Experimental Validation of the Modified Continuously Variable Command Law of a Semi-Active Suspension Integrating a Magneto-Rheological (MR) Damper

2014 ◽  
Vol 1016 ◽  
pp. 279-286
Author(s):  
Said Boukerroum ◽  
Nacer Hamzaoui
Keyword(s):  
Numerical Model ◽  
Degrees Of Freedom ◽  
Test Bench ◽  
Mr Damper ◽  
Active Suspension ◽  
Suspension System ◽  
Compression And Expansion ◽  
Low Speeds ◽  
Secondary Suspension ◽  
Magneto Rheological

The present work consists of an experimental performances analysis of a suspension system with two degrees of freedom governed by a semi-active modified continuously variable command (MCVC) law. The internal dynamics of Magneto-Rheological (MR) damper used in this study is highlighted by the modified Bouc-Wen model in the mathematical modelling of the secondary suspension system. After the dynamic characterization of the MR damper, a comparison of performance obtained by this control scheme is carried out from the responses calculated using a numerical model and measured experimentally from a test bench of a semi-active suspension incorporating an MR damper and controlled by a dSPACE control chain. For a better representativeness of the modified Bouc-Wen numerical model, a rapprochement between the calculated and measured responses for the same dynamic characteristics of the test bench is possible by adjusting the most influential parameters of the numerical model. Through better management of the suspension during the low speeds, the modified Bouc-Wen model is more representative of the real behaviour of the MR damper, given its sensitivity at these low speeds during transitions between compression and expansion phases of the damper.

Magnetorheological Semi-Active Suspension to Improve High Speed Railway Vehicles Performance

2012 ◽  
Author(s):  
Dan Baiasu ◽  
Gheorghe Ghita ◽  
Ioan Sebesan
Keyword(s):  
High Speed ◽  
Degrees Of Freedom ◽  
Active Suspension ◽  
Railway Vehicle ◽  
Lateral Dynamics ◽  
Multibody Model ◽  
Logic Control ◽  
Secondary Suspension ◽  
Magneto Rheological ◽  
The Mathematical Model

The paper presents the opportunity of using a magneto-rheological damper to control the lateral oscillations of a passenger railway vehicle to increase its comfort and speed features. The lateral dynamics of the vehicle is simulated using a multibody model with 17 degrees of freedom considering the lateral, yawing and rolling oscillations. The equations describing the model are integrated by the authors using original software. The mathematical model considers the geometrical nonlinearities of the wheel-track contact. The nonlinear stability of the vehicle running on tangent tracks with irregularities is assessed and it is shown the influence of the construction parameters of the suspensions on the vehicle’s performance. A magneto-rheological device with sequential damping based on balance logic control strategy is introduced in the secondary suspension of the vehicle to reduce the lateral accelerations generated by the track’s irregularities. The system’s response in terms of accelerations is compared for both passive and semi-active cases. It is shown that the magneto-rheological semi-active suspension improves the safety and the comfort of the railway vehicle.

Performance analysis of MR damper based semi-active suspension system using optimally tuned controllers

2021 ◽  
pp. 095440702110044
Author(s):  
Gurubasavaraju Tharehalli mata ◽  
Vijay Mokenapalli ◽  
Hemanth Krishna
Keyword(s):  
Pid Controller ◽  
Ride Comfort ◽  
Sliding Mode ◽  
Dynamic Performance ◽  
Parametric Method ◽  
Mr Damper ◽  
Active Suspension ◽  
Suspension System ◽  
Sliding Mode Controller ◽  
Road Excitation

This study assesses the dynamic performance of the semi-active quarter car vehicle under random road conditions through a new approach. The monotube MR damper is modelled using non-parametric method based on the dynamic characteristics obtained from the experiments. This model is used as the variable damper in a semi-active suspension. In order to control the vibration caused under random road excitation, an optimal sliding mode controller (SMC) is utilised. Particle swarm optimisation (PSO) is coupled to identify the parameters of the SMC. Three optimal criteria are used for determining the best sliding mode controller parameters which are later used in estimating the ride comfort and road handling of a semi-active suspension system. A comparison between the SMC, Skyhook, Ground hook and PID controller suggests that the optimal parameters with SMC have better controllability than the PID controller. SMC has also provided better controllability than the PID controller at higher road roughness.

