Preview-based techniques for vehicle suspension control: a state-of-the-art review

Abstract Automotive suspension systems are key to ride comfort and handling performance enhancement. In the last decades semi-active and active suspension configurations have been the focus of intensive automotive engineering research, and have been implemented by the industry. The recent advances in road profile measurement and estimation systems make road-preview-based suspension control a viable solution for production vehicles. Despite the availability of a significant body of papers on the topic, the literature lacks a comprehensive and up-to-date survey on the variety of proposed techniques for suspension control with road preview, and the comparison of their effectiveness. To cover the gap, this literature review deals with the research conducted over the past decades on the topic of semi-active and active suspension controllers with road preview. The main formulations are reported for each control category, and the respective features are critically analysed, together with the most relevant performance indicators. The paper also discusses the effect of the road preview time on the resulting system performance, and identifies control development trends

Active suspension control of electric vehicle with in-wheel motors

In-wheel motor (IWM) technology has attracted increasing research interests in recent years due to the numerous advantages it offers. However, the direct attachment of IWMs to the wheels can result in an increase in the vehicle unsprung mass and a significant drop in the suspension ride comfort performance and road holding stability. Other issues such as motor bearing wear motor vibration, air-gap eccentricity and residual unbalanced radial force can adversely influence the motor vibration, passenger comfort and vehicle rollover stability. Active suspension and optimized passive suspension are possible methods deployed to improve the ride comfort and safety of electric vehicles equipped with inwheel motor. The trade-off between ride comfort and handling stability is a major challenge in active suspension design. This thesis investigates the development of novel active suspension systems for successful implementation of IWM technology in electric cars. Towards such aim, several active suspension methods based on robust H∞ control methods are developed to achieve enhanced suspension performance by overcoming the conflicting requirement between ride comfort, suspension deflection and road holding. A novel fault-tolerant H∞ controller based on friction compensation is in the presence of system parameter uncertainties, actuator faults, as well as actuator time delay and system friction is proposed. A friction observer-based Takagi-Sugeno (T-S) fuzzy H∞ controller is developed for active suspension with sprung mass variation and system friction. This method is validated experimentally on a quarter car test rig. The experimental results demonstrate the effectiveness of proposed control methods in improving vehicle ride performance and road holding capability under different road profiles. Quarter car suspension model with suspended shaft-less direct-drive motors has the potential to improve the road holding capability and ride performance. Based on the quarter car suspension with dynamic vibration absorber (DVA) model, a multi-objective parameter optimization for active suspension of IWM mounted electric vehicle based on genetic algorithm (GA) is proposed to suppress the sprung mass vibration, motor vibration, motor bearing wear as well as improving ride comfort, suspension deflection and road holding stability. Then a fault-tolerant fuzzy H∞ control design approach for active suspension of IWM driven electric vehicles in the presence of sprung mass variation, actuator faults and control input constraints is proposed. The T-S fuzzy suspension model is used to cope with the possible sprung mass variation. The output feedback control problem for active suspension system of IWM driven electric vehicles with actuator faults and time delay is further investigated. The suspended motor parameters and vehicle suspension parameters are optimized based on the particle swarm optimization. A robust output feedback H∞ controller is designed to guarantee the system’s asymptotic stability and simultaneously satisfying the performance constraints. The proposed output feedback controller reveals much better performance than previous work when different actuator thrust losses and time delay occurs. The road surface roughness is coupled with in-wheel switched reluctance motor air-gap eccentricity and the unbalanced residual vertical force. Coupling effects between road excitation and in wheel switched reluctance motor (SRM) on electric vehicle ride comfort are also analysed in this thesis. A hybrid control method including output feedback controller and SRM controller are designed to suppress SRM vibration and to prolong the SRM lifespan, while at the same time improving vehicle ride comfort. Then a state feedback H∞ controller combined with SRM controller is designed for in-wheel SRM driven electric vehicle with DVA structure to enhance vehicle and SRM performance. Simulation results demonstrate the effectiveness of DVA structure based active suspension system with proposed control method its ability to significantly improve the road holding capability and ride performance, as well as motor performance

Use of numerical optimisation to determine on-limit handling behaviour of race cars.

The aim of this research is to use numerical optimisation to investigate the on-limit behaviour of an open wheel downforce type race car using the best compromise of modelling accuracy and computational effort. The current state of lap simulation methods are identified, and the GG speed diagram is described. The use of constrained optimisation, which is a form of optimal control, is used to develop the methods described in this thesis. A seven degree of freedom vehicle model validated by other researchers is used for method validation purposes, and is extended, where possible, to make the modelling of vehicle components more physically significant, without adversely affecting the computational time. This research suggests a quasi steady state approach that produces a GG speed diagram and circuit simulation tool that is capable of optimising vehicle parameters and subsystems in addition to the prevailing control vector of steer and throttle response. The use of numerical optimisation to optimise the rear differential hydraulic pressure and the roll stiffness distribution to maximise vehicle performance is demonstrated. The optimisation of the rear differential hydraulic pressure showed a very small improvement in vehicle performance in combined high speed braking and cornering, but highlighted the ability of the differential to affect the cornering behaviour of the vehicle. The optimisation of the roll stiffness distribution research showed that a significant improvement in the lateral acceleration capability of the vehicle could be achieved at all vehicle speeds between 20 and 80m/s, especially in combined braking and cornering. In addition, a parameter sensitivity study around a realistic Formula One vehicle setup was conducted, looking at the sensitivity of vehicle mass, yaw inertia, tyres, centre of gravity location and engine torque to vehicle performance. An investigation into the importance of the path finding calculation is also reported

