Optimal Skyhook and Groundhook Control for Semiactive Suspension: A Comprehensive Methodology

This manuscript establishes a methodology that guides the designers to develop an optimal controller for a semiactive suspension system. The methodology’s processes are generally explained and straightforwardly, so a designer can extrapolate the methodology to a specific problem. Furthermore, this research presents an optimal control strategy for a semiactive control applied to a quarter vehicle model as an example of using the methodology. A particular interest is made in the advantages of such a simple synthesis and in the compromises that must be done in skyhook and groundhook control law applications. This manuscript exposes a logical and straightforward approach for choosing the controllers’ design parameters; also, efforts must be made to express precise performance specifications and constraints in the control design. The herein methodology could be relevant in the process design for intelligent suspensions, from one-quarter toward the entire vehicle.

Hybrid Model Predictive Control of Semiactive Suspension in Electric Vehicle with Hub-Motor

In hub-motor electric vehicles (HM-EVs), the unbalanced electromagnetic force generated by the HM will further deteriorate the dynamic performance of the electric vehicle. In this paper, a semiactive suspension control method is proposed for HM-EVs. A quarter HM-EV model with an electromechanical coupling effect is established.The model consists of three parts: a motor model, road excitation model and vehicle model. A hybrid model predictive controller (HMPC) is designed based on the developed model, taking into account the nonlinear constraints of damping force. The focus is on improving the vertical performance of the HM-EV. Then, a Kalman filter is designed to provide the required state variables for the controller. The proposed control algorithm and constrained optimal control (COC) algorithm are simulation compared under random road excitation and bump road excitation, and the results show that the proposed control algorithm can improve ride comfort, reduce motor vibration, and improve handling stability more substantially.

Dynamic Response of a Semiactive Suspension System with Hysteretic Nonlinear Energy Sink Based on Random Excitation by means of Computer Simulation

This paper aims to investigate the property and behavior of the hysteretic nonlinear energy sink (HNES) coupled to a half vehicle system which is a nine-degree-of-freedom, nonlinear, and semiactive suspension system in order to improve the ride comfort and increase the stability in shock mitigation by using the computer simulation method. The HNES model is a semiactive suspension device, which comprises the famous Bouc–Wen (B-W) model employed to describe the force produced by both the purely hysteretic spring and linear elastic spring of potentially negative stiffness connected in parallel, for the half vehicle system. Nine nonlinear motion equations of the half vehicle system are derived in terms of the seven displacements and the two dimensionless hysteretic variables, which are integrated numerically by employing the direct time integration method for studying both the variables of vertical displacements, velocities, accelerations, chassis pitch angle, and the ride comfort and driver safety, respectively, based on the bump and random road inputs of the pseudoexcitation method as excitation signal. Simulation results show that, compared with the HNES model and the magnetorheological (MR) model coupled to the half vehicle system, the ride comfort and stability have been evidently improved. A successful validation process has been performed, which indicated that both the ride comfort and driver safety properties of the HNES model coupled to half vehicle significantly improved.

Semiactive Control of High-Speed Railway Vehicle Suspension Systems with Magnetorheological Dampers

Using the magnetorheological (MR) damper model, this paper derives a semiactive suspension model for a high-speed railway vehicle, and a new evaluating method is proposed to analyze the effect of two kinds of time delay existing in control systems on vehicle dynamic performance. The railway vehicle is modeled by a 50 degree-of-freedom (DOF) system which considers the full 6 DOF of each wheelset, bogie, car body, and the pitch angle of each axle box. Several control strategies, sky-hook (SH), acceleration-driven damping (ADD), and mixed SH-ADD, are considered in the semiactive suspension system. To evaluate the effect of these semiactive controls and the different kinds of time delay on the lateral ride index of a high-speed railway vehicle, a 3D surface in a rectangular coordinate system is described. The cross curve between the 3D surface and a horizontal plane which represents the performance of passive suspension is projected on the X-Y plane, and the area enclosed by the contour line, X-axis, and Y-axis can be used to evaluate the performance of semiactive controls. The results show that the new method is convenient to evaluate the performance of semiactive control strategies visually when there is more than one kind of time delay.

Robust Nonfragile H∞ Control of Lateral Semiactive Suspension of Rail Vehicles

This paper focuses on the riding comfort of railway vehicle. A nonfragile control strategy is proposed based on robust theory for semiactive suspension system. First, the rail vehicle dynamic model was simplified reasonably, the control model of rail vehicle train lateral semiactive suspension was built, which involved lateral-moving, head-shaking, and side-rolling of the vehicle body and the lateral-moving of the two bogies, and the robust nonfragile H∞ control of head-shaking and side-rolling were designed, respectively. Then the H∞ norm was used to reflect riding comfort; the sufficient conditions for the existence of robust nonfragile H∞ control were developed based on linear matrix inequality (LMI) approach. The design of a robust nonfragile H∞ control with gain perturbation was changed into an optimization issue with linear inequality constraint and a linear objective function. And then the damping effect of the robust nonfragile H∞ controller was evaluated, the wavelet packet analysis theory was used to decompose and reconstruct the acceleration signal, the fragility of the controller was analyzed, and the theory of mathematical statistics was adopted to analyze the influence of robust nonfragile H∞ controller on the probability distribution of vibration acceleration. Finally, the simulation results show that the proposed control strategy can ensure the riding comfort of railway vehicle efficiently and has a comparatively strong nonfragility.

Smith Predictor-Taylor Series-Based LQG Control for Time Delay Compensation of Vehicle Semiactive Suspension

A Smith predictor-Taylor series-based LQG (STLQG) control to compensate time delay of a semiactive suspension system is newly presented. This control consists of a Taylor series-based LQG (TLQG) control and a Smith predictor based on the TLQG. The TLQG control compensates one half of time delay to decrease magnification from whole time delay compensation. The Smith predictor based on the TLQG compensates the other half to decrease horizontal shift from whole time delay compensation using the Smith predictor-based LQG. Finally, a practical case illustrates advantages of the STLQG control.

Modeling and Control of a Shear-Valve Mode MR Damper for Semiactive Vehicle Suspension

Aiming at demonstrating the feasibility and capability of applying magnetorheological (MR) dampers to the vehicle vibration control, the hyperbolic tangent model is established to characterize the performance of a shear-valve mode MR damper that was developed for a vehicle suspension system in this study. An experimentally derived differential evolution (DE) algorithm is used to find the optimal parameters of the model. To demonstrate the effectiveness of the MR damper for semiactive suspension systems, a model was constructed of a quarter-car suspension system with the damper. A fuzzy control algorithm with a correction factor was adopted to control the output force of the damper and obtain better overall control of the performance of the suspension system. Simulation results indicate that the improved fuzzy control algorithm provides a better ride comfort than normal fuzzy control and passive control. Furthermore, the semiactive suspension system displayed effectively vibration suppression thanks to the MR damper combined with corresponding control algorithms.