Abstract
This paper presents a novel approach for estimating the vertical load exerted on the rear axle of agricultural vehicles during fieldwork using tire compression measurements. The system comprises an optical time-of-fight (TOF) sensor integrated into the wheel rim, a microcontroller, and an online identification algorithm. The sensor exhibits minimal measurement error, approximately 1%, which, when combined with effective preprocessing and a piecewise linear regression model fueled by tire pressure data, yields a root mean square error (RMSE) of around 7%, with a maximum drawdown of 3% when considering periodic updates. This technology promises to reduce production costs while enabling optimal tire pressure calibration, thereby ensuring reduced fuel consumption and improved comfort for agricultural vehicle operators.
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