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电动汽车应用的数字孪生平台概述。

Overview of Digital Twin Platforms for EV Applications.

机构信息

Department of Electrical Power Engineering and Mechatronics, Tallinn University of Technology, 19086 Tallinn, Estonia.

出版信息

Sensors (Basel). 2023 Jan 27;23(3):1414. doi: 10.3390/s23031414.

Abstract

Digital twin (DT) technology has been used in a wide range of applications, including electric vehicles. The DT platform provides a virtual representation or advanced simulation of a physical object in real-time. The implementation of DT on various aspects of EVs has recently transpired in different research studies. Generally, DT can emulate the actual vehicle on the road to predict/optimize its performance and improve vehicle safety. Additionally, DT can be used for the optimization of manufacturing processes, real-time condition monitoring (at all levels and in all powertrain components), energy management optimization, repurposing of the components, and even recycling processes. This paper presents an overview of different DT platforms that can be used in EV applications. A deductive comparison between model-based and data-driven DT was performed. EV main systems have been discussed regarding the usable DT platform. DT platforms used in the EV industry were addressed. Finally, the review showed the superiority of data-driven DTs over model-based DTs due to their ability to handle systems with high complexity.

摘要

数字孪生 (DT) 技术已广泛应用于各个领域,包括电动汽车。DT 平台实时提供物理对象的虚拟表示或高级模拟。最近,不同的研究在电动汽车的各个方面都实施了 DT。一般来说,DT 可以模拟实际车辆在道路上的行驶情况,以预测/优化其性能并提高车辆安全性。此外,DT 还可用于优化制造工艺、实时状态监测(在所有级别和所有动力传动系统组件中)、能源管理优化、部件再利用,甚至回收过程。本文概述了可用于电动汽车应用的不同 DT 平台。对基于模型和基于数据的 DT 进行了演绎比较。讨论了电动汽车的主要系统,以及可用的 DT 平台。讨论了电动汽车行业中使用的 DT 平台。最后,综述表明,由于数据驱动的 DT 能够处理具有高复杂性的系统,因此其优于基于模型的 DT。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b1b0/9919527/94bb21429a87/sensors-23-01414-g001.jpg

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