A systematic review of digital twins for electric vehicles

IF 7.4 2区 工程技术 Q1 ENGINEERING, CIVIL Journal of Traffic and Transportation Engineering-English Edition Pub Date : 2024-10-01 DOI:10.1016/j.jtte.2024.04.004
Shrey Verma , Ankush Sharma , Binh Tran , Damminda Alahakoon
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Abstract

The transport sector emits 18% of global CO2. Industry and consumers must adopt green mobility to reduce emissions and climate change. This will help achieve sustainability by improving efficiency and reducing greenhouse gas emissions. Thus, smart electric vehicles (SEVs) have emerged. Digital twins concept and technology may help launch SEVs to the market by analysing and optimising supporting infrastructure. This work aims to fill in the gaps between different pieces of research by giving a full review from a technical and scientifically neutral point of view. The study looks at how digital twin technology can be used in smart car systems by looking at its promise and the hurdles faced. Based on a comprehensive literature survey, this is the first in-depth look at how digital twin technology can be used in smart electric cars. The review has been organised into specific areas of the smart vehicle system, such as drive train system battery management system, driver assistance system, vehicle health monitoring system, vehicle power electronics. This review goes into detail about each component of the car to provide an overall view of the smart vehicle system as a whole. This review makes it easier to understand how digital twin technology can be utilized into each area from a scientific point of view. Lastly, the work looks at the technological and economic impact of digital twin technology, which will make considerable changes in car manufacturing processes, as well as help address current obstacles in utilizing advanced technologies.
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电动汽车数字孪生系统回顾
交通部门排放的二氧化碳占全球总量的 18%。工业和消费者必须采用绿色交通,以减少排放和气候变化。这将有助于通过提高效率和减少温室气体排放来实现可持续发展。因此,智能电动汽车(SEVs)应运而生。数字孪生概念和技术可通过分析和优化配套基础设施,帮助将智能电动汽车推向市场。这项工作旨在从技术和科学中立的角度进行全面审查,从而填补不同研究之间的空白。本研究通过审视数字孪生技术的前景和面临的障碍,探讨如何将其应用于智能汽车系统。在全面文献调查的基础上,本研究首次深入探讨了数字孪生技术如何应用于智能电动汽车。综述按智能汽车系统的具体领域进行了分类,如传动系统、电池管理系统、驾驶员辅助系统、车辆健康监测系统、车辆电力电子系统等。本综述详细介绍了汽车的每个组件,以提供智能汽车系统的整体视图。通过回顾,我们更容易从科学的角度理解如何将数字孪生技术应用到各个领域。最后,本研究还探讨了数字孪生技术对技术和经济的影响,它将极大地改变汽车制造流程,并有助于解决目前在利用先进技术方面存在的障碍。
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来源期刊
CiteScore
13.60
自引率
6.30%
发文量
402
审稿时长
15 weeks
期刊介绍: The Journal of Traffic and Transportation Engineering (English Edition) serves as a renowned academic platform facilitating the exchange and exploration of innovative ideas in the realm of transportation. Our journal aims to foster theoretical and experimental research in transportation and welcomes the submission of exceptional peer-reviewed papers on engineering, planning, management, and information technology. We are dedicated to expediting the peer review process and ensuring timely publication of top-notch research in this field.
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