A Digital Twinning Approach for the Internet of Unmanned Electric Vehicles (IoUEVs) in the Metaverse

Abstract

Regarding the importance of the Internet of Things (IoT) and the Metaverse as two practical emerging technologies to enhance the digitalization of public transportation systems, this article introduces an approach for the improvement of IoT and unmanned electric vehicles in the Metaverse, called the Internet of Unmanned Electric Vehicles (IoUEVs). This research includes two important contributions. The first contribution is the description of a framework for how unmanned electric vehicles can be used in the Metaverse, and the second contribution is the creation of a digital twin for an unmanned electric vehicle. In the digital twin section, which is the focus of this research, we present a digital twin of an electronic differential system (EDS) in which the stability has been improved. Robust fuzzy logic algorithm-based speed controllers are employed in the EDS to independently control the EV wheels driven by high-performance brushless DC (BLDC) electric motors. In this study, the rotor position information of the motors, which is estimated from the low-precision Hall-effect sensors mounted on the motors’ shafts, is combined and converted to a set of common switching signals for empowering the EDS of the electric vehicle traction drive system. The proposed digital twin EDS relies on an accurate Hall sensor signals-based synchronizing/locking strategy with a dynamic steering pattern capable of running in severe road conditions with different surface profiles to ensure the EV’s stability. Unlike recent EDSs, the proposed digital twinning approach includes a simple practical topology with no need for auxiliary infrastructures, which is able to reduce mechanical losses and stresses and can be adapted to IoUEVs more effectively.