Magnetorheological Damper Research Articles

Performance Characteristics of a Compact Core Annular-Radial Magnetorheological Damper for Vehicle Suspension Systems

The magnetorheological (MR) damper is a by-wire system capable of providing variable damping stiffness by responding to an apparent magnetic field. In response to the magnetic field application, the magnetorheological fluid (MR fluid) exhibited altered behavior within the damper. Typically, a damper’s internal and external valves operate in flow mode, where the flow is regulated by controlling the magnetic field. This study aims to investigate the performance characteristics of a small core annular and radial magnetorheological valve (SCARMV) designed for applications in vehicle suspension systems. The proposed design of the simplified MR valve is based on a meandering-type valve composed of multiple valve cores that have been simplified to a single core. Dynamic testing was performed on the proposed valve, which features a single rod tube damper, to investigate the damping force characteristics by varying currents and frequencies. The characteristics of the measured damping force were compared to the calculated damping force based on the pressure drop calculation and the FEMM simulation of magnetic flux. By increasing the stroke length of the valve travel is set to 10 mm at a current input of 0 A to 1.0 A, the maximum output of the MR valve damping force was approximately 1.57 kN. In addition, a mathematical model of SCARMV is presented and compared to the experimental data. Therefore, based on the experimental results, it was concluded that the usability of a compact core MR valve is reliable. However, more in-depth studies are required before these dampers can be applied to vehicle suspension systems.

Novel approaches in developing sustainable and cost-effective semi-active suspension systems for smart vehicles—A review

The dynamic evolution of automotive technology necessitates integrating intelligent systems in suspension systems to enhance vehicle dynamic performance and environmental sustainability. The major challenge in the vehicle suspension design is to achieve an optimum tradeoff between riding comfort and ground holding with the available rattle space. Semi-active suspension systems (SASSs), which meet these requirements more effectively than passive and active systems, have gained prominence for their potential. Different SA control strategies and dampers have been developed to enhance dynamic performance. The optimal control strategies and design parameters improve the responsiveness of SASSs in the vehicle dynamic performance. The algorithms attempt to avail the full potential of various dampers controlled electronically. The accurate representation of nonlinearities in mathematical modeling with noise mitigation enhances the practical implementation of novel controllers in SASSs. This review investigates the forefront of research and development in SASSs, focusing on innovative strategies to make these systems more sustainable, adaptive, and cost-effective for smart vehicles. Semi-active magnetorheological dampers have more commercial applications than other dampers, but the high cost makes them unaffordable for economical cars. Several researchers have attempted to develop inexpensive, high-performance dampers that can vary damping coefficients precisely for different road conditions. Real-time energy harvesting-based dampers for sustainable electric mobility are under development. Commercially available SASSs are less expensive than active suspensions but they have limited applications than passive suspensions. The low market share of existing SASSs and their regenerative inability are the major drawbacks in making it a sustainable suspension system. The novel strategies attempted to develop an effective smart suspension system and its limitations are discussed in this review. The next generation of SASSs that aligns with the global drive towards smarter, greener, and economical vehicles is identified.

Robust Static Output Feedback Control of a Semi-Active Vehicle Suspension Based on Magnetorheological Dampers

This paper proposes a novel design method for a magnetorheological (MR) damper-based semi-active suspension system. An improved MR damper model that accurately describes the hysteretic nature and effect of the applied current is presented. Given the unfeasibility of installing sensors for all vehicle states, an MR damper current controller that only considers the suspension deflection and deflection rate is proposed. A linear matrix inequality problem is formulated to design the current controller, with the objective of enhancing ride safety and comfort while guaranteeing vehicle stability and robustness against any road disturbance. A series of experiments demonstrates the enhanced performance of the proposed MR damper model, which exhibits greater accuracy than other state-of-the-art damper models, such as Bingham or bi-viscous. An evaluation of the vehicle behavior under two simulated road scenarios has been conducted to demonstrate the performance of the proposed output feedback MR damper-based semi-active suspension system.

