Magnetorheological damper voltage control using artificial neural network for optimum vehicle ride comfort

2021 ◽  
Vol 15 (1) ◽  
pp. 7648-7661
Author(s):  
M. F. Yakhni ◽  
M. A. El-Gohary ◽  
M. N. Ali
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Ride Comfort ◽  
Mr Damper ◽  
Suspension System ◽  
Magnetorheological Damper ◽  
Vehicle Speed ◽  
Passive Suspension ◽  
Passive Suspension System ◽  
Artificial Neural

Suspension system design is an important challenging duty that facing car manufacturers, so the challenge has become to design the best system in terms of providing ride comfort and handling ability under all driving situations. The goal of this paper is to provide assistance in enhancing the effectiveness of the suspension system. A full car model with eight degrees of freedom (DOF) was developed using MATLAB/Simulink. Validation of the Simulink model was obtained. The model was assumed to travel over a speed hump that has a half sine wave shape and amplitude that changing from 0.01 to 0.2 m. The vehicle was moving with variable speeds from 20 to 120 km/h. Magneto Rheological (MR) damper was implanted to the model to study its effect on ride comfort. Artificial Neural Network (ANN) was used to find the optimum voltage value applied to the MR damper, to skip the hump at least displacement. This network uses road profile and the vehicle speed as inputs. A comparison of the results for passive suspension system and model with MR damper, are illustrated. Results show that the MR damper give significant improvements of the vehicle ride performance over the passive suspension system.

scholarly journals Artificial neural network predication and validation of optimum suspension parameters of a passive suspension system

2019 ◽  
Vol 1 (6) ◽  
Author(s):  
Mahesh P. Nagarkar ◽  
M. A. El-Gohary ◽  
Yogesh J. Bhalerao ◽  
Gahininath J. Vikhe Patil ◽  
Rahul N. Zaware Patil
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Suspension System ◽  
Passive Suspension ◽  
Suspension Parameters ◽  
Passive Suspension System ◽  
Artificial Neural

Ride comfort of a higher speed rail vehicle using a magnetorheological suspension system

2017 ◽  
Vol 232 (1) ◽  
pp. 32-48 ◽  
Author(s):  
Sunil Kumar Sharma ◽  
Anil Kumar
Keyword(s):  
Ride Comfort ◽  
Suspension System ◽  
Magnetorheological Damper ◽  
Ride Quality ◽  
Railway Vehicle ◽  
Passive Suspension ◽  
Railway Vehicles ◽  
Rail Vehicle ◽  
Passive Suspension System ◽  
Secondary Suspension

In a railway vehicle, vibrations are generated due to the interaction between wheel and track. To evaluate the effect of vibrations on the ride quality and comfort of a passenger vehicle, the Sperling's ride index method is frequently adopted. This paper focuses on the feasibility of improving the ride quality and comfort of railway vehicles using semiactive secondary suspension based on magnetorheological fluid dampers. Equations of vertical, pitch and roll motions of car body and bogies are developed for an existing rail vehicle. Moreover, nonlinear stiffness and damping functions of passive suspension system are extracted from experimental data. In view of improvement in the ride quality and comfort of the rail vehicle, a magnetorheological damper is integrated in the secondary vertical suspension system. Parameters of the magnetorheological damper depend on current, amplitude and frequency of excitations. Three semi-active suspension strategies with magnetorheological damper are analysed at different running speeds and for periodic track irregularity. The performance indices calculated at different semi-active strategies are juxtaposed with the nonlinear passive suspension system. Simulation results establish that magnetorheological damper strategies in the secondary suspension system of railway vehicles reduce the vertical vibrations to a great extent compared to the existing passive system. Moreover, they lead to improved ride quality and passenger comfort.

Prediction of Vehicular Traffic Flow using Levenberg-Marquardt Artificial Neural Network Model: Italy Road Transportation System

2022 ◽  
Vol 24 (2) ◽  
pp. E74-E86
Author(s):  
Isaac Oyeyemi Olayode ◽  
Alessandro Severino ◽  
Tiziana Campisi ◽  
Lagouge Kwanda Tartibu
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Traffic Flow ◽  
Traffic Control ◽  
Traffic Congestion ◽  
Autonomous Vehicles ◽  
Time Of Day ◽  
Vehicle Speed ◽  
Road Transportation ◽  
Artificial Neural

In the last decades, the Italian road transport system has been characterized by severe and consistent traffic congestion and in particular Rome is one of the Italian cities most affected by this problem. In this study, a LevenbergMarquardt (LM) artificial neural network heuristic model was used to predict the traffic flow of non-autonomous vehicles. Traffic datasets were collected using both inductive loop detectors and video cameras as acquisition systems and selecting some parameters including vehicle speed, time of day, traffic volume and number of vehicles. The model showed a training, test and regression value (R2) of 0.99892, 0.99615 and 0.99714 respectively. The results of this research add to the growing body of literature on traffic flow modelling and help urban planners and traffic managers in terms of the traffic control and the provision of convenient travel routes for pedestrians and motorists.