Research on the Decoupling Control Algorithm of Full Vehicle Semi-Active Suspension

2012 ◽  
Vol 479-481 ◽  
pp. 1355-1360
Author(s):  
Jian Guo Chen ◽  
Jun Sheng Cheng ◽  
Yong Hong Nie
Keyword(s):  
Differential Geometry ◽  
Control Algorithm ◽  
Active Suspension ◽  
Suspension System ◽  
Decoupling Control ◽  
Vehicle Suspension ◽  
Full Vehicle ◽  
Vibration Attenuation ◽  
Magneto Rheological ◽  
Suspension Model

Vehicle suspension is a MIMO coupling nonlinear system; its vibration couples that of the tires. When magneto-rheological dampers are adopted to attenuate vibration of the sprung mass, the damping forces of the dampers need to be distributed. For the suspension without decoupling, the vibration attenuation is difficult to be controlled precisely. In order to attenuate the vibration of the vehicle effectively, a nonlinear full vehicle semi-active suspension model is proposed. Considering the realization of the control of magneto-rheological dampers, a hysteretic polynomial damper model is adopted. A differential geometry approach is used to decouple the nonlinear suspension system, so that the wheels and sprung mass become independent linear subsystems and independent to each other. A control rule of vibration attenuation is designed, by which the control current applied to the magneto-rheological damper is calculated, and used for the decoupled suspension system. The simulations show that the acceleration of the sprung mass is attenuated greatly, which indicates that the control algorithm is effective and the hysteretic polynomial damper model is practicable.

Control Bifurcations in a Nonlinear Active Suspension System for System Design

2005 ◽  
Author(s):  
Amit Shukla ◽  
Jeong Hoi Koo
Keyword(s):  
Control System ◽  
Ride Comfort ◽  
Active Suspension ◽  
Nonlinear Damping ◽  
Suspension System ◽  
Suspension Systems ◽  
System A ◽  
Controlled Systems ◽  
Automotive Suspension ◽  
Magneto Rheological

Nonlinear active suspension systems are very popular in the automotive applications. They include nonlinear stiffness and nonlinear damping elements. One of the types of damping element is a magneto-rheological fluid based damper which is receiving increased attention in the applications to the automotive suspension systems. Latest trends in suspension systems also include electronically controlled systems which provide advanced system performance and integration with various processes to improve vehicle ride comfort, handling and stability. A control bifurcation of a nonlinear system typically occurs when its linear approximation loses stabilizability. These control bifurcations are different from the classical bifurcation where qualitative stability of the equilibrium point changes. Any nonlinear control system can also exhibit control bifurcations. In this paper, control bifurcations of the nonlinear active suspension system, modeled as a two degree of freedom system, are analyzed. It is shown that the system looses stability via Hopf bifurcation. Parametric control bifurcation analysis is conducted and results presented to highlight the significance of the design of control system for nonlinear active suspension system. A framework for the design of feedback using the parametric analysis for the control bifurcations is proposed and illustrated for the nonlinear active suspension system.

Neural Network Based Fault Tolerant Control for a Semi-Active Suspension

2019 ◽  
Author(s):  
Sergio Alberto Rueda Villanoba ◽  
Carlos Borrás Pinilla
Keyword(s):  
Neural Network ◽  
Control System ◽  
Fault Tolerant ◽  
Mr Damper ◽  
Fault Tolerant Control ◽  
Active Suspension ◽  
Suspension System ◽  
Vehicle Body ◽  
Force Model ◽  
The Neural Network

Abstract In this study a Neural Network based fault tolerant control is proposed to accommodate oil leakages in a magnetorheological suspension system based in a half car dynamic model. This model consists of vehicle body (spring mass) connected by the MR suspension system to two lateral wheels (unsprung mass). The semi-active suspension system is a four states nonlinear model; it can be written as a state space representation. The main objectives of a suspension are: Isolate the chassis from road disturbances (passenger comfort) and maintain contact between tire and road to provide better maneuverability, safety and performance. On the other hand, component faults/failures are inevitable in all practical systems, the shock absorbers of semi-active suspensions are prone to fail due to fluid leakage but quickly detect and diagnose this fault in the system, avoid major damage to the system and ensure the safety of the driver. To successfully achieve desirable control performance, it is necessary to have a damping force model which can accurately represent the highly nonlinear and hysteretic dynamic of the MR damper. To simulate parameters of the damper, a quasi-static model was applied, quasi-static approaches are based on non-newtonian yield stress fluids flow by using the Bingham MR Damper Model, relating the relative displacement of the piston, the frictional force, a damping constant, the stiffness of the elastic element of the damper and an offset force. The Fault detection and isolation module is based on residual generation algorithms. The residua r is computed as the difference between the displacement signal of functional and faulty model, when the residual is close to zero, the process is free of faults, while any change in r represents a faulty scheme then a wavelet transform, (Morlet wave function) is used to determine the natural frequencies and amplitudes of displacement and acceleration signal during the failure, this module provides parameters to the neural network controller in order to accommodate the failure using compensation forces from the remaining healthy damper. The neural network uses the error between the plant output and the neural network plant for computing the required electric current to correct the malfunction using the inverse dynamics function of the MR damper model. Consequently, a bump condition, and a random profile road (ISO 8608) described by the power spectral density (PSD) of its vertical displacement, is used as disturbance of control system. The performance of the proposed FTC structure is demonstrated trough simulation. Results shows that the control system could reduce the effect of the partial fault of the MR Damper on system performance.

