible cases that may occur during the practical control scenarios of DC-DC converter applications are discussed. Simulations and experimental verification are conducted, showing that the digital twin can dynamically track the physical DC-DC converter, detect the failure of the physical controller and replace it in real time. |
| URL | [Source Record] |
| Indexed By | |
| Language | English
|
| Important Publications | NI Journal Papers
|
| SUSTech Authorship | Others
|
| Funding Project | China Postdoctoral Science Foundation[2022T150496];National Natural Science Foundation of China-Yunnan Joint Fund[62073247];National Natural Science Foundation of China-Yunnan Joint Fund[62103308];National Natural Science Foundation of China-Yunnan Joint Fund[62173255];National Natural Science Foundation of China-Yunnan Joint Fund[62188101];
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| WOS Research Area | Science & Technology - Other Topics
|
| WOS Subject | Multidisciplinary Sciences
|
| WOS Accession No | WOS:001068217000005
|
| Publisher | |
| Scopus EID | 2-s2.0-85170649186
|
| Data Source | Scopus
|
| Citation statistics |
Cited Times [WOS]:0
|
| Document Type | Journal Article |
| Identifier | http://kc.sustech.edu.cn/handle/2SGJ60CL/559402 |
| Department | Southern University of Science and Technology |
| Affiliation | 1.Department of Artificial Intelligence and Automation,School of Electrical Engineering and Automation,Wuhan University,Wuhan,430072,China 2.Center for Control Science and Technology,Southern University of Science and Technology,Shenzhen,518055,China |
| Recommended Citation GB/T 7714 |
Lei，Zhongcheng,Zhou，Hong,Dai，Xiaoran,et al. Digital twin based monitoring and control for DC-DC converters[J]. Nature Communications,2023,14(1).
|
| APA |
Lei，Zhongcheng,Zhou，Hong,Dai，Xiaoran,Hu，Wenshan,&Liu，Guo Ping.(2023).Digital twin based monitoring and control for DC-DC converters.Nature Communications,14(1).
|
| MLA |
Lei，Zhongcheng,et al."Digital twin based monitoring and control for DC-DC converters".Nature Communications 14.1(2023).
|
| Files in This Item: | There are no files associated with this item. | |||||
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