Advanced Calibration and Compensation for Nonlinearities in Ball Joint-Integrated Hall Sensors for Accurate Ride Height Measurement

Abstract

This study is motivated by the critical need for accurate and durable ride height sensors in modern automotive systems, particularly as these sensors play a crucial role in maintaining vehicle stability and safety. Current sensors’ susceptibility to environmental damage and inherent nonlinearities highlight the necessity for improved sensor designs and nonlinearity correction algorithms. To address these issues, this study proposes a novel sensor system that integrates a ball joint and a Hall sensor to enhance the accuracy and durability of ride height sensors and develops a Real-time Nonlinearity Correction and Calibration (RNCC) Algorithm for real-time correction. The RNCC algorithm combines Model Reference Adaptive Control (MRAC), Kalman filtering, and nonlinear optimization techniques to correct sensor nonlinearity in real-time, enabling precise position measurement. Experimental results demonstrate that the RNCC algorithm can calibrate sensors more quickly and accurately than existing methods and is effective in handling outlier data. This research suggests the potential for the RNCC algorithm to be applied in various real-time control applications and contribute to improving automotive suspension systems.

Keywords

• Hall sensor calibration
• ball joint integration
• ride height measurement
• nonlinear compensation
• real-time nonlinear compensation and calibration (RNCC)