The DOI matches its Crossref record; 79 of the 79 references it cites were found in a registry or an index.
Towards the future of smart electric vehicles: Digital twin technology
Abstract
Abstract Worldwide, transportation accounts for 18% of global carbon dioxide emissions (as of 2019). In order to battle the impending threat of climate change, consumers and industry must adopt sustainable transport that complies with the United Nations Sustainable Development Goals of increased energy efficiency and reduced greenhouse gas emissions. To fulfil these objectives, a new class of vehicles has recently emerged, smart electric vehicles, which is forecasted to reduce carbon dioxide emissions up to 43% as compared to diesel engine vehicles. However, to bring these vehicles to the mainstream, supporting architecture is needed to optimize them in a sustainable manner. One such novel architecture is Digital Twin Technology, which is a virtual mapping technology, extending from it, capable of investigating the lifecycle of multisystem bodies in a digital environment. In recent years, digital twin technology is becoming an underpinning area of research globally. As a result, novel individual research covering digital twin implementation on various aspects of smart vehicles has transpired in research and industrial studies, consequently allowing digital twin technology to evolve over the years. This work aims to bridge the gap between individual research to provide a comprehensive review from a technically-informed and academically neutral standpoint. Conceptual groundwork of digital twin technology is built systematically for the reader, to allow insight into its inception and evolution. The study sifts the digital twin domain for contributions in smart vehicle systems, exploring its potential and contemporaneous challenges to realization. The study then proceeds to review recent research and commercial projects for innovation within this domain. To the knowledge of the authors, this is the first extensive review of the application of digital twin technology in smart electric vehicles. The review has been systematically classified into specific domains within the smart vehicle system such as autonomous navigation control, advanced driver assistance systems, vehicle health monitoring, battery management systems, vehicle power electronics, and electrical power drive systems. An in-depth discussion of each vehicle subsystem is undertaken to present this review as an eclectic panorama of the smart vehicle system. This review further facilitates appreciation of the role of digital twin technology within each classification from a holistic technical perspective. Finally, the work ends with an inspection of the techno-socio-economic impact of digital twin technology that will revolutionize mainstream vehicle technology and the obstacles for further development.
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Citations
Cites
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DIGITAL TWIN: MANUFACTURING EXCELLENCE THROUGH VIRTUAL FACTORY REPLICATION
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Internet of Things: Technology and Value Added
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Cited by
Digital twin: benefits, use cases, challenges, and opportunities
Attaran, M., & Celik, B. G. (2023) · Decision Analytics Journal · doi:10.1016/j.dajour.2023.100165 · Cited by 704
A Survey on Digital Twin for Industrial Internet of Things: Applications, Technologies and Tools
Xu, H., Wu, J., Pan, Q., Guan, X., & Guizani, M. (2023) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2023.3297395 · Cited by 304
A survey of Digital Twin techniques in smart manufacturing and management of energy applications
Wang, Y., Kang, X., & Chen, Z. (2022) · Green Energy and Intelligent Transportation · doi:10.1016/j.geits.2022.100014 · Cited by 147
Lv, Z., & Xie, S. (2024) · Digital Twin · doi:10.12688/digitaltwin.17524.2 · Cited by 112
San, O. (2021) · Nature Computational Science · doi:10.1038/s43588-021-00077-0 · Cited by 66
Metadata
- Authors
- Bhatti, G., Mohan, H., & Raja Singh, R.
- Venue
- Renewable and Sustainable Energy Reviews
- Publisher
- Elsevier BV
- Published
- 2021-05
- Volume
- 141
- Pages
- 110801
- ISSN
- 1364-0321 (ISSN-L)
- OpenAlex
- W3129920713
- Cited by
- 533
- References
- 79
- FWCI
- 46.34
- Type
- journal article
- Language
- en
- Open access
- closed
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