Intelligent fuzzy logic with firefly algorithm and particle swarm optimization for semi-active suspension system using magneto-rheological damper

2016 ◽  
Vol 23 (3) ◽  
pp. 501-514 ◽  
Author(s):  
Mat Hussin Ab Talib ◽  
Intan Zaurah Mat Darus
Keyword(s):  
Fuzzy Logic ◽  
Particle Swarm Optimization ◽  
Firefly Algorithm ◽  
Ride Comfort ◽  
Particle Swarm ◽  
Mr Damper ◽  
Suspension System ◽  
System Response ◽  
Swarm Optimization ◽  
Magneto Rheological

This paper presents a new approach for intelligent fuzzy logic (IFL) controller tuning via firefly algorithm (FA) and particle swarm optimization (PSO) for a semi-active (SA) suspension system using a magneto-rheological (MR) damper. The SA suspension system’s mathematical model is established based on quarter vehicles. The MR damper is used to change a conventional damper system to an intelligent damper. It contains a magnetic polarizable particle suspended in a liquid form. The Bouc–Wen model of a MR damper is used to determine the required damping force based on force–displacement and force–velocity characteristics. The performance of the IFL controller optimized by FA and PSO is investigated for control of a MR damper system. The gain scaling of the IFL controller is optimized using FA and PSO techniques in order to achieve the lowest mean square error (MSE) of the system response. The performance of the proposed controllers is then compared with an uncontrolled system in terms of body displacement, body acceleration, suspension deflection, and tire deflection. Two bump disturbance signals and sinusoidal signals are implemented into the system. The simulation results demonstrate that the PSO-tuned IFL exhibits an improvement in ride comfort and has the smallest MSE for acceleration analysis. In addition, the FA-tuned IFL has been proven better than IFL–PSO and uncontrolled systems for both road profile conditions in terms of displacement analysis.

scholarly journals H∞control of 8 degrees of freedom vehicle active suspension system

2018 ◽  
Vol 30 (2) ◽  
pp. 161-169 ◽  
Author(s):  
Syed M. Hur Rizvi ◽  
Muhammad Abid ◽  
Abdul Qayyum Khan ◽  
Shaban Ghias Satti ◽  
Jibran Latif
Keyword(s):  
Degrees Of Freedom ◽  
Active Suspension ◽  
Suspension System

Vibration Control Applied in a Semi-Active Suspension Using Magneto Rheological Damper and Optimal Linear Control Design

2013 ◽  
Vol 464 ◽  
pp. 229-234 ◽  
Author(s):  
Bruno Sousa Carneiro da Cunha ◽  
Fábio Roberto Chavarette
Keyword(s):  
Optimal Control ◽  
Nonlinear Systems ◽  
Control Design ◽  
Mr Damper ◽  
Active Suspension ◽  
Linear Control ◽  
Linear Feedback ◽  
Optimal Linear ◽  
Magneto Rheological ◽  
Non Linear System

In this paper we study the behavior of a semi-active suspension witch external vibrations. The mathematical model is proposed coupled to a magneto rheological (MR) damper. The goal of this work is stabilize of the external vibration that affect the comfort and durability an vehicle, to control these vibrations we propose the combination of two control strategies, the optimal linear control and the magneto rheological (MR) damper. The optimal linear control is a linear feedback control problem for nonlinear systems, under the optimal control theory viewpoint We also developed the optimal linear control design with the scope in to reducing the external vibrating of the nonlinear systems in a stable point. Here, we discuss the conditions that allow us to the linear optimal control for this kind of non-linear system.

scholarly journals Design of the optimal control for the active suspension

2021 ◽  
Vol 31 ◽  
pp. 1-6
Author(s):  
Sorin MARCU ◽  
◽  
Dinel POPA ◽  
Nicolae-Doru STANESCU ◽  
Nicolae PANDREA
Keyword(s):  
Optimal Control ◽  
Degrees Of Freedom ◽  
Active Suspension ◽  
Suspension System ◽  
Vertical Acceleration ◽  
Passive System ◽  
Active System ◽  
Matlab Simulink ◽  
Two Degrees Of Freedom ◽  
Lqr Control

The main purpose of the suspension is to minimize vertical acceleration. Through this paper we aim to analyze two PID and LQR control techniquesto reduce system vibrations. The active system will be compared to a passive system using two types of profile. Matlab / Simulink software is used to evaluate the performance of the two controllers using a system with two degrees of freedom. The analysis shows that we can control the suspension system using the two techniques to improve the comfort and safety of the vehicle.

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