Digital twin technology in electric and self-navigating vehicles: Readiness, convergence, and future directions - Uma Ravi Sankar Yalavarthy; N Bharath Kumar; Attuluri R Vijay Babu; Rajanand Patnaik Narasipuram; Sanjeevikumar Padmanaban (Energy Conversion and Management: X)
Digital Twin (DT) technology, which creates digital replicas of physical systems, significantly enhances the lifecycle of complex items, systems, and processes. It is especially important in the automotive industry for improving the design, construction, and operation of Electric Vehicles (EVs). Digital Twins make EVs safer, more comfortable, and more enjoyable to drive, thereby enhancing user experience. As mobility systems evolve to become more intelligent and eco-friendlier, electric and self-navigating vehicles are increasingly replacing internal combustion engine vehicles by leveraging technologies such as IoT, Big Data, AI, ML, and 5G. Significant contribution of transportation to global CO2 emissions underscores the need for sustainable practices. Smart EVs, capable of significantly reducing emissions, require innovative architectures like DTs for optimal performance. The advancement of data analytics and IoT has accelerated the adoption of DTs to increase the efficiency of system design, construction, and operation. EV batteries, being the most expensive components, necessitate thorough analysis for State of Charge (SoC) and State of Health (SoH). This review examines the application of DT technology in Intelligent Transportation Systems (ITS), addressing challenges with particular attention on issues regarding monitoring, tracking, battery and charge administration, communication, assurance, and safety. It also explores current trends in EV energy storage technologies and the crucial role of Digital Twins in optimizing battery systems. This technology enables comprehensive digital lifecycle analysis, enhancing battery management efficiency through optimal models for SoC and SoH assessments. Additionally, this review provides insights into various models, future challenges, and discusses DTs for EV battery systems, highlighting case studies, characteristics, and technological opportunities.