A semi-active suspension using a magnetorheological damper with nonlinear negative-stiffness component

Yang, Jie; Ning, Donghong; Sun, Shuaishuai; Zheng, Jun; Lu, Hongda; Nakano, Masami; Zhang, S; Du, Haiping; Li, Weihua

doi:10.1016/j.ymssp.2020.107071

Cited by 134 publications

(44 citation statements)

References 44 publications

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“…The model is shown in Figure 1 for a passive seat suspension system with fixed damping rate, cs, and spring constant, ks, while semi-active suspension system has a different value of damping rate, cs. Previous researcher has shown that a passive suspension system fails to attenuate the amplitude of given vibration sources when the frequency of the vibration is at low frequency [9]. An active suspension system is designed by replacing the spring and damper between the seat and the floor with an actuator model which means the actuator work ABSTRACT -This paper presents a modified intelligent active force control (AFC) control strategy in a semi active seat suspension system.…”

Section: Seat Suspension Modelmentioning

confidence: 99%

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Semi Active Seat Suspension System using Modified Intelligent Active Force Control

Rosli

Mohamed

Priyandoko

2021

IJAME

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This paper presents a modified intelligent active force control (AFC) control strategy in a semi active seat suspension system. The main actuator studied in this research is the Magneto-rheological (MR) damper. Since a semi-active device like MR damper can only dissipate energy so a modified version of AFC controller is needed. The modified AFC controller main function is to determine the appropriate control force. A Heaviside Step Function (HSF) is used to ensure the MR damper produce the desired damping force according to the control force generated by AFC controller. The phenomenological Bouc-Wen is used to study the effectiveness of the new AFC controller taking into account the dynamic response of the damper. Sinusoidal signals simulated as vibration sources are applied to the seat suspension system to investigate the improvement of ride comfort as well as to ascertain the new AFC controller robustness. Comparison of body acceleration signals from the passive suspension with AFC controller semi active seat suspension system shows up to to 45% improvement to the occupant ride comfort under different vibration intensities.

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Section: Seat Suspension Modelmentioning

confidence: 99%

“…Semi-active system can be applied by either controlling the damping force or the spring rate of the suspension system. Many researchers utilise the magnetorheological, MR damper as a vibration isolation system in various engineering applications as it offers a large amount of control force with a very minimum power input [7][8][9][10].…”

Section: Introductionmentioning

confidence: 99%

Semi Active Seat Suspension System using Modified Intelligent Active Force Control

Rosli

Mohamed

Priyandoko

2021

IJAME

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“…It is defined as a mechanical two-terminal device with the property that the applied force is proportional to the relative acceleration between these two terminals. The applications of inerter in various mechanical structures have been investigated, such as vehicle suspensions (Hu et al, 2014;Li et al, 2012;Nie et al, 2010;Ning et al, 2019;Smith and Wang, 2004;Wang and Chan, 2011;Yang et al, 2021), train suspension systems (Liao, 2006), building vibration control (Xu, 2005). A generator-based semi-active inerter was proposed to achieve energy harvesting and the captured energy was employed for vibration control of the system (Liu et al, 2020(Liu et al, , 2021Qian et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

Vibration control of vehicle suspension with magneto-rheological variable damping and inertia

Dong

et al. 2021

Journal of Intelligent Material Systems and Structures

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To avoid the limitation of conventional vehicle magnetorheological (MR) suspension, a variable damping and inertia device is applied in the vehicle suspension with MR technology. A semi-active adaptive MR inerter (AMRI) is discussed. A quarter car suspension model with an AMRI installed in parallel with a double-ended MR damper (D-MRD) is considered. First, the vehicle suspension with variable damping and inertia is analyzed. The prototype of D-MRD and MR variable inertia flywheel (MRVIF) are fabricated and tested respectively. Then, the control model of D-MRD and MRVIF is developed on the basis of test data. An improved Fuzzy PID controller for the semi-active suspension with D-MRD and AMRI is formulated. Numerical simulation is investigated to validate the proposed variable damping and inertia device. The results demonstrate that the performance of the semi-active suspension with D-MRD and AMRI can achieve much better ride comfort than the semi-active suspension with only D-MRD or AMRI.

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“…Magnetorheological fluids (MRFs) are smart materials utilized to implement semi-active systems to enable their controllability [1]. MRFs have gained massive interests during the last decades and been incorporated in many applications, including dampers, control valves, brakes and clutches [2][3][4][5].…”

Section: Introductionmentioning

confidence: 99%

Parametric Estimation From Empirical Data Using Particle Swarm Optimization Method for Different Magnetorheological Damper Models

et al. 2021

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The nonlinearity behaviour of magnetorheological fluid (MRF) can be described using a number of established models such as Bingham and Modified Bouc-Wen models. Since these models require the identification of model parameters, there is a need to estimate the parameters' value carefully. In this paper, an optimization algorithm, i.e., the Particle Swarm Optimization (PSO) algorithm, is utilized to identify the models' parameters. The PSO algorithm distinctively controls the best fit value by minimizing marginal error through root-mean-square error between the models and the empirical response. The validation of the algorithm is attained by comparing the resulting modified Bouc-Wen model behaviour using PSO against the same model's behaviour, identified using Genetic Algorithm (GA). The validation results indicate that the application of PSO is better in identifying the model parameters. Results from this estimation can be used to design a controller for various applications such as prosthetic limbs.

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A semi-active suspension using a magnetorheological damper with nonlinear negative-stiffness component

Cited by 134 publications

References 44 publications

Semi Active Seat Suspension System using Modified Intelligent Active Force Control

Semi Active Seat Suspension System using Modified Intelligent Active Force Control

Vibration control of vehicle suspension with magneto-rheological variable damping and inertia

Parametric Estimation From Empirical Data Using Particle Swarm Optimization Method for Different Magnetorheological Damper Models

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