Nonlinear observers of tire forces and sideslip angle estimation applied to road safety: Simulation and experimental validation

Extensive research is focus on the stability control in the modern industrial auto-mobile society. Some active safety systems, such as Electronic Stability Program (ESP) and Traction Control System (TCS) have been widely used as safety option in our quotidian cars. These systems are based on the information which contains the motion characteristic of vehicle. Nevertheless, some complex safety system needs more information which can preferable describe the precise motion features, such as sideslip angle and tire forces. This article will principally present two non-linear observers: EKF (Extended Kalman filter) and PF (Particle filter) to estimate these variables, respectively. These observers are designed based on the non-linear double track model. The Dugoff model is used to elaborate the relation between tire forces and sideslip angle. Performances of these observers are tested by using the experimental data in real driving test, using our laboratory vehicle equipped with a real-time sampling and processing system. Particularly, the estimation process with EKF has been developed as a real-time application for the onboard test. Furthermore, a simulator is involved in the critical driving test which is hazardous in real driving condition.

[1]  J. Kim Identification of lateral tyre force dynamics using an extended Kalman filter from experimental road test data , 2009 .

[2]  Rajesh Rajamani,et al.  Vehicle dynamics and control , 2005 .

[3]  Uwe Kiencke,et al.  NONLINEAR OBSERVER DESIGN FOR LATERAL VEHICLE DYNAMICS , 2005 .

[4]  H. Dugoff,et al.  Tire performance characteristics affecting vehicle response to steering and braking control inputs. Final report , 1969 .

[5]  Rudolph van der Merwe,et al.  The unscented Kalman filter for nonlinear estimation , 2000, Proceedings of the IEEE 2000 Adaptive Systems for Signal Processing, Communications, and Control Symposium (Cat. No.00EX373).

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

[7]  J. Christian Gerdes,et al.  EXPERIMENTAL STUDIES OF USING STEERING TORQUE UNDER VARIOUS ROAD CONDITIONS FOR SIDESLIP AND FRICTION ESTIMATION , 2007 .

[8]  Neil J. Gordon,et al.  A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking , 2002, IEEE Trans. Signal Process..

[9]  D Lechner,et al.  A method to estimate the lateral tire force and the sideslip angle of a vehicle: Experimental validation , 2010, Proceedings of the 2010 American Control Conference.

[10]  Li,et al.  Real-time Tire Parameters Observer for Vehicle Dynamics Stability Control , 2010 .

[11]  Ali Charara,et al.  Nonlinear observer of sideslip angle using a particle filter estimation methodology , 2011 .

[12]  Bo-Chiuan Chen,et al.  Sideslip angle estimation using extended Kalman filter , 2008 .

[13]  Takeshi Nishida,et al.  Dynamic state estimation using particle filter and adaptive vector quantizer , 2009, 2009 IEEE International Symposium on Computational Intelligence in Robotics and Automation - (CIRA).

[14]  Ali Charara,et al.  Experimental evaluation of observers for tire–road forces, sideslip angle and wheel cornering stiffness , 2008 .