An Indirect TPMS Algorithm Based on Tire Resonance Frequency Estimated by AR Model

Paper #:
  • 2016-01-0459

Published:
  • 2016-04-05
Citation:
Zhao, J., Su, J., Zhu, B., and Shan, J., "An Indirect TPMS Algorithm Based on Tire Resonance Frequency Estimated by AR Model," SAE Int. J. Passeng. Cars - Mech. Syst. 9(1):99-106, 2016, https://doi.org/10.4271/2016-01-0459.
Pages:
8
Abstract:
Proper tire pressure is very important for multiple driving performance of a car, and it is necessary to monitor and warn the abnormal tire pressure online. Indirect Tire Pressure Monitoring System (TPMS) monitors the tire pressure based on the wheel speed signals of Anti-lock Braking System (ABS). In this paper, an indirect TPMS method is proposed to estimate the tire pressure according to its resonance frequency of circumferential vibration. Firstly, the errors of ABS wheel speed sensor system caused by the machining tolerance of the tooth ring are estimated based on the measured wheel speed using Recursive Least Squares (RLS) algorithm and the measuring errors are eliminated from the wheel speed signal. Then, the data segments with drive train torsional vibration are found out and eliminated by the methods of correlation analysis. Using the corrected and selected vibration noise, the resonance frequency of the tire vibration system is identified by Maximum Entropy Spectral Estimation (MESE) based on Auto-regressive (AR) model. Finally, the proposed algorithm is verified by test data, and the results show that the resonance frequency can be estimated and the changing of tire pressure can be indicated consequently.
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