Minyi Zheng

A Condensation Method for the Dynamic Analysis of Vertical Vehicle–Track Interaction Considering Vehicle Flexibility

This paper is aimed at developing a computationally efficient approach to simulate the vertical dynamic behavior of vehicle–track coupled system. With the finite element method, the car body, bogies, and rail are modeled as Euler beams supported by springs and dashpots, which can investigate the influence of flexibility of the vehicle on structural dynamic response. By a variant of component-mode synthesis (CMS), the degrees-of-freedom (DOFs) within the substructures are condensed and the two substructures are coupled through nonlinear Hertzian theory. Although the system matrix is updated and factorized during the calculation, the total computational efficiency is significantly improved due to the much smaller size of the equations of motion and direct solution algorithm instead of iterative procedure. Compared with an existing model, the accuracy and efficiency of the method are investigated. Application of the model is shown by numerical example.

Physical parameter identification method based on modal analysis for two-axis on-road vehicles: Theory and simulation

Physical parameters are very important for vehicle dynamic modeling and analysis. However, most of physical parameter identification methods are assuming some physical parameters of vehicle are known, and the other unknown parameters can be identified. In order to identify physical parameters of vehicle in the case that all physical parameters are unknown, a methodology based on the State Variable Method(SVM) for physical parameter identification of two-axis on-road vehicle is presented. The modal parameters of the vehicle are identified by the SVM, furthermore, the physical parameters of the vehicle are estimated by least squares method. In numerical simulations, physical parameters of Ford Granada are chosen as parameters of vehicle model, and half-sine bump function is chosen to simulate tire stimulated by impulse excitation. The first numerical simulation shows that the present method can identify all of the physical parameters and the largest absolute value of percentage error of the identified physical parameter is 0.205%; and the effect of the errors of additional mass, structural parameter and measurement noise are discussed in the following simulations, the results shows that when signal contains 30 dB noise, the largest absolute value of percentage error of the identification is 3.78%. These simulations verify that the presented method is effective and accurate for physical parameter identification of two-axis on-road vehicles. The proposed methodology can identify all physical parameters of 7-DOF vehicle model by using free-decay responses of vehicle without need to assume some physical parameters are known.

A New Physical Parameter Identification Method for Two-Axis On-Road Vehicles: Simulation and Experiment

A new physical parameter identification method for two-axis on-road vehicle is presented. The modal parameters of vehicle are identified by using the State Variable Method. To make it possible to determine the matrices , , and of the vehicle, a known mass matrix is designed to add into the vehicle in order to increase the number of equations ensuring that the number of equations is more than the one of unknowns. Therefore, the physical parameters of vehicle can be estimated by using the least square method. To validate the presented method, a numerical simulation example and an experiment example are given in this paper. The numerical simulation example shows that the largest of absolute value of percentage error is 1.493%. In the experiment example, a school bus is employed in study for the parameter identification. The simulation result from full-car model with the estimated physical parameters is compared with the test result. The agreement between the simulation and the test proves the effectiveness of the proposed estimation method.