Parameter Identification Of Tire Cornering Stiffness For Commercial Vehicle

Tire cornering stiffness of commercial vehicle is closely related to vehicle handling stability, which is one of the key parameters of vehicle dynamics. At present, using GPS for centroid side-slip Angle, thus the cornering stiffness of front axle is calculated, but there is a measure the actual problem such as cost, reliability, and can not be widely used. Considering the actual situation, this paper only rely on the automotive sensor configuration to realize the model of input and output observations, using the recursive least squares method to identify the cornering stiffness of four wheels for dual-track model vehicle, the specific content as follows.1. The significant meaning of identification of commercial vehicle tire cornering stiffness was studied, and the basic principle、main problems、the main problem、the main methods and research status at home and abroad of parameter identification were summarized. The several commonly used identification methods were listed and the advantages and disadvantages of them are evaluated, which provided the strong basis for selection of identification method in this paper.2. In order to estimate the lateral force and slip angle, the lateral velocity of vehicle centroid was estimated firstly with extended Kalman filter algorithm and building the2-DOF vehicle model of the four wheels for dual-track, based on the HSRI nonlinear tire model.3. Co-simulation of Simulink and Trucksim was adopted to verify validity, in which the curve from the Trucksim was taken as the target. The results showed that the estimated curves were consistent with the target ones, therefore, the accuracy and reliability of the extended Kalman filter estimation method was verified and we could obtain the estimation of lateral force and side-slip angle.4. The cornering stiffness was identified by the recursive least squares method. Recursive least squares algorithm was extracted by the basic idea of the least squares method. The recursive algorithm and the derivation was introduced to estimate the four-wheel cornering stiffness identification and the results were good enough to verify that the modeling was correct and the method was feasible.