Robust algorithm of indirect tyre pressure monitoring system based on tyre torsional resonance frequency analysis

This paper focuses on an indirect Tyre Pressure Monitoring System (TPMS) algorithm based on frequency analysis of tyre torsional vibration. Tyre vibration is analysed using a tyre structure model, and the tyre resonance frequency is estimated using an Autoregressive (AR) model. The vibration disturbances from the engine and driveline that affect the estimation of the tyre torsional frequency are analysed, and a notch filter is designed to eliminate the disturbances. The torsional vibration of the driveline is identified by the correlation analysis of driving wheel speed. Two qualitative evaluation indexes of tyre torsional vibration characteristics are proposed. The corresponding quantitative parameters are used to determine the tyre torsional vibration state to eliminate the interference of undesirable vibration states on the frequency calculation. A road roughness estimation method is proposed based on tyre vertical vibration information in the wheel speed. The estimated road roughness parameters compensate for the calculated resonance frequency affected by road roughness. Based on the relationship between measured resonance frequency and temperature under a constant tyre pressure condition, the frequency variation value affected by tyre rubber stiffness variation due to temperature variation is calculated using the ambient temperature signal. The calculated resonance frequency is corrected to eliminate the coupling effect of gas stiffness and rubber stiffness, the impact of temperature variation on tyre pressure estimation is compensated. The results of vehicle road tests demonstrate the robustness of the proposed tyre pressure monitoring algorithm.

Automated summary

This paper focuses on an algorithm for an indirect Tyre Pressure Monitoring System (TPMS) based on frequency analysis of tyre torsional vibration. The authors analyze tyre vibration using a tyre structure model and estimate the resonance frequency using an Autoregressive (AR) model. They also propose a method to compensate for road roughness and temperature variation effects on tyre pressure estimation. The results of road tests demonstrate the robustness of the proposed algorithm.