Development and experimental validation of system-level modelling techniques for mechatronic drivetrain analysis

The performance of mechatronic drivetrains is largely governed by the elasto-dynamic behavior of the gears and bearings. Accurate numerical tools to predict the behavior of these components under a variety of operating conditions are indispensable for reliable and cost-effective virtual prototyping and virtual sensing. While significant strides have been made towards increasing the accuracy and reducing the computational complexity of these tools in view of component-level analyses, the same is not true for system-level analyses. These analyses adhere to different accuracy and efficiency standards, which are driven by the dynamic interaction among the various components in the mechatronic drivetrain. The goal of this PhD is to exploit recent advances in component-level drivetrain modelling to develop and validate, through industrial applications and experiments, system-level modelling strategies in service of virtual prototyping and virtual sensing of mechatronic drivetrains.