Exploration and practice of high speed EMU digital train based on digital twin

Abstract

Digital twin is one of the key technologies driving the digitalization and intelligence of railway transportation equipment. The development of enabling technologies such as big data, industrial internet of things, and artificial intelligence has facilitated the deep integration of digital twin technology with railway transportation, promoting the high-quality development of the railway transportation industry. This paper studies the design, manufacturing, operation, and maintenance scenarios and requirements of high-speed train sets. Based on the current status of the application and development trends of digital twin technology, it proposes the overall architecture and functional architecture of a digital train for high-speed train sets. The paper also presents the engineering implementation of key high-speed train set bogie systems, providing valuable information for the future construction of digital trains for high-speed train sets.

Keywords

Digital twin / Digital train / Full life cycle / Digital bogie

CRediT authorship contribution statement

Wei Dong: Writing – review & editing, Writing – original draft, Formal analysis, Data curation, Conceptualization. Kexin Sun: Methodology, Formal analysis. Bochuan Ding: Software, Methodology, Data curation. Jilei Yin: Methodology, Conceptualization.

Declaration of Competing Interests

The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Wei Dong reports financial support was provided by the National Key Research and Development Program of China. Wei Dong reports financial support was provided by CRRC Qingdao Sifang Co., Ltd. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgments

The project is supported by the National Key R&D Program of China (Grant No. 2022YFB4301303) and the Major Scientific Research Project of CRRC Qingdao Sifang Co., Ltd. (Grant No. SF/JS-Xu Zi-2024–439).

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