Self-powered actively-controlled lateral suspensions of high-speed trains using energy-regenerative electromagnetic damper and model predictive control

Self-powered actively-controlled lateral suspensions of high-speed trains using energy-regenerative electromagnetic damper and model predictive control

Research on robust backstepping sliding mode control strategy for magnetorheological semi-active suspension based on quantized input signals

Research on robust backstepping sliding mode control strategy for magnetorheological semi-active suspension based on quantized input signals

Design, dynamic modeling and testing of a novel MR damper for cable-stayed climbing robots under wind loads

To increase the adaptability of bridge construction equipment in high-altitude settings, this study examines a magnetorheological (MR) damper designed for cable-stayed climbing robots. Initially, a novel damper incorporating a spring-MR fluid combination and three magnetic circuit units is developed. A robot-cable-wind coupling dynamic model is subsequently formulated via Hamilton’s principle, based on force analysis. The simulation results indicate that the damper’s maximum output force is 204.60 N, with optimal working currents of 0.2 A (Force 4) and 0.4 A (Force 7). To verify the analysis, testing is conducted using an MR damper. The results reveal an average relative error of 4.60% for the actual output damping force. When mounted on the robot, the climbing speed range, average relative error, and maximum relative error are controlled within 0.66 mm/s, 0.78% and 2.5%, respectively. This approach allows for the rapid selection of suitable working currents and markedly enhances the climbing stability of the robot.

Design and performance analysis of a vibration energy harvesting magnetorheological damper

Design and performance analysis of a vibration energy harvesting magnetorheological damper

Optimal replicator dynamic controller for semi active control of long span cable stayed bridge with considering special variability of seismic excitations

Cable-stayed bridges are lifeline infrastructures. However, due to their design and structural characteristics, they are sensitive to the vibrations. Thus, vibration control in these structures is essential. Semi-active control systems have gained significant attention due to their high performance and adaptability. However, the implementation of these systems has always faced serious challenges particularly when it comes to developing appropriate control algorithms because semi active devices have complex and non-linear characteristics. Inspired by evolutionary game theory, the author utilizes the replicator dynamic controller concept to optimize the performance of MR dampers to improve the vibration reduction of cable-stayed bridges. Two key parameters in the proposed control methodologies using replicator dynamics are the total population (total available resources or the sum of actuator forces) and the growth rate. Instead of using the sensitivity analysis that has been done in previous studies for vibration reduction of highway bridges using a replicator controller, the author used an evolutionary algorithm named the nondominated sorting genetic algorithm (NSGA-II) to create an optimal replicator dynamic controller for more effective vibration reduction. The proposed methodology is evaluated through its numerical application to a second-generation benchmark example based on the Bill Emerson Memorial Bridge, which considers a more realistic behavior of the cable-stayed bridge by accounting for multiple support excitations. The study indicates that the optimal replicator dynamic controller improves the vibration reduction performance of MR dampers. Specifically, deck displacement is reduced by 46 % compared to passive control system and shear forces at the tower base are reduced by 33 % compared to active control systems for the El Centro earthquake. The results indicate that the proposed Replicator Dynamic Controller optimized through NSGA-II provides a robust and effective solution for improving seismic resilience of cable-stayed bridges.

Comparative Study of Semi-Active Control Effectiveness of Structures on Soft Soil Using MR Damper: Shaking Table Investigation

The effect of soil-structure interaction (SSI) cannot be neglected in semi-active vibration control of structures located on soft soil. To investigate the mitigating effect of magnetorheological (MR) damper on the semi-active control of structures considering the SSI, shaking table tests were conducted to evaluate the performance of the MR damper-based semi-active control system for structures on soft soil. In addition to a novel fuzzy control method based on online learning deep neural network (OL-DFNN), various control strategies, including passive OFF, passive ON, ON–OFF and deep neural network fuzzy control (DFNN) were systematically evaluated. The test results showed that the OL-DFNN control method exhibited superior adaptability to varying ground motion and structural dynamic characteristics compared to the other control methods. In particular, the OL-DFNN controller effectively mitigated the peak displacement and root mean square displacement, outperforming the passive OFF, passive ON, ON–OFF and DFNN control strategies. The test results highlight the effectiveness of the OL-DFNN control method in addressing the challenges posed by dynamic and time-varying characteristics in structural vibration control systems considering SSI.

A Variable Horizon Model Predictive Control for Magnetorheological Semi-Active Suspension with Air Springs.

