Dynamic analysis of automotive wheel bearings

Bearings are mechanical components that support loads and transmit rotational motion. With the increasing demand for high-value-added products, such as semiconductors, aerospace components, and robotics, the need for more precise and diverse applications has grown. Consequently, accurate bearing performance prediction and evaluation technologies have become essential. Bearing performance prediction is generally classified into static and dynamic approaches. Traditionally, research has primarily focused on static and quasi-static predictions based on bearing theory. However, these methods have a significant limitation in that they fail to accurately consider the actual behavior of bearings. As a result, the necessity for prediction methods based on numerical analysis, which can account for the time-dependent behavior of bearings, has been increasingly recognized. In this study, dynamic analysis of bearings was conducted to evaluate their behavior over time. First, dynamic analysis of deep groove ball bearing was performed, and the results were compared with those obtained using bearing theory to validate the reliability of the proposed dynamic analysis. Additionally, dynamic analysis of an automotive wheel bearing was carried out to investigate the behavior of key elements, particularly balls and contact angles.