Citation: Ibrahim, M.; Rassõlkin, A.;
Vaimann, T.; Kallaste, A. Overview
on Digital Twin for Autonomous
Electrical Vehicles Propulsion Drive
System. Sustainability 2022, 14, 601.
https://doi.org/10.3390/
su14020601
Academic Editors: J. C. Hernandez
and Thanikanti Sudhakar Babu
Received: 25 November 2021
Accepted: 4 January 2022
Published: 6 January 2022
Publisher’s Note: MDPI stays neutral
with regard to jurisdictional claims in
published maps and institutional affil-
iations.
Copyright: © 2022 by the authors.
Licensee MDPI, Basel, Switzerland.
This article is an open access article
distributed under the terms and
conditions of the Creative Commons
Attribution (CC BY) license (https://
creativecommons.org/licenses/by/
4.0/).
sustainability
Review
Overview on Digital Twin for Autonomous Electrical Vehicles
Propulsion Drive System
Mahmoud Ibrahim * , Anton Rassõlkin , Toomas Vaimann and Ants Kallaste
Department of Electrical Power Engineering and Mechatronics, Tallinn University of Technology,
19086 Tallinn, Estonia; anton.rassolkin@taltech.ee (A.R.); toomas.vaimann@taltech.ee (T.V.);
ants.kallaste@taltech.ee (A.K.)
* Correspondence: mahmoh@taltech.ee
Abstract: 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.
Keywords: electric vehicle propulsion drive system; digital twin; hardware in the loop;
real-time simulation
1. Introduction
Considerable values have been brought to the entire industry over the last decades
due to digital manufacturing. Through virtually represented factories, resources, work-
forces, and skills, etc., digital manufacturing builds models and simulates product and
process development. The remarkable progress in communication and information tech-
nologies has advanced the development of manufacturing widely [1]. Computer-aided
technologies, including Computer-Aided Design (CAD), Computer-Aided Engineering
(CAE), Computer-Aided Manufacturing (CAM), Finite Element Analysis (FEA), Product
Data Management (PDM), etc., are quickly developing and playing a vitally critical role
in the modern industry [2,3]. Advanced data analytics and the Internet of Things (IoT)
connectivity have increased the volume of data usable from manufacturing, healthcare,
and smart city environments [4]. IoT environment, coupled with data analytics, provides
an essential resource for predictive maintenance, fault detection, the future health of man-
ufacturing processes, and smart city developments [5]. Digital Twin (DT) can overcome
integration between IoT and data analytics through its ability to create connected physi-
cal and virtual models. A DT environment enables high-speed and real-time simulation
analysis accurately [6].
This review highlights DT as a trending technology in different applications and
sectors as it is ongoingly discussed in the following sections. A deductive comparison
between different simulation technologies over time is discussed in Section 1.1. Different
existing and prospective applications of DT are presented in Section 1.2. In Section 1.3,
varieties of DT software and platforms and their specific applications are discussed. DT
for AEV propulsion drive system as the main review topic is extensively discussed in
Section 2. A comparative analysis between Hardware in loop HIL and DT simulations for
AEV propulsion drive systems is discussed in Sections 2.2 and 2.3, respectively. Figure 1
provides an illustrative diagram of the Introduction section’s content.
Sustainability 2022, 14, 601. https://doi.org/10.3390/su14020601 https://www.mdpi.com/journal/sustainability