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

State of the art of control schemes for smart systems featuring magneto-rheological materials

This review presents various control strategies for application systems utilizing smart magneto-rheological fluid (MRF) and magneto-rheological elastomers (MRE). It is well known that both MRF and MRE are actively studied and applied to many practical systems such as vehicle dampers. The mandatory requirements for successful applications of MRF and MRE include several factors: advanced material properties, optimal mechanisms, suitable modeling, and appropriate control schemes. Among these requirements, the use of an appropriate control scheme is a crucial factor since it is the final action stage of the application systems to achieve the desired output responses. There are numerous different control strategies which have been applied to many different application systems of MRF and MRE, summarized in this review. In the literature review, advantages and disadvantages of each control scheme are discussed so that potential researchers can develop more effective strategies to achieve higher control performance of many application systems utilizing magneto-rheological materials

Advanced suspension system using magnetorheological technology for vehicle vibration control

In the past forty years, the concept of controllable vehicle suspension has attracted extensive attention. Since high price of an active suspension system and deficiencies on a passive suspension, researchers pay a lot attention to semi-active suspension. Magneto-rheological fluid (MRF) is always an ideal material of semi-active structure. Thanks to its outstanding features like large yield stress, fast response time, low energy consumption and significant rheological effect. MR damper gradually becomes a preferred component of semi-active suspension for improving the riding performance of vehicle. However, because of the inherent nonlinear nature of MR damper, one of the challenging aspects of utilizing MR dampers to achieve high levels of performance is the development of an appropriate control strategy that can take advantage of the unique characteristics of MR dampers. This is why this project has studied semi-active MR control technology of vehicle suspensions to improve their performance. Focusing on MR semi-active suspension, the aim of this thesis sought to develop system structure and semi-active control strategy to give a vehicle opportunity to have a better performance on riding comfort. The issues of vibration control of the vehicle suspension were systematically analysed in this project. As a part of this research, a quarter-car test rig was built; the models of suspension and MR damper were established; the optimization work of mechanical structure and controller parameters was conducted to further improve the system performance; an optimized MR damper (OMRD) for a vehicle suspension was designed, fabricated, and tested. To utilize OMRD to achieve higher level of performance, an appropriate semi-active control algorithm, state observer-based Takagi-Sugeno fuzzy controller (SOTSFC), was designed for the semi-active suspension system, and its feasibility was verified through an experiment. Several tests were conducted on the quarter-car suspension to investigate the real effect of this semiactive control by changing suspension damping. In order to further enhance the vibration reduction performance of the vehicle, a fullsize variable stiffness and variable damping (VSVD) suspension was further designed, fabricated, and tested in this project. The suspension can be easily installed into a vehicle suspension system without any change to the original configuration. A new 3- degree of freedom (DOF) phenomenological model to further accurately describe the dynamic characteristic of the VSVD suspension was also presented. Based on a simple on-off controller, the performance of the variable stiffness and damping suspension was verified numerically. In addition, an innovative TS fuzzy modelling based VSVD controller was designed. The TS fuzzy modelling controller includes a skyhook damping control module and a state observer based stiffness control module which considering road dominant frequency in real-time. The performance evaluation of the VSVD control algorithm was based on the quarter-car test rig which equipping the VSVD suspension. The experiment results showed that this strategy increases riding comfort effectively, especially under off-road working condition. The semi-active control system developed in this thesis can be adapted and used on a vehicle suspension in order to better control vibration

Modelling and control of semi active suspension system incorporating magnetorheological damper for generic vehicle

