Reduced Order Model of Vehicle Parametric Components Based on Reduced Basis

With the rapid development and accelerated breakthrough of the new generation of information technology, digital twin technology is deeply integrated with the transportation industry, and digital transformation has become an important trend in the development of transportation. How to accurately construct the digital twin model of complex traffic through the fusion of virtual and real is an urgent scientific problem in the current academic research frontier. As a key component of the digital twin, the reduced order model can build a high-fidelity simplified model of the system and provide a high reliability basis for the decision making of the complex system. It is difficult for complex system models to solve the problems of developing simplified models in offline stage and evaluating full-order models many times in online stage. To address these challenges, this paper proposes a reduced order model method for vehicle parameterized components based on reduced basis.