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Digital twinning based adaptive development environment for automotive cyber-physical systems

Digital twinning based adaptive development environment for automotive cyber-physical systems
Digital twinning based adaptive development environment for automotive cyber-physical systems

Automotive cyber-physical systems need to be rigorously checked and tested under various physical conditions. Automakers aim to improve development efficiency of the automotive cyber-physical systems in the fierce market competition. However, the actual development process suffers from the challenges of long development cycle, poor scalability, and low test integrity. To tackle these challenges, this paper develops a digital twinning based adaptive development environment for automotive cyber-physical systems, which addresses two critical problems: 1) each physical entity (i.e., ECU, component, test source, etc) needs to clone a corresponding digital twin; 2) digital twins and the physical entities need to interact closely. The first problem is addressed through proposing an integrated digital twinning clone flow. The second problem is addressed through developing a smart digital twinning board. The case study with the automotive body control system demonstrates that the adaptive development environment achieves a high adaptability with short development cycle, low complexity, low cost, high scalability, and high flexibility, which meet various automotive cyber-physical design requirements during the development process.

Automotive cyber-physical systems, Automotive engineering, Cloning, Digital twin, Industries, Informatics, Process control, Scalability, development environment, digital twinning
1941-0050
Xie, Gouqi
df9bc0be-d3f2-472a-a050-4f1fc373236e
Yang, Kehua
59f3f744-c101-472c-b64d-0bac8470baef
Xu, Cheng
af526865-aee4-4ef6-8174-def5c38149a2
Li, Renfa
dee1a9aa-ab89-49e3-a9eb-64606c7e89b5
Hu, Shiyan
19bb09b2-bf52-4bd7-818a-63e8da474072
Xie, Gouqi
df9bc0be-d3f2-472a-a050-4f1fc373236e
Yang, Kehua
59f3f744-c101-472c-b64d-0bac8470baef
Xu, Cheng
af526865-aee4-4ef6-8174-def5c38149a2
Li, Renfa
dee1a9aa-ab89-49e3-a9eb-64606c7e89b5
Hu, Shiyan
19bb09b2-bf52-4bd7-818a-63e8da474072

Xie, Gouqi, Yang, Kehua, Xu, Cheng, Li, Renfa and Hu, Shiyan (2021) Digital twinning based adaptive development environment for automotive cyber-physical systems. IEEE Transactions on Industrial Informatics. (doi:10.1109/TII.2021.3064364).

Record type: Article

Abstract

Automotive cyber-physical systems need to be rigorously checked and tested under various physical conditions. Automakers aim to improve development efficiency of the automotive cyber-physical systems in the fierce market competition. However, the actual development process suffers from the challenges of long development cycle, poor scalability, and low test integrity. To tackle these challenges, this paper develops a digital twinning based adaptive development environment for automotive cyber-physical systems, which addresses two critical problems: 1) each physical entity (i.e., ECU, component, test source, etc) needs to clone a corresponding digital twin; 2) digital twins and the physical entities need to interact closely. The first problem is addressed through proposing an integrated digital twinning clone flow. The second problem is addressed through developing a smart digital twinning board. The case study with the automotive body control system demonstrates that the adaptive development environment achieves a high adaptability with short development cycle, low complexity, low cost, high scalability, and high flexibility, which meet various automotive cyber-physical design requirements during the development process.

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More information

Accepted/In Press date: 2021
e-pub ahead of print date: 8 March 2021
Additional Information: Publisher Copyright: IEEE Copyright: Copyright 2021 Elsevier B.V., All rights reserved.
Keywords: Automotive cyber-physical systems, Automotive engineering, Cloning, Digital twin, Industries, Informatics, Process control, Scalability, development environment, digital twinning

Identifiers

Local EPrints ID: 450107
URI: http://eprints.soton.ac.uk/id/eprint/450107
ISSN: 1941-0050
PURE UUID: 72e2875d-0789-40ce-bb52-01eab9fdfa34

Catalogue record

Date deposited: 09 Jul 2021 16:34
Last modified: 25 Nov 2021 21:42

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Contributors

Author: Gouqi Xie
Author: Kehua Yang
Author: Cheng Xu
Author: Renfa Li
Author: Shiyan Hu

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