High-Fidelity Methodology for Vibration Prediction of Electric Vehicle Gearbox Using Multibody Dynamics Simulation Seoul National University, Department of Biosystems Engineer

Format:

Book

Conference/Event

Author/Creator:

Im, Dongu, author.

Contributor:

Cho, Huije

Chung, Woo-Jin

Lee, Youngsu

Park, Young-Jun

Yim, Heung-Hyeok

Conference Name:

Automotive Technical Papers (2022-01-01 : Warrendale, Pennsylvania, United States)

Language:

English

Physical Description:

1 online resource cm

Place of Publication:

Warrendale, PA SAE International 2022

Summary:

This study proposed a multibody dynamics (MBD) simulation approach for predicting the vibration performance of electric vehicle (EV) gearboxes. Here, the electromagnetic (EM) force excitation was considered with additional EM simulations under discretely increasing rotational speeds to improve the fidelity of the model. The simulation models were built with various scenarios and included the bearing stiffness and radial internal clearance (RIC), output torque, and EM force. The acceleration data obtained from those scenarios were then compared to each other. The results demonstrated: (1) the time-domain simulation represents the transient characteristics of the system, such as the system response at critical speed; (2) EM excitation must be considered for noise, vibration, and harshness prediction of EV gearboxes because it is one of the main excitation sources; and (3) bearing parameters such as RIC and stiffness should be carefully chosen as they directly affect the vibration performance of the gearboxes. The MBD models developed in this study were confirmed to be applicable to the early stage of product development to predict the vibration performance of a prototype

Notes:

Vendor supplied data

Publisher Number:

2022-01-5105

Access Restriction:

Restricted for use by site license