Tyre pressure monitoring using a dynamical model-based estimator

In the last few years, various control systems have been investigated in the automotive field with the aim of increasing the level of safety and stability, avoid roll-over, and customise handling characteristics. One critical issue connected with their integration is the lack of state and parameter information. As an example, vehicle handling depends to a large extent on tyre inflation pressure. When inflation pressure drops, handling and comfort performance generally deteriorate. In addition, it results in an increase in fuel consumption and in a decrease in lifetime. Therefore, it is important to keep tyres within the normal inflation pressure range. This paper introduces a model-based approach to estimate online tyre inflation pressure. First, basic vertical dynamic modelling of the vehicle is discussed. Then, a parameter estimation framework for dynamic analysis is presented. Several important vehicle parameters including tyre inflation pressure can be estimated using the estimated states. This method aims to work during normal driving using information from standard sensors only. On the one hand, the driver is informed about the inflation pressure and he is warned for sudden changes. On the other hand, accurate estimation of the vehicle states is available as possible input to onboard control systems.

[1]  Paul J.Th. Venhovens,et al.  Vehicle Dynamics Estimation Using Kalman Filters , 1999 .

[2]  Takaji Umeno,et al.  Observer Based Estimation of Parameter Variations and Its Application to Tire Pressure Diagnosis , 1998 .

[3]  L. Guvenc,et al.  Tire Pressure Monitoring [Applications of Control] , 2007, IEEE Control Systems.

[4]  Jo Yung Wong,et al.  Theory of ground vehicles , 1978 .

[5]  J. A. Lines,et al.  The stiffness of agricultural tractor tyres , 1991 .

[6]  Lei Zuo,et al.  Structured H2 Optimization of Vehicle Suspensions Based on Multi-Wheel Models , 2003 .

[7]  Ali Charara,et al.  Vehicle Dynamics Estimation using Kalman Filtering: Experimental Validation , 2012 .

[8]  Fredrik Gustafsson Slip-Based Estimation of Tire-Road Friction , 1995 .

[9]  M. Ouladsine,et al.  Estimation and Analysis of the Tire Pressure Effects on the Comportment of the Vehicle Center of Gravity , 2006, International Workshop on Variable Structure Systems, 2006. VSS'06..

[10]  Uwe Kiencke,et al.  Automotive Control Systems , 2005 .

[11]  S. Bittanti,et al.  Deterministic convergence analysis of RLS estimators with different forgetting factors , 1988, Proceedings of the 27th IEEE Conference on Decision and Control.

[12]  Fredrik Gustafsson,et al.  Slip-based tire-road friction estimation , 1997, Autom..

[13]  Fredrik Gustafsson,et al.  Indirect Tire Pressure Monitoring using Sensor Fusion , 2002 .

[14]  R. Anderson,et al.  Estimation of tire cornering stiffness using GPS to improve model based estimation of vehicle states , 2005, IEEE Proceedings. Intelligent Vehicles Symposium, 2005..

[15]  Kazuya Yoshida,et al.  Odometry Correction Using Visual Slip Angle Estimation for Planetary Exploration Rovers , 2010, Adv. Robotics.

[16]  Hideki Ohashi,et al.  Observer based estimation of parameter variations and its application to tyre pressure diagnosis , 2001 .

[17]  Levent Guvenc,et al.  Tire Pressure Monitoring , 2007 .