数字孪生系统在电动汽车动力系统中的应用:综述

IF 2.6 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC World Electric Vehicle Journal Pub Date : 2024-05-10 DOI:10.3390/wevj15050208
Xiaokang Li, Wenxu Niu, Haobin Tian
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引用次数: 0

摘要

数字孪生(DT)被广泛认为是一种极具潜力的技术,有可能给各行各业带来革命性的变化,成为工业 4.0 时代的一个重要趋势。在低成本、无风险的环境下,数字孪生促进了物理和信息领域的互动与融合。数字孪生的应用横跨不同领域,包括航空航天、医疗保健、智能制造和智慧城市。随着电动汽车的快速发展,对创新技术的开发需求日益增长。数字孪生的一个潜在应用领域是汽车行业。电动汽车(EV)的动力总成系统由动力源、电力电子系统和电机三部分组成,被视为电动汽车的核心部件。本文的重点是对数字孪生技术在电动汽车(EV)动力总成中的应用进行系统回顾。在回顾数字孪生技术发展的同时,分析了其主要应用场景及其在电动汽车动力系统中的应用。最后,总结了数字孪生目前遇到的几个需要解决的挑战,以及其在电动汽车中应用的未来发展。
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Application of Digital Twin in Electric Vehicle Powertrain: A Review
Digital Twin (DT) is widely regarded as a highly promising technology with the potential to revolutionize various industries, making it a key trend in the Industry 4.0 era. In a cost-effective and risk-free setting, digital twins facilitate the interaction and merging of the physical and informational realms. The application of digital twins spans across different sectors, including aerospace, healthcare, smart manufacturing, and smart cities. As electric vehicles have experienced rapid growth, there is a growing demand for the development of innovative technologies. One potential area for digital twins application is within the automotive sector. The powertrain system of electric vehicles (EVs) consists of three parts, power source, power electronic system, and electric motor, which are considered as the core components of electric vehicles. The focus of this paper is to conduct a methodical review regarding the use of digital twins in the powertrain of electric vehicles (EVs). While reviewing the development of digital twin technology, its main application scenarios and its use in electric vehicle powertrains are analysed. Finally, the digital twins currently encounter several challenges that need to be addressed, and so the future development of their application to electric vehicles are summarized.
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来源期刊
World Electric Vehicle Journal
World Electric Vehicle Journal Engineering-Automotive Engineering
CiteScore
4.50
自引率
8.70%
发文量
196
审稿时长
8 weeks
期刊最新文献
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