This study presents the simulation and experimental works for Magnetorheological (MR) semi active suspension system in generic vehicles. In simulation study, a seven degree of freedom (7-DOF) vehicle model was developed using MATLAB-Simulink and verified using TruckSim. A semi active controller with road friendliness oriented was developed to reduce vehicle tire force; besides, ride comfort becomes the secondary objective of the proposed controller. The proposed semi active controllers which are Tire Force Control (TFC), Aided Tire Force Control (ATFC) and ground Semi Active Damping Force Estimator (gSADE) and simulation results were compared with existing controller known as Groundhook (GRD) and passive suspension system. Then, these controllers were applied experimentally using generic quarter vehicle model. The overall results showed gSADE is the most effective controller in reducing vehicle tire force and improving ride comfort. Both reduction of gSADE vehicle tire force and ride comfort compared with passive system are similar about 14.2%. In the simulation study, ideal and real cases (using MR damper model) were conducted. In the ideal case, two bump profiles were used to test the effectiveness of the controller and the results showed gSADE recorded the highest improvement of the tire force followed by ATFC, TFC, GRD and passive system. The maximum improvement of gSADE control compared with passive system is about 21% in reduction of tire force and 22% in improving ride comfort. A similar test was conducted using MR damper model, and the overall result showed gSADE recorded almost similar improvement of the tire force compared with TFC. The maximum reduction of vehicle tire force and improvement of ride comfort using gSADE control compared with passive are 15% and 30%, respectively

Feasibility of Using Nonlinear Time-Frequency Control for Magnetorheological Dampers in Vehicle Suspension

Semi-active vehicle suspensions that use magnetorheological (MR) dampers are able to better dissipate vibrations compared to conventional dampers because of their controllable damping characteristics. The performance of current MR damper control methods is often hindered by incorrect assumptions and linearized models. Therefore, a need exists to design an adaptive controller with improved accuracy and reliability. The objective of this research is to design an improved controller for MR dampers in vehicle suspension using the nonlinear time-frequency control approach and evaluate its feasibility by numerically employing MATLAB Simulink. Simulations in this research are performed using a simplified quarter car suspension model and modified Bouc-Wen damper model. The proposed control method is evaluated based on its ability to reduce the amplitude of vibrations and minimize acceleration of the car body for various test cases. Simulations are also performed using the skyhook controller and passive suspension to assess the performance of the proposed controller. The results of the simulations show that the proposed nonlinear time-frequency controller can successfully be applied to an MR damper suspensions system for vibration control. The proposed controller outperforms the skyhook controller in terms of reducing acceleration of the car body in each of the tested scenarios. The proposed controller also shows the ability to more efficiently manage the current input to the system. In general, the skyhook controller gives more improved vibration amplitude responses but is prone to generate large spikes in car body acceleration at higher frequency road profile inputs. Simulations performed with the passive system show large displacement amplitudes and inability to prevent oscillation. The feed-forward aspect and adaptive nature of the proposed controller gives it the ability to better compensate for the time-delay in the operation of the MR damper. The proposed controller shows sensitivity to controller parameters when pursuing the best response for different road profile input cases

Intelligent controllers for vechicle suspension system using magnetorheological damper

Semi-active suspension control with magnetorheological (MR) damper is one of the most fascinating systems being studied in improving the vehicle ride comfort. This study aims to investigate the development of intelligent controllers for vehicle suspension system using MR damper, namely, the proportional-integral-derivative (PID) and fuzzy logic (FL) controllers optimized using particle swarm optimization (PSO), firefly algorithm (FA) and advanced firefly algorithm (AFA). Since the conventional optimization method always has a problem in identifying the optimum values and it is time consuming, the evolutionary algorithm is the best approach in replacing the conventional method as it is very efficient and consistent in exploring the values for every single space. The PSO and FA are among of the evolutionary algorithms which have been studied in this research. Nevertheless, the weakness of FA such as getting trapped into several local minima is an attractive area that has been focused more as a possible improvement during the evolutionary process. Thus, a new algorithm based on the improvement of the original FA was introduced to improve the solution quality of the FA. This algorithm is called advanced firefly algorithm. A parametric modelling technique known as Spencer model was proposed and employed to compute the dynamic behaviour of the MR damper system. The Spencer model was experimentally validated and conducted to capture the behaviour of the Lord RD-1005-3 MR damper with the same excitation input. A simulation of a semi-active suspension system was developed within MATLAB Simulink environment. The effectiveness of all control schemes were investigated in two major issues, namely the ability of the controller to reject the unwanted motion of the vehicle and to overcome the damping constraints. The result indicates that, the PID-AFA control scheme is more superior as compared to the PID-PSO, PID-FA, FL-PSO, FL-FA, FL-AFA and passive system with up to 27.1% and 19.1% reduction for sprung mass acceleration and sprung mass displacement, respectively. Finally, the performance of the proposed intelligent control schemes which are implemented experimentally on the developed quarter vehicle suspension test rig shows a good agreement with the results of the simulation study. The proposed control scheme of PID-AFA has reduced the sprung mass acceleration and sprung mass displacement over the FL-AFA and passive system up to 28.21% and 16.9%, respectively

