Digital Twin in Automotive: A Comprehensive Review of Concepts, Applications, Technologies, and Perspectives

Digital Twin (DT) technology is emerging as a pivotal innovation in the automotive industry. Representing a dynamic, virtual replica of a physical vehicle or component, DTs facilitate bidirectional data flow between the real and virtual worlds. This enables real-time monitoring and sophisticated data fusion, providing the foundation for predictive system analytics and generating critical simulation insights. Leveraging these capabilities, DTs are applied across the entire vehicle lifecycle, from design and manufacturing optimization to crucial operational aspects such as predictive maintenance, particularly for battery health (SoH, RUL), and enhancing vehicle performance, safety, and energy efficiency. While the implementation of automotive DTs presents significant challenges, including complex model construction, data management, and cost, addressing these issues is essential to fully realize the future prospects of this technology in driving forward automotive efficiency, sustainability, and safety.

کلیدواژه ها:

Digital Twin (DT) ، Automotive Industry ، Electric Vehicles ، Battery Management ، Predictive Maintenance ، Artificial Intelligence ، Internet of Things