Virtual Sensing System of Vehicle Steering Motor with Virtual Reality

This paper presents a new virtual sensing system for the real-time monitoring of a vehicle steering motor. The aim of the proposed system is to identify the unmeasured dynamic characteristics of the target structure using the inverse force identification method. The system matrices (mass, stiffness, and damping) of the steering motor vibration are generated using the finite element (FE) method, model update approach, and the well-known Craig-bampton reduced-order method. The implicit inverse force identification method is subsequently integrated with the system matrices to predict the unmeasured loading state based on a limited set of measurable acceleration data. Finally, forward time integration provides the full vibration responses and reaction forces of the entire structure. The accuracy and efficiency of the proposed system are examined by the experimental study. The utilization of HoloLens visualization software is implemented in the proposed virtual sensing system for human perception. TCP/IP data connection is then employed to guarantee the attainment of real-time functionality. The user can effectively monitor the physical condition of the target structure using the mixed reality environment.