Feasibility of Using Nonlinear Time-Frequency Control for Magnetorheological Dampers in Vehicle Suspension

Semi-active vehicle suspensions that use magnetorheological (MR) dampers are able to better dissipate vibrations compared to conventional dampers because of their controllable damping characteristics. The performance of current MR damper control methods is often hindered by incorrect assumptions and linearized models. Therefore, a need exists to design an adaptive controller with improved accuracy and reliability. The objective of this research is to design an improved controller for MR dampers in vehicle suspension using the nonlinear time-frequency control approach and evaluate its feasibility by numerically employing MATLAB Simulink. Simulations in this research are performed using a simplified quarter car suspension model and modified Bouc-Wen damper model. The proposed control method is evaluated based on its ability to reduce the amplitude of vibrations and minimize acceleration of the car body for various test cases. Simulations are also performed using the skyhook controller and passive suspension to assess the performance of the proposed controller. The results of the simulations show that the proposed nonlinear time-frequency controller can successfully be applied to an MR damper suspensions system for vibration control. The proposed controller outperforms the skyhook controller in terms of reducing acceleration of the car body in each of the tested scenarios. The proposed controller also shows the ability to more efficiently manage the current input to the system. In general, the skyhook controller gives more improved vibration amplitude responses but is prone to generate large spikes in car body acceleration at higher frequency road profile inputs. Simulations performed with the passive system show large displacement amplitudes and inability to prevent oscillation. The feed-forward aspect and adaptive nature of the proposed controller gives it the ability to better compensate for the time-delay in the operation of the MR damper. The proposed controller shows sensitivity to controller parameters when pursuing the best response for different road profile input cases

Optimal vibration control of beams with total and partial MR-fluid treatments

This paper presents the synthesis of full state and limited state flexible mode shape (FMS) based controllers for the suppression of transient and forced vibration of a cantilever beam with full and partial magnetorheological (MR) fluid treatments. The governing equations of motion of the three layer MR sandwich beam are expressed in the state variable form comprising a function of the control magnetic field. An optimal control strategy based on the linear quadratic regulator (LQR) and a full state dynamic observer is formulated to suppress the vibration of the beam under limited magnetic field intensity. The lower flexural mode shapes of the passive beam are used to obtain estimates of the deflection states so as to formulate a limited state LQR control synthesis. The transient and forced vibration control performances of both the full state observer-based and the limited state FMS-based LQR control strategies are evaluated for the fully as well as partially treated MR-fluid sandwich beams. The results show that the full state observer-based LQR control can substantially reduce the tip deflection responses and the settling time of free vibration oscillations. The limited state LQR control based on the mode shapes effectively adapts to the deflections of the closed loop beam and thus yields vibration attenuation performance comparable to that of the full state LQR controller. The partially treated beam with MR-fluid concentration near the free end also yields vibration responses comparable to the fully treated beam, while the natural frequencies of the partially treated beams are considerably higher

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