Track: Undergraduate Research Competition

Abstract

A Digital Twin is a virtual representation of a real dynamic system that can simulate its current conditions, predict its future behavior, and log valuable information about its internal operation and interactions with other systems. The unique capability of automatic bidirectional information flow between virtual and physical worlds and predictive analysis of Digital Twins are what make this emergent technology greatly innovative and of significant value. The objective of this case study is to implement a vehicle’s performance Digital Twin concept on an electric passenger bus and analyze the technology’s adaptability level, capabilities, scope, limits, and future improvements. This system incorporates a network of sensing devices mounted on the vehicle, a real-time simulation model, edge computing capabilities and the possibility of incorporating predictive maintenance models to determine remaining useful life of components. The Digital Twin is thought to have great value when it comes to gaining deep insight on the dynamic performance of the bus, analyzing energy waste, exploring determining factors of energy usage and monitoring the current and future state of the vehicle. All of this being possible through simulation technology, digital modeling, physical and virtual sensors, edge computing, Internet-of-Things networks, and Machine Learning algorithms.