The significant progress in the electric automotive industry brought a higher need for new technological innovations. Digital Twin (DT) is one of the hottest trends of the fourth industrial revolution. It allows representing physical assets under various operating conditions in a low-cost and zero-risk environment. DTs are used in many different fields from aerospace to healthcare. However, one of the perspective applications of such technology is the automotive industry. This paper presents an overview of the implementation of DT technology in electric vehicles (EV) propulsion drive systems. A general review of DT technology is supplemented with main applications analysis and comparison between different simulation technologies. Primary attention is given to the adaptation of DT technology for EV propulsion drive systems.

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.

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