Vehicle states estimation (e.g., vehicle sideslip angle and tire force) is a key factor for vehicle stability control. However, the accurate values of these parameters could not be obtained directly. In this paper, an interacting multiple model-cubature Kalman filter (IMM-CKF) is used to estimate the vehicle state parameters. And improvements about estimation method are achieved in this paper. Firstly, the accuracy of the reference model is improved by building two different models: one is 7-degree-of-freedom (7 DOF) vehicle model with linear tire model, and the other is 7 DOF vehicle model with nonlinear Dugoff tire model. Secondly, the different models are switched by IMM-CKF to match different driving condition. Thirdly, the lateral acceleration correction for sideslip angle estimation is considered, because the sensor of lateral acceleration is easy to be influenced by the gravity on banked road. Then, to compare cubature Kalman filter (CKF) estimation method and IMM-CKF estimation method Hardware-In-Loop (HIL) tests are carried out in the paper. And simulation results show that IMM-CKF methodology can provide accurate estimation values of vehicle states parameters.
For the single-rod double-cylinder and double-coil magnetorheological (MR) damper studied in this paper, the damping force model of the damper is established by adopting multidisciplinary domain modeling method bond graph theory. Firstly, combined with the structure of the MR damper, the bond graph model of the MR damper was established, the damping force model of the damper was derived through the bond graph theory, and the influence factors, such as the displacement, velocity, and acceleration of the damper were considered in the model. Based on the simulation of force-displacement and force-velocity characteristics of the damping force carried out by the damper theoretical model under different currents and velocities as well as the comparison with the damper bench test results, it was found that the force-displacement and force-velocity characteristic experiment curves of the damper agreed well with the simulation results. Under different working conditions, the maximum error of damping force of the MR damper was 7.2%. e damping force model of the MR damper studied in this paper was compared with that of the damper without considering the inertia force of MR fluid, and the influence of the inertia force of MR fluid on the damping force of the MR damper was analyzed. e results show that when the frequency of the damper is large, the inertial force of MR fluid has an important influence on the damping force; therefore, considering the inertial force of MR fluid in the model can greatly improve the accuracy of the model. e influence degree of key parameters on the damping force of the MR damper was studied through the theoretical model; such key parameters ranging from large to small were the channel clearance, energizing current, piston diameter, motion velocity, channel length, zero-field viscosity of MR fluid, and nitrogen pressure. is provides a basis for the adjustment of the damping force of the MR damper.
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