Guido Koch

Potential of low bandwidth active suspension control with continuously variable damper

Due to rising customer demands for driving comfort, the integration of controlled active and semi-active elements in modern vehicle suspension systems has increased considerably. A significant number of upper class vehicle suspensions is either equipped with continuously variable dampers or low bandwidth actuators. However, the combination of these suspension elements is not applied so far. In this paper active quarter car models are used to design timeinvariant LQR controllers for specific road conditions. By optimizing the controller weights and damping ratio based on a new iterative optimization procedure, the potential of road adaptive low bandwidth systems with continuously variable dampers is clearly highlighted. It is shown that ride comfort can be significantly increased while satisfying given constraints for ride safety (maximum tire deflections) and suspension travel. The achievable performance is compared to passive and high bandwidth active suspension systems using carpet plots.

Nonlinear and filter based estimation for vehicle suspension control

The paper analyzes the performance of a new estimation method for vehicle suspensions, which incorporates three parallel Kalman filters and takes into account the nonlinear damper characteristic of the suspension. For the performance evaluation, an Extended Kalman filter (nonlinear estimator) is utilized as a benchmark. The estimator structures are tuned by means of a multiobjective genetic optimization algorithm in order to maximize their performance. The advantages of the parallel Kalman filter concept are its low computational effort and good estimation accuracy despite the presence of nonlinearities in the suspension setup. Both estimators are compared to a computationally simple concept that gains the estimates directly from measurement signals by conventional filtering techniques. The performance of the estimators is analyzed in simulations and experiments using a quarter-vehicle test rig and excitation signals gained from measurements of real road profiles.

Multi-Objective Road Adaptive Control of an Active Suspension System

In the design of automobile suspension systems, the classical conflict between minimizing vertical chassis acceleration to increase passenger comfort and keeping the dynamic wheel load small in order to ensure safe driveability must be further eased due to increasing customer demands. In order to moderate the conflicting suspension objectives, a switching controller structure for an active suspension system is developed which schedules linear optimal regulators depending on the present dynamic wheel load and suspension deflection. The goal is to maximize ride comfort while the wheel load is below certain safety critical bounds and the suspension deflection remains within given construction-conditioned limits. Stability of the switching control system is analyzed using a multiple Lyapunov function approach. The performance of the road adaptive suspension control system is compared with a linear controller and the passive suspension system in simulations to point out the benefits of the developed control concept.

A nonlinear estimator concept for active vehicle suspension control

A new Kalman filter based signal estimation concept for active vehicle suspension control is presented in this paper considering the nonlinear damper characteristic of a vehicle suspension setup. The application of a multi-objective genetic optimization algorithm for the tuning of the estimator shows that three parallel Kalman filters enhance the estimation performance for the variables of interest (states, dynamic wheel load and road profile). The Kalman filter structure is validated in simulations and on a testrig for an active suspension configuration using measurements of real road profiles as disturbance input. The advantages of the concept are its low computational effort compared to Extended or Unscented Kalman filters and its good estimation accuracy despite the presence of nonlinearities in the suspension setup.

Reference model based adaptive control of a hybrid suspension system

Abstract The paper presents a new adaptive controller structure for a hybrid quarter-vehicle suspension system containing a low bandwidth actuator and a semi-active damper. The optimal control force to ease the conflict between ride comfort, ride safety and limited suspension deflection is obtained from a reference model based on a passive suspension system with timevarying stiffness and damping. By allocating the resulting control force to the two actuators, the power demand of the hybrid suspension system is significantly lower compared to a high bandwidth active system although their performance is similar. Stability of the adaptive controller structure is guaranteed using a Lyapunov function approach. The hybrid suspension is compared with benchmark systems in simulations under realistic assumptions regarding nonlinearities of the suspension elements, the actuator and sensor architecture as well as the road profile.

Multi-objective preview control of active vehicle suspensions: Experimental results

This study concerns with the application of multi-objective H∞/GH2 preview control to a real quarter vehicle suspension system. To this goal both linear and nonlinear models of the test rig are derived, and a unified design framework for preview design schemes of LQG-preview and multi-objective preview is introduced. Simulations are carried out to compare both strategies. The study involves the inclusion of actuator dynamics in both analyses and syntheses. It also considers the effect of system nonlinearities in the analyses. Finally, it reports the practical implementation results.

Potential of Low Bandwidth Active Suspension Control with Continuously Variable Damper

In this paper, the performance potential of a new hardware combination for active suspension systems is presented. It consists of a low bandwidth actuator and a continuously variable damper, a setup that is shown to be competitive to high bandwidth active suspension systems especially if energy, cost and implementability aspects are taken into account. This is achieved by an iterative optimization procedure for the damping ratio and the weights of time-invariant LQR controllers for active quarter-car models. The results of the procedure are obtained by simulations employing a road disturbance model that is validated using measurements of a real highway profile. The achievable performance of the new hardware combination is compared to passive and high bandwidth active suspension systems by means of carpet plots. Based on the comparison results, it is shown that ride comfort can be significantly increased while satisfying given constraints for ride safety (maximum tire deflections) and suspension travel.

Physical Modeling of a Nonlinear Semi-Active Vehicle Damper

Abstract In this paper a physical model of a continuously variable semi-active dual-tube damper, which will be used for controller design for a mechatronic suspension system, is presented. The model of the passive damper is extended with an electro-/fluid-mechanical model, which captures the continuously variable damping effects by two independently adjustable electromagnetic valves. The unknown physical model parameters are estimated with a genetic algorithm and a gradient-based optimization method to match measurement data. The fluid-dynamic effects are derived from the compressibility of the oil, geometry and the adiabatic compression of the gas. The electrical model of the dampers power unit also incorporates an internal current controller. The validity of the semi-active model is demonstrated for different currents by comparing the simulation results with measurement data from a test rig.

A dynamic feedforward control approach for a semi-active damper based on a new hysteresis model

Abstract In this paper a dynamic feedforward control approach for a continuously variable hydraulic semi-active damper of a vehicle suspension is presented. It takes into account dynamic effects in the damper force generation by employing a new hysteresis model. The hysteresis model describes the damper behavior considerably better than static characteristics do. The latter resemble the state of the art for the calculation of the control inputs of semi-active dampers in order to track reference forces from higher level suspension controllers. The low complexity of the hysteresis model enables its real time capability and thus the applicability of the damper control approach. The performance of the concept is validated in experiments on a quarter-car test rig by comparing the dynamic control approach with the static characteristic based control using a skyhook controller and a linear optimal regulator. The new dynamic feedforward controller especially improves ride safety by enabling better force tracking in the range of the wheel resonance frequency.

Modified optimal control of a nonlinear active suspension system

In this paper a new control approach for active vehicle suspensions based on a modified optimal control problem is presented, which considers the nonlinear damper characteristic of a vehicle suspension setup. In this context a new method for the systematic construction of a control Lyapunov function is presented, that is applicable to a class of nonlinear systems. The states that are required by the controller are estimated from the available measurement signals using a nonlinear Kalman filter concept recently presented by the authors. In order to achieve the best possible performance with respect to the conflicting objectives passenger comfort, ride safety and suspension deflection, the controller parameters are determined by means of a multiobjective genetic optimization algorithm. The potential of the controller is demonstrated by comparing it to a conventional linear quadratic regulator. The concept is validated on a quarter-vehicle test rig using measurements of real road profiles as disturbance input.