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Optimal Tire Force Allocation by Means of Smart Tire Technology

Journal Article
ISSN: 1946-3995, e-ISSN: 1946-4002
Published April 08, 2013 by SAE International in United States
Optimal Tire Force Allocation by Means of Smart Tire Technology
Citation: Arat, M., Singh, K., and Taheri, S., "Optimal Tire Force Allocation by Means of Smart Tire Technology," SAE Int. J. Passeng. Cars - Mech. Syst. 6(1):163-176, 2013,
Language: English


The effectiveness of active vehicle safety systems soars with the advances in on-board electronics that allows increasingly complex algorithms to be implemented. Numerous studies expose statistical results that underline the rate of reduction in the involvement of the vehicles equipped with such systems in road accidents. These facts clearly indicate how much the current systems have advanced. Nevertheless there are several areas of improvement for these systems, among which utilizing more information about tire-road states (e.g., tire forces, tire slip and slip-angle, surface friction) ranks very high due to the key role tires play in providing directional stability and control. This study introduces the use of an arriving technology, namely the smart tire technology, to estimate and utilize the aforementioned tire-road states along with an optimal tire force allocation scheme for improved vehicle stability. Based on smart tire data collected using the prototype developed at the Center for Tire Research, an observer scheme is proposed which estimates the lateral and longitudinal tire forces. Lyapunov's direct method is utilized for developing the upper level controller while Quadratic Programming (QP) is used to solve the optimality problem for the tire force allocation which ensures that the control system does not push the tires into the saturation region where the vehicle response dramatically deviates from the expected. The resulting tire forces are then applied through differential braking and torque distribution schemes that are assumed to be available on the vehicle. The proposed control algorithm is implemented in the MATLAB/SimulinkĀ® environment and evaluated using a D-class sedan vehicle model downloaded from CarSimĀ®. Finally the results of the execution of a double lane change maneuver are presented in addition to a discussion about the advantages the proposed method has to offer.