Date of Award
2014
Publication Type
Master Thesis
Degree Name
M.A.Sc.
Department
Mechanical, Automotive, and Materials Engineering
Keywords
Dynamic, Powertrain, Shaker, Simulation, Virtual
Supervisor
Minaker, Bruce
Rights
info:eu-repo/semantics/openAccess
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Abstract
In the automotive industry, multi-axis shaker tables are often used to study the damage caused by motion-induced inertia loads to components such as engine mounts or fuel tank strips. To assess the component durability characteristics using this approach, prototype parts must be built and a test rig must be installed. This process is both time and budget consuming, so there is an incentive to reduce the number of physical shaking tests. To that end, this thesis introduces a set of software tools that are capable of conducting virtual shaking simulations with quality output results, i.e., a virtual multi-axial shaker table (VMAST). By refining and reproducing vehicle body acceleration signals collected from the proving grounds, the VMAST is able to replay the body motion of a vehicle. The reproduced motion (drive file) can then be used to drive the virtual dynamic shaking. With the additional consideration of vehicle body local flexibility, the flexible motion can be added to the rigid body motion to improve the simulation accuracy. The dynamic shaking simulation can be done natively in MATLAB, or the drive files derived from MATLAB can be used by other commercial software, such as Altair MotionView. The virtual load data acquisition of the engine bushing mount is implemented during the simulation to predict the fatigue index, which can be referenced in the design procedure. This VMAST provides the automotive engineer with a cost effective tool for analysis, and optimizes the testing process, allowing rapid design iteration.
Recommended Citation
Yang, Xiaowu, "A Virtual Shaker Table for Predicting Loads in Automotive Powertrain Mounts" (2014). Electronic Theses and Dissertations. 5185.
https://scholar.uwindsor.ca/etd/5185