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

Series active variable geometry suspension application to comfort enhancement

This paper explores the potential of the Series Active Variable Geometry Suspension (SAVGS) for comfort and road holding enhancement. The SAVGS concept introduces significant nonlinearities associated with the rotation of the mechanical link that connects the chassis to the spring-damper unit. Although conventional linearization procedures implemented in multi-body software packages can deal with this configuration, they produce linear models of reduced applicability. To overcome this limitation, an alternative linearization approach based on energy conservation principles is proposed and successfully applied to one corner of the car, thus enabling the use of linear robust control techniques. An H∞ controller is synthesized for this simplified quarter-car linear model and tuned based on the singular value decomposition of the system's transfer matrix. The proposed control is thoroughly tested with one-corner and full-vehicle nonlinear multi-body models. In the SAVGS setup, the actuator appears in series with the passive spring-damper and therefore it would typically be categorized as a low bandwidth or slow active suspension. However, results presented in this paper for an SAVGS-retrofitted Grand Tourer show that this technology has the potential to also improve the high frequency suspension functions such as comfort and road holding

Hardware-in-the-loop simulation of magnetorheological dampers for vehicle suspension systems

Magnetorheological (MR) fluids provide an elegant means to enhance vibration control in primary vehicle suspensions. Such fluids can rapidly modify their flow characteristics in response to a magnetic field, so they can be used to create semi-active dampers. However, the behaviour of MR dampers is inherently non-linear and as a consequence, the choice of an effective control strategy remains an unresolved problem. Previous research has developed a method to linearize the damper's force/velocity response, to allow implementation of classical control techniques. In the present study, this strategy is used to implement skyhook damping laws within primary automotive suspensions. To simulate the vehicle suspension, a two-degree-of-freedom quarter car model is used, which is excited by realistic road profiles. The controller performance is investigated experimentally using the hardware-in-the-loop-simulation (HILS) method. This experimental method is described in detail and its performance is validated against numerical simulations for a simplified problem. The present authors demonstrate that feedback linearization can provide significant performance enhancements in terms of passenger comfort, road holding, and suspension working space compared with other control strategies. Furthermore, feedback linearization is shown to desensitize the controller to uncertainties in the input excitation such as changes in severity of the road surface roughness

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

Discrete optimal actuator-fault-tolerant control for vehicle active suspension

This paper studies the discrete actuator-fault-tolerant control problem for a vehicle active suspension system under persistent road disturbances. The discrete model of vehicle active suspension with actuator faults is formulated firstly, in which the actuator faults are described as the output of an exogenous system with unknown initial values. By designed a fault diagnoser, the optimal actuator-fault-tolerant controller is derived from the discrete Riccati equation and Stein equations, respectively. Simulation results illustrate that the ride comfort, road holding ability, and suspension deflection can be reduced significantly and the reliability of the vehicle active suspension can be improved

Parallel active link suspension: full car application with frequency-dependent multi-objective control strategies

In this article, a recently proposed at basic level novel suspension for road vehicles, the parallel active link suspension (PALS), is investigated in the realistic scenario of a sport utility vehicle (SUV) full car. The involved rocker-pushrod assembly is generally optimized to maximize the PALS capability in improving the suspension performance. To fully release the PALS functions of dealing with both low- and high-frequency road cases, a PID control scheme is first employed for the chassis attitude stabilization, focusing on the minimization of both the roll and pitch angles; based on a derived linear equivalent model of the PALS-retrofitted full car, an H∞ control scheme is designed to enhance the ride comfort and road holding; moreover, a frequency-dependent multiobjective control strategy that combines the developed PID and H∞ control is proposed to enable: 1) chassis attitude stabilization at 0-1 Hz; 2) vehicle vibration attenuation at 1-8 Hz; and 3) control effort penalization (for energy saving) above 10 Hz. With a group of ISO-defined road events tested, numerical simulation results demonstrate that, compared to the conventional passive suspension, the PALS has a promising potential in full-car application, with up to 70% reduction of the chassis vertical acceleration in speed bumps and chassis leveling capability of dealing with up to 4.3-m/s² lateral acceleration

Optimal design of a quadratic parameter varying vehicle suspension system using contrast-based Fruit Fly Optimisation

In the UK, in 2014 almost fifty thousand motorists made claims about vehicle damages caused by potholes. Pothole damage mitigation has become so important that a number of car manufacturers have officially designated it as one of their priorities. The objective is to improve suspension shock performance without degrading road holding and ride comfort. In this study, it is shown that significant improvement in performance is achieved if a clipped quadratic parameter varying suspension is employed. Optimal design of the proposed system is challenging because of the multiple local minima causing global optimisation algorithms to get trapped at local minima, located far from the optimum solution. To this end an enhanced Fruit Fly Optimisation Algorithm − based on a recent study on how well a fruit fly’s tiny brain finds food − was developed. The new algorithm is first evaluated using standard and nonstandard benchmark tests and then applied to the computationally expensive suspension design problem. The proposed algorithm is simple to use, robust and well suited for the solution of highly nonlinear problems. For the suspension design problem new insight is gained, leading to optimum damping profiles as a function of excitation level and rattle space velocity

Proportional-integral state-feedback controller optimization for a full-car active suspension setup using a genetic algorithm

The use of active car suspensions to maximize driver comfort has been of growing interest in the last decades. Various active car suspension control technologies have been developed. In this work, an optimal control for a full-car electromechanical active suspension is presented. Therefore, a scaled-down lab setup model of this full-car active suspension is established, capable of emulating a car driving over a road surface with a much simpler approach in comparison with a classical full-car setup. A kinematic analysis is performed to assure system behaviour which matches typical full-car dynamics. A state-space model is deducted, in order to accurately simulate the behaviour of a car driving over an actual road prole, in agreement with the ISO 8608 norm. The active suspension control makes use of a Multiple-Input-Multiple- Output (MIMO) state-feedback controller with proportional and integral actions. The optimal controller tuning parameters are determined using a Genetic Algorithm, with respect to actuator constraints and without the need of any further manual fine-tuning

Passive fault-tolerant control for vehicle active suspension system based on H2/H∞ approach

In this paper, a robust passive fault-tolerant control (RPFTC) strategy based on H2/H∞ approach and an integral sliding mode passive fault tolerant control (ISMPFTC) strategy based on H2/H∞ approach for vehicle active suspension are presented with considering model uncertainties, loss of actuator effectiveness and time-domain hard constraints of the suspension system. H∞ performance index less than γ and H2 performance index is minimized as the design objective, avoid choosing weighting coefficient. The half-car model is taken as an example, the robust passive fault-tolerant controller and the integral sliding mode passive fault tolerant control law is designed respectively. Three different fault modes are selected. And then compare and analyze the control effect of vertical acceleration of the vehicle body and pitch angular acceleration of passive suspension control, robust passive fault tolerant control and integral sliding mode passive fault tolerant control to verify the feasibility and effectiveness of passive fault tolerant control algorithm of active suspension. The studies we have performed indicated that the passive fault tolerant control strategy of the active suspension can improve the ride comfort of the suspension system