Design of Robust Digital Pole Placer for Car Active Suspension with Input Constraint

This chapter deals with the problem of state feedback control for an active quarter-car suspension system with control input constraint. The dynamics of the suspension system is first formed in terms of the control objectives: ride comfort, suspension deflection, and maximum actuator control force. The control task is formulated as robustly placing the closed poles in a desired region against different passenger load. Since digital computers are widely used in the vehicle industry, a new saturated controller design method is presented for regional pole-placement of uncertain discrete time systems. The constraint of control input saturation is considered in the design phase. The desired dynamic performance for uncertain discrete-time systems is represented by the settling time and damping ratio. A sufficient condition is derived to place the poles in a desired region. The design is formulated in terms of linear matrix inequality optimization. The effectiveness of the proposed design is illustrated by applying it to a quarter?car active suspension system. Different road tests for the proposed controller are carried out: step and bump disturbances. The proposed design achieves the desired oscillation damping due to road disturbances in addition to passenger comfort. The results are compared with the passive suspension system

Convolution based real-time control strategy for vehicle active suspension systems

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.A novel real-time control method that minimises linear system vibrations when it is subjected to an arbitrary external excitation is proposed in this study. The work deals with a discrete differential dynamic programming type of problem, in which an external disturbance is controlled over a time horizon by a control force strategy constituted by the well-known convolution approach. The proposed method states that if a control strategy can be established to restore an impulse external disturbance, then the convolution concept can be used to generate an overall control strategy to control the system response when it is subjected to an arbitrary external disturbance. The arbitrary disturbance is divided into impulses and by simply scaling, shifting and summation of the obtained control strategy against the impulse input for each impulse of the arbitrary disturbance, the overall control strategy will be established. Genetic Algorithm was adopted to obtain an optimal control force plan to suppress the system vibrations when it is subjected to a shock disturbance, and then the Convolution concept was used to enable the system response to be controlled in real-time using the obtained control strategy. Numerical tests were carried out on a two-degree of freedom quarter-vehicle active suspension model and the results were compared with results generated using the Linear Quadratic Regulator (LQR) method. The method was also applied to control the vibration of a seven-degree of freedom full-vehicle active suspension model. In addition, the effect of a time delay on the performance of the proposed approach was also studied. To demonstrate the applicability of the proposed method in real-time control, experimental tests were performed on a quarter-vehicle test rig equipped with a pneumatic active suspension. Numerical and experimental results showed the effectiveness of the proposed method in reducing the vehicle vibrations. One of the main contributions of this work besides using the Convolution concept to provide a real time control strategy is the reduction in the number of sensors needed to construct the proposed method as the disturbance amplitude is the only parameter needed to be measured (known). Finally, having achieved what has been proposed above, a generic robust control method is accomplished, which not only can be applied for active suspension systems but also in many other fields

Advanced robust control strategies of mechatronic suspensions for cars

Two novel mechatronic suspensions for road vehicles are studied in this thesis: the Series Active Variable Geometry Suspension (SAVGS) and the Parallel Active Link Suspension (PALS). The SAVGS and the PALS complement each other in terms of the vehicle categories they serve, which range from light high-performance vehicles (the Grand Tourer) to heavy SUV vehicles, respectively, based on the sprung mass and the passive suspension stiffness. Previous work developed various control methodologies for these types of suspension. Compared to existing active suspension solutions, both the SAVGS and the PALS are capable of low-frequency chassis attitude control and high-frequency ride comfort and road holding enhancement. In order to solve the limitation of both SAVGS and PALS robustness, mu-synthesis control methodologies are first developed for SAVGS and PALS, respectively, to account for structured uncertainties arising from changes to system parameters within realistic operating ranges. Subsequently, to guarantee robustness of both low-frequency and high-frequency vehicle dynamics for PALS, the mu-synthesis scheme is combined with proportional-integral-derivative (PID) control, employing a frequency separation paradigm. Moreover, as an alternative robustness guaranteeing scheme that captures plant nonlinearities and road unevenness as uncertainties and disturbances, a novel robust model predictive control (RMPC) based methodology is proposed for the SAVGS, motivated by the promise shown by RMPC in other industrial applications. Finally, aiming to provide further performance stability and improvements, feedforward control is developed for the PALS. Nonlinear simulations with a set of ISO driving situations are performed to evaluate the efficiency and effectiveness of the proposed control methods in this thesis.Open Acces

Control and Evaluation of Slow-Active Suspensions with Preview for a Full Car

An optimal control design method based on the use of the correlation between the front and rear wheel inputs (wheelbase preview) is introduced and then applied to the optimum design of a slow-active suspension system. The suspension consists of a limited bandwidth actuator in series with a passive spring, the combination being in parallel with a passive damper. A three-dimensional seven degrees of freedom car riding model subjected to four correlated random road inputs is considered. The performance potential of the limited bandwidth system with wheelbase preview in comparison with the nonpreview (uncorrelated inputs) case is investigated