To improve the characteristics of traditional model predictive control (MPC) semi-active suspension that cannot achieve the optimal suspension control effect under different conditions, a variable horizon model predictive control (VHMPC) method is devised for magnetorheological semi-active suspension with air springs. Mathematical models are established for the magnetorheological dampers and air springs. Based on the improved hyperbolic tangent model, a forward model is established for the magnetorheological damper. The adaptive fuzzy neural network method is used to establish the inverse model of the magnetorheological damper. The relationship between different road excitation frequencies and the control effect of magnetorheological semi-active suspension with air springs is simulated, and the optimal prediction horizons under different conditions are obtained. The VHMPC method is designed to automatically switch the predictive horizon according to the road surface excitation frequency. The results demonstrate that under mixed conditions, compared with the traditional MPC, the VHMPC can improve the smoothness of the suspension by 2.614% and reduce the positive and negative peaks of the vertical vibration acceleration by 11.849% and 6.938%, respectively. Under variable speed road conditions, VHMPC improved the sprung mass acceleration, dynamic tire deformation, and suspension deflection by 7.191%, 7.936%, and 22.222%, respectively, compared to MPC.

Quasi-static modeling of a full-channel effective magnetorheological damper with shunt and bending magnetic circuit

Magnetorheological dampers (MRD) are widely used in vibration control due to their rapid response and adjustable damping forces. However, conventional MRD designs with closed rectangular magnetic circuits suffer from limited effective working lengths and inadequate damping force for vehicle suspensions. To address this, a novel full-channel effective MRD with shunt and bending magnetic circuit (FEMRD_SB) is proposed. This design increases the effective working length of the damping channel by incorporating a bending motion in the magnetic circuit. Magnetic circuit shunting is integrated to mitigate magnetic leakage during bending, improving energy utilization efficiency. To better meet the practical needs of vehicle suspension, a quasi-static mathematical model aiming to explain the mechanical properties of the damper is investigated. Traditional models often overlook the uneven distribution of magnetic fields, which leads to poor modeling accuracy. To improve the precision of the quasi-static model, a multiphysical field coupling quasi-static modeling method is proposed. This method, utilizing the Takagi–Sugeno fuzzy neural network establishes the relationship between magnetic field and displacement, facilitating the integration of magnetic, flow, and solid fields for more precise modeling outcomes. Simulations and experiments validate the effectiveness of the FEMRD_SB and the quasi-static model. The real-vehicle experiments demonstrate that the FEMRD_SB effectively suppresses the sprung mass acceleration of a vehicle, improving the vehicle’s ride comfort.

Evaluation of the seismic performance of a multi-coil MR damper using non-linear method

Magnetorheological dampers (MR) have the ability to provide high damping and subsequent energy dissipation which has a potential application in mitigation of natural hazard. These features of advanced damping technology achieved from the interaction between magnetic field induced MR fluid and the rod of piston. In this paper, hybrid simulation is evaluated for a Reinforced Concrete (RC) frame with MR Damper under various configuration subjected to dynamic loading is numerically investigated using OpenSees framework and validated experimentally. In OpenSees framework Bouc Wen Material parameters were incorporated by the experimental results of MR Damper. The response of the three RC frames, both numerically and the experimentally having diagonally attached MR damper at 0 A current, 3 A current and without MR damper, were compared for El-Centro excitation. In comparison of results, the specimen with MR Damper at 3 A current displays better performance. Maximum of 23.02 % displacement reduction with 38.35 % frame force increment can be achieved when compared with bare frame. This validation proves the hybrid simulation system has successfully predicted the seismic response of the test specimen.

Micromechanism of interparticle normal magnetic attraction effect in magnetorheological suspensions based on magnetic-dipole theory

In order to reveal adsorption-regulation micromechanism and debonding micromechanism between wall surface and magnetorheological (MR) wall-climbing robot legs, an interparticle normal magnetic attraction (NMA) mechanics model was constructed based upon the magnetic-dipole theory. According to analysis of NMA mechanics, it was confirmed that the interparticle NMA could be intensified with enhancing magnetic-particle diameter but was weakened with ratio of adjacent magnetic-particles distance to magnetic-particle radius. It means that the adhesive capacity between MR wall-climbing robot legs and wall surface could be strengthened by increasing magnetic-particle size and decreasing interparticle distance. Furthermore, it was found that the NMA of the first particle in the magnetic chain was positively related to magnetic-particles number until the magnetic-particles number reached a critical value. Consequently, the adsorption ability between MR wall-climbing robot legs and wall surface could be effectively controlled by changing magnetic-particles number. Besides, the strongest NMA appeared at the middle of the magnetic chain. However, the weakest NMA locates at both ends of the magnetic chain. Thus, it could be concluded that the end of the magnetic chain would be separated from wall surface rather than fracture occurred in the middle of the magnetic chain when the MR wall-climbing robot legs divorced from wall surface.