Active Vehicle Suspension Control Using Full State-Feedback Controller

2015 ◽  
Vol 1115 ◽  
pp. 440-445 ◽  
Author(s):  
Musa Mohammed Bello ◽  
Amir Akramin Shafie ◽  
Raisuddin Khan
Keyword(s):  
State Feedback ◽  
Ride Comfort ◽  
Active Suspension ◽  
Suspension System ◽  
Feedback Controller ◽  
Vehicle Suspension ◽  
Passive Suspension ◽  
Full State ◽  
Full State Feedback ◽  
Passive Suspension System

The main purpose of vehicle suspension system is to isolate the vehicle main body from any road geometrical irregularity in order to improve the passengers ride comfort and to maintain good handling stability. The present work aim at designing a control system for an active suspension system to be applied in today’s automotive industries. The design implementation involves construction of a state space model for quarter car with two degree of freedom and a development of full state-feedback controller. The performance of the active suspension system was assessed by comparing it response with that of the passive suspension system. Simulation using Matlab/Simulink environment shows that, even at resonant frequency the active suspension system produces a good dynamic response and a better ride comfort when compared to the passive suspension system.

A New Variable Stiffness Suspension Mechanism

2011 ◽  
Author(s):  
Olugbenga M. Anubi ◽  
Carl D. Crane
Keyword(s):  
Transfer Function ◽  
Ride Comfort ◽  
Main Idea ◽  
Variable Stiffness ◽  
Suspension System ◽  
Passive Suspension ◽  
Quarter Car Model ◽  
Road Disturbance ◽  
Passive Suspension System ◽  
Suspension Performance

A new variable stiffness suspension system based on a recent variable stiffness mechanism is proposed. The overall system is composed of the traditional passive suspension system augmented with a variable stiffness mechanism. The main idea is to improve suspension performance by varying stiffness in response to road disturbance. The system is analyzed using a quarter car model. The passive case shows much better performance in ride comfort over the tradition counterpart. Analysis of the invariant equation shows that the car body acceleration transfer function magnitude can be reduced at both the tire-hop and rattle space frequencies using the lever displacement transfer function thereby resulting in a better performance over the traditional passive suspension system. An H∞ controller is designed to correct for the performance degradation in the rattle space thereby providing the best trade-off between the ride comfort, suspension deflection and road holding.

Non-Parametric Modelling and Validation of Magnetorheological Damper for Lateral Suspension of Railway Vehicle Using Interpolated Sixth Order Polynomial

2014 ◽  
Vol 699 ◽  
pp. 283-288
Author(s):  
Mohamad Hafiz Harun ◽  
Fauzi Ahmad ◽  
Mohd Razali Md Yunos ◽  
Ahmad Kamal Mat Yamin
Keyword(s):  
Ride Comfort ◽  
Mr Damper ◽  
Active Suspension ◽  
Suspension System ◽  
Magnetorheological Damper ◽  
Sixth Order ◽  
Railway Vehicle ◽  
Parametric Modelling ◽  
Track Maintenance ◽  
Order Polynomial

Passenger ride comfort is an important factor in railway vehicle services. However, passenger ride comfort is sometimes affected by the vibrations resulting from the track irregularities. It will be critical when the track is exposed to prolonged sun’s heat and lack of track maintenance. This means that the optimization of passive suspension parameters alone could not cope with these cases. Semi-active suspension system for railway vehicles has been developed as a way to solve these problems. The technology of semi-active suspension is widely used especially in the railway vehicle application. Magnetorheological (MR) damper is one of the applications of the concept of semi-active suspension. However, there are a variety of criteria for MR dampers based on usage. To meet the requirements of railway vehicle suspension system, a MR damper have been developed. The criteria for the MR damper are obtained experimentally. Then, the model for the MR damper is developed using Interpolated Sixth Order Polynomial and validated by experimental. The MR damper model has shown improvement, especially in the railway vehicle dynamics performance.

scholarly journals Mountain Bike Rear Suspension Design: Utilizing a Magnetorheological Damper for Active Vibration Isolation and Performance

2020 ◽  
Vol 25 (4) ◽  
pp. 504-512
Author(s):  
Robert Pierce ◽  
Sudhir Kaul ◽  
Jacob Friesen ◽  
Thomas Morgan
Keyword(s):  
Vibration Isolation ◽  
Ride Comfort ◽  
Mr Damper ◽  
Suspension System ◽  
Performance Characteristics ◽  
Magnetorheological Damper ◽  
Control Algorithms ◽  
Mountain Bike ◽  
Rear Suspension ◽  
And Performance

This paper presents experimental results from the development of a rear suspension system that has been designed for a mountain bike. A magnetorheological (MR) damper is used to balance the need of ride comfort with performance characteristics such as handling and pedaling efficiency by using active control. A preliminary seven degree-of-freedom mathematical model has also been developed for the suspension system. Two control algorithms have been tested in this study: on/off control and proportional control. The rear suspension system has been integrated into an existing bike frame and tested on a shaker table as well as a mountain trail. Shaker table testing demonstrates the effectiveness of the damper. Trail testing indicates that the MR damper-based shock absorber can be used to implement different control algorithms. Test results indicate that the control algorithm can be further investigated to accommodate rider preferences and desired performance characteristics.

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