This paper provides an overview of the latest advances in road vehicle suspension design, dynamics, and control, together with the authors' perspectives, in the context of vehicle ride, handling and stability. The general aspects of road vehicle suspension dynamics and design are discussed, followed by descriptions of road roughness excitations with a particular emphasis on road potholes. Passive suspension system designs and their effects on road vehicle dynamics and stability are presented in terms of in-plane and full-vehicle arrangements. Controlled suspensions are also reviewed and discussed. The paper concludes with some potential research topics, in particular those associated with development of hybrid and electric vehicles.

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This paper presents two alternative implementations of skyhook control, named “skyhook function” and “no-jerk skyhook,” for reducing the dynamic jerk that is often experienced with conventional skyhook control in semiactive suspension systems. An analysis of the relationship between the absolute velocity of the sprung mass and the relative velocity across the suspension are used to show the damping-force discontinuities that result from the conventional implementation of skyhook control. This analysis shows that at zero crossings of the relative velocity, conventional skyhook introduces a sharp increase (jump) in damping force, which, in turn, causes a jump in sprung-mass acceleration. This acceleration jump, or jerk, causes a significant reduction in isolation benefits that can be offered by skyhook suspensions. The alternative implementations of skyhook control included in this study offer modifications to the formulation of conventional skyhook control such that the damping force jumps are eliminated. The alternative policies are compared to the conventional skyhook control in the laboratory, using a base-excited semiactive system that includes a heavy-truck seat suspension. An evaluation of the damping force, seat acceleration, and the electrical currents supplied to a magnetorheological damper, which is used for this study, shows that the alternative implementations of skyhook control can entirely eliminate the damping-force discontinuities and the resulting dynamic jerks caused by conventional skyhook control.

In this paper, we will present a nonlinear-model-based adaptive semiactive control algorithm developed for magnetorheological (MR) suspension systems exposed to broadband nonstationary random vibration sources that are assumed to be unknown or not measurable. If there exist unknown and∕or varying parameters of the dynamic system such as mass and stiffness, then the adaptive algorithm can include on-line system identification such as a recursive least-squares method. Based on a nonparametric MR damper model, the adaptive system stability is proved by converting the hysteresis inherent with MR dampers to a memoryless nonlinearity with sector conditions. The convergence of the adaptive system, however, is investigated through a linearization approach including further numerical illustration of specific cases. Finally the simulation results for a magnetorheological seat suspension system with the suggested adaptive control are presented. The results are compared with low-damping and high-damping cases, and such comparison further shows the effectiveness of the proposed nonlinear model-based adaptive control algorithm for damping tuning.

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This article studies the application of nonparametric modeling approach to model magnetorheological (MR) dampers. For comparison purposes, another typical parametric modeling method for electrorheological (ER) and MR dampers is reviewed. The existing parametric MR damper model includes a stiff Bouc-Wen model that is not friendly for simulation study and real time implementation of model-based advanced control algorithms. In order to avoid the difficulties by using the existing parametric model, the test data from a commercialized MR damper is employed to develop nonparametric models, which can consist of a series of numerically efficient mathematic functions. In addition, the selected functions are required to be continuous and differentiable for potential model-based control algorithms. The results of the nonparametric models show that such different models are comparable. Furthermore, one nonparametric model is selected to be compared with a parametric model and the test data to illustrate the accuracy of the model. The comparison shows that the proposed nonparametric models are able to accurately predict the damper force characteristics, damper bilinear behavior, hysteresis, and electromagnetic saturation. It is further shown that the nonparametric models can be numerically solved with an integration step size of the order of 10 2 s, much faster than the parametric models of the order of 10 5 s, which clearly shows that the proposed nonparametric models are feasible even for real time model-based control algorithms.