Semi-active vibration control via a magnetorheological damper and active disturbance rejection control

This work provides an alternative for the semi-active vibration control problem via state feedback plus an active disturbance rejection control (K-ADRC) for a multistory building structure equipped with one magnetorheological damper (MRD) located between the ground and the first story. This control law introduces a disturbance observer (DOB) to estimate the total disturbance in real time, produced by the earthquake perturbation, unmodeled dynamics, and parametric uncertainties, and then cancel their effect using a part of the control signal. Moreover, using a diffeomorphism, the K-ADRC provides a proportional derivative (PD) controller designed to improve internal stability. A prominent feature of the active disturbance rejection control (ADRC) algorithm is that the value of the DOB gain is selected according to the system bandwidth. The stability of the system is verified via Lyapunov analysis. Moreover, the building structure model and the MRD are accomplished by incorporating a nonlinearity state that represents the hysteresis effect to perform real behavior in addition to assuming that acceleration is the only available measurement of building structures. Thus, integral filters are provided based on the appropriate cut-off frequency to estimate displacement and velocity, avoiding bias, offset, and phase shifts. Experimental results from a reduced-scale two-story building prototype demonstrate that the proposed K-ADRC is promising for real applications, and it has better performance than the state feedback (K) and the linear quadratic regulator (LQR) control techniques.

Application of optimized polynomial controllers based on Bayesian optimization and weight matrix adjustment

AbstractThis paper uses a polynomial controller with non‐linear performance that is a summation of polynomials in non‐linear states. The optimal performance of this controller depends to a large extent on the weighting matrices elements whose determination is not easy via analytical methods for high dimension control systems. This paper focuses on optimizing a polynomial controller applied to a 20‐story non‐linear benchmark building using the Bayesian optimization (BO). BO is a powerful strategy for optimizing functions that are expensive to evaluate. In setting up the optimization problem, design variables are the parameters of weighting matrices. The objective function is a ratio of the controlled and uncontrolled response for the maximum absolute acceleration of the building, and the maximum inter‐story drift is taken as the constraint. The efficiency of the proposed control scheme is tested on a 20‐story non‐linear benchmark building equipped with magnetorheological dampers. The considered evaluation criteria are compared with other control methods. The results show that the considered algorithm is desirable in reducing the maximum seismic response under different earthquakes.

Semi-Active Suspension Design for Truck Using Pneumatic Spring Joining MR Fluid Damper Based on Neural Networks Controller

<div>In order to modify both stiffness and damping rates according to various road conditions, this research introduces a pneumatic spring in conjunction with a magnetorheological (MR) fluid damper as a single suspension unit for each wheel in the truck. Preventing weight transfer and improving riding comfort during braking, acceleration, and trajectory prediction are the main objectives. A two-axle truck has been used, consisting of three degrees of freedom for the sprung mass, including vertical, pitch, and roll motions, and four degrees of freedom for the unsprung masses, which have been redesigned according to the different types of springs and dampers. Pneumatic-controlled springs, often referred to as dynamic or classic models, replace laminated leaf springs commonly found in vehicles. Additionally, an MR damper replaces a hydraulic double-acting telescopic shock absorber. These models are studied to evaluate the effect of pneumatic spring parameters on truck dynamics. Pneumatic stiffness and the intended damping force are monitored by a recurrent neural network in conjunction with leveling control. This process provides the recommended voltage for the MR damper based on the Signum function damper controller. The performance of the suspension is assessed in the time and frequency domains for both step and random road excitations using vehicle dynamic parameters. Six suspension system configurations are compared with the air spring dynamic model integrated with the MR damper (Model 6), which is recommended as a suspension system for trucks. According to simulation data, when compared to alternative suspension systems, Model 6 significantly enhances both ride comfort and vehicle stability. Model 6 offers improvements in tire workload, truck path, tire–ground contact point during acceleration, braking efficiency, and stopping distance. Compared to previous controlled models, Model 6 also demonstrates zero steady-state offset and zero steady-state error.</div>

Vibrations Control of a SODF Structure Using TMD and MR Damper with Fuzzy Logic Algorithm Based on Velocity

