MEMS-Enabled Retrofitting of Automobile Wheel Balancer for Automatic Unbalance Detection

Abstract

The presence of asymmetries in the mass distribution of automobile tires causes anomalous forces and torques, which lead to vibrations and to ride disturbances. For this reason, detection of unbalanced masses is fundamental in order to perform a careful balancing, improving both safety and comfort. To this aim, traditional wheel balancers are passive devices that allow one to detect unbalances relying on force sensors. The major drawbacks of this technology are the high production costs and the loss of accuracy of the force sensors during the wheel balancer lifetime. In this article, a new sensors layout for the next generation of wheel balancers is proposed together with a structural modification of the machine that allows us to magnify the information provided by the sensors. Notably, these modifications are quite practical, and allows retrofitting traditional machines. The goal is to prove the effectiveness of accelerometers and gyroscopes, which are low-cost devices requiring minimum calibration effort, for unbalance detection purposes. To this aim, an unbalance detection algorithm is developed. Starting from the amplitudes and phases of the signals acquired by the sensors, the severity and the angular position of the unbalance are determined relying on a regression model. Then, the proposed detection strategy is experimentally tested in different unbalance conditions.