A Computational Framework for Predicting Vibrations in the Front-Loading Washing Machine Using Component-Level Experiments and Mathematical Modeling

Abstract

This study proposes a computational framework for developing a multibody dynamics (MBD) model to accurately predict the vibration behavior of front-loading washing machines. The framework integrates component-level experiments and mathematical modeling to characterize the dynamic behavior of key components, including the free-stroke damper, connecting bushing, and gasket, which significantly influence the machine's vibration. Simplified, yet precise, mathematical models were developed and validated against experimental data to represent these components' dynamic characteristics. The validated models were then integrated into a comprehensive MBD model of a front-loading washing machine. This model was further verified by comparing its predicted vibrations with experimental results obtained from actual washing machines. A parametric study assessed the model's accuracy under various unbalanced mass conditions and revolutions per minute ranges, which revealed that the model is capable of generalization across different operating scenarios. Although some errors remain in specific cases involving phase differences, the overall average error is 20.11%, with a standard deviation of 4.10%. These results demonstrate that the proposed framework effectively captures the vibration behavior of front-loading washing machines, offering a reliable tool for enhancing design and operational efficiency.