In this study, the effects of using a passive tuned mass damper (TMD) with optimal parameters and a semi-active magnetorheological damper (MR damper) have been evaluated separately and simultaneously to control seismic vibrations of a linear single degree of freedom system, which was a simple "mass-spring-damper" model. OpenSEES software was used to model the single degree of freedom system and TMD, and MATLAB software was used to model MR damper. Fuzzy logic algorithm was used by MATLAB to determine the appropriate voltage for MR damper. By solving the dynamic equation of the damper, its force was calculated and this force was applied to the single degree of freedom system by OpenSEES. In the following, incremental dynamic analysis (IDA) has been performed using 7 earthquake records with maximum acceleration of 0.1g to1.0g with incremental step of 0.1g. Earthquakes are applied to four models without dampers, equipped with optimized TMD, equipped with MR damper, and equipped with both TMD and MR damper. The results showed that the simultaneous use of TMD and MR damper had the greatest effect on controlling the vibration of the system and reduced the maximum displacement by 22.36% and the maximum base shear by 21.85% compared to the case without dampers. Also, using only MR damper had a greater effect than using only TMD on reducing the seismic responses of the single degree of freedom system.

A fuzzy skyhook control strategy optimized by particle swarm strategy for magnetorheological semi-active suspension

In order to solve the problem of unsatisfactory control effect caused by uncertain parameters in the fuzzy skyhook control method, a fuzzy skyhook control strategy optimized by particle swarm strategy is proposed. The magnetorheological (MR) damper is put on the bench for mechanical characteristics experiment, and the forward model of MR damper is established. The adaptive network fuzzy inference system (ANFIS) system in simulation software is used to build its inverse model to verify the accuracy of the forward model of MR damper. A quarter vehicle suspension model is established, and a fuzzy skyhook control strategy based on particle swarm optimization is designed. Numerical simulations are carried out under the excitation of random road. The acceleration, suspension dynamic deflection and tire dynamic load are used to evaluate its performance. Compared with the passive control, the root mean square (RMS) values of the acceleration for the fuzzy skyhook control strategy are improved by 41.9% and 37.6%, the RMS values of the suspension dynamic deflection for the fuzzy skyhook control strategy are improved by 53.3% and 48.0%, and the RMS values of the tire dynamic load for the fuzzy skyhook control strategy are improved by 17.6% and 14.5% under the B-Class and C-Class road excitations. The simulations and experimental results verify the effectiveness of the controller.

Demagnetization optimization of hybrid excitation eddy current damper under intensive impact load

The hybrid excitation eddy current damper is a novel principle damper characterized by high reliability, simple structure, and controllable magnetic field. Under intensive impact loads, hybrid excitation electromagnetic damping can induce demagnetization effects, resulting in significant fluctuations of the electromagnetic damping force at 6-8 ms. To mitigate this phenomenon, this study established a finite element model of the hybrid excitation damper using COMSOL and developed a control module based on a BP neural network in Simulink. Through co-simulation of COMSOL and Simulink, the difference between the maximum and minimum electromagnetic damping force at 6-8ms is reduced from 45 kN to 5 kN. This research provides valuable technical references for the optimization and practical application of eddy current dampers.

A novel flexural damping channel magnetorheological damper with high effective magnetic field coverage and experimental verification of damping performance

Abstract Conventional magnetorheological dampers (MRDs) have limitations owing to their low effective magnetic field coverage, and improving MRD structures is a common approach to address this issue. However, many existing MRD designs have limitations such as large radial dimensions and high coil power consumption. Therefore, this paper transformed the conventional damping channel into the flexural damping channel to increase the effective magnetic field coverage of the MRD based on the conventionalstructure. And then, the pressure drop model was utilized to preliminarily determine the structural parameters of the new MRD. Subsequently, a multi-physics coupling finite element method (FEM) analysis model was constructed to accurately determine the structural parameters, ensuring that the novel flexural damping channel (NFDC) MRD increases the output peak damping force while reducing the radial dimension and input power. Furthermore, the damping force variable range is stabilized when the excitation current is zero (field-off). Finally, a large number of vibration tests were conducted on both the conventional and NFDC MRDs, and it was found that the NFDC MRD has better vibration energy dissipation capacity and higher output peak damping force while maintaining a basically same field-off damping force variable range compared with the conventional MRD. The above process not only proved that the NFDC MRD possesses excellent output damping capability and working condition adaptability, but also validated the operational effectiveness of employing the multi-physics coupling analysis method to design the NFDC MRD.