Active Suspension System Modeling for a Passenger Car Subjected to Random Road Profile Inputs

2020 ◽  
pp. 427-433
Author(s):  
Mohd Avesh ◽  
Rajeev Srivastava
Keyword(s):  
System Modeling ◽  
Active Suspension ◽  
Suspension System ◽  
Passenger Car ◽  
Road Profile

scholarly journals Online Reinforcement Learning-Based Control of an Active Suspension System Using the Actor Critic Approach

2020 ◽  
Vol 10 (22) ◽  
pp. 8060
Author(s):  
Ahmad Fares ◽  
Ahmad Bani Younes
Keyword(s):  
Reinforcement Learning ◽  
Least Squares Method ◽  
Linear Quadratic Regulator ◽  
Active Suspension ◽  
Suspension System ◽  
Recursive Least Squares ◽  
Linear Quadratic ◽  
Reward Function ◽  
Road Profile ◽  
The One

In this paper, a controller learns to adaptively control an active suspension system using reinforcement learning without prior knowledge of the environment. The Temporal Difference (TD) advantage actor critic algorithm is used with the appropriate reward function. The actor produces the actions, and the critic criticizes the actions taken based on the new state of the system. During the training process, a simple and uniform road profile is used while maintaining constant system parameters. The controller is tested using two road profiles: the first one is similar to the one used during the training, while the other one is bumpy with an extended range. The performance of the controller is compared with the Linear Quadratic Regulator (LQR) and optimum Proportional-Integral-Derivative (PID), and the adaptiveness is tested by estimating some of the system’s parameters using the Recursive Least Squares method (RLS). The results show that the controller outperforms the LQR in terms of the lower overshoot and the PID in terms of reducing the acceleration.

scholarly journals Road Profile Estimation Using a 3D Sensor and Intelligent Vehicle

Sensors ◽  
2020 ◽  
Vol 20 (13) ◽  
pp. 3676 ◽  
Author(s):  
Tao Ni ◽  
Wenhang Li ◽  
Dingxuan Zhao ◽  
Zhifei Kong
Keyword(s):  
Real Time ◽  
Autonomous Vehicles ◽  
Active Suspension ◽  
Suspension System ◽  
Global Navigation Satellite Systems ◽  
Cloud Data ◽  
Uneven Terrain ◽  
Road Profile ◽  
Data Points ◽  
Profile Estimation

Autonomous vehicles can achieve accurate localization and real-time road information perception using sensors such as global navigation satellite systems (GNSSs), light detection and ranging (LiDAR), and inertial measurement units (IMUs). With road information, vehicles can navigate autonomously to a given position without traffic accidents. However, most of the research on autonomous vehicles has paid little attention to road profile information, which is a significant reference for vehicles driving on uneven terrain. Most vehicles experience violent vibrations when driving on uneven terrain, which reduce the accuracy and stability of data obtained by LiDAR and IMUs. Vehicles with an active suspension system, on the other hand, can maintain stability on uneven roads, which further guarantees sensor accuracy. In this paper, we propose a novel method for road profile estimation using LiDAR and vehicles with an active suspension system. In the former, 3D laser scanners, IMU, and GPS were used to obtain accurate pose information and real-time cloud data points, which were added to an elevation map. In the latter, the elevation map was further processed by a Kalman filter algorithm to fuse multiple cloud data points at the same cell of the map. The model predictive control (MPC) method is proposed to control the active suspension system to maintain vehicle stability, thus further reducing drifts of LiDAR and IMU data. The proposed method was carried out in outdoor environments, and the experiment results demonstrated its accuracy and effectiveness.

scholarly journals The algorithm of adaptive control for active suspension systems using pole assign and cascade design method

2020 ◽  
Vol 9 (4) ◽  
pp. 271
Author(s):  
Chi Nguyen Van
Keyword(s):  
Control Method ◽  
Reference Model ◽  
Active Suspension ◽  
Suspension System ◽  
Control Force ◽  
Control Loop ◽  
The Road ◽  
Suspension Systems ◽  
Road Profile ◽  
Control Scheme

This paper presents the active suspension system (ASS) control method using the adaptive cascade control scheme. The control scheme is implemented by two control loops, the inner control loop and outer control loop are designed respectively. The inner control loop uses the pole assignment method in order to move the poles of the original system to desired poles respect to the required performance of the suspension system. To design the controller in the inner loop, the model without the noise caused by the road profile and velocity of the car is used. The outer control loop then designed with an adaptive mechanism calculates the active control force to compensate for the vibrations caused by the road profile and velocity of the car. The control force is determined by the error between states of the reference model and states of suspension systems, the reference model is the model of closed-loop with inner control loop without the noise. The simulation results implemented by using the practice date of the road profile show that the capability of oscillation decrease for ASS is quite efficient

Dynamic Behaviour of a 7 DoF Passenger Car Model

2017 ◽  
Vol 9 (1) ◽  
Author(s):  
P.P.D. Rao ◽  
S. Palli ◽  
R.C. Sharma
Keyword(s):  
Natural Frequencies ◽  
Ride Comfort ◽  
Active Suspension ◽  
High Energy ◽  
Suspension System ◽  
Mode Shapes ◽  
Active System ◽  
Passenger Car ◽  
Conventional Vehicle ◽  
Suspension Systems

Conventional vehicle suspension systems, which are passive in nature consists of springs with constant stiffness and dampers with constant damping coefficient. These suspension systems cannot meet the characteristics such as ride comfort, road handing and suspension deflection during abnormal road conditions simultaneously. Active and semi-active suspension systems are the solutions to achieve the desired suspension characteristics. Since, active system is bulky and requires high energy for working, a semi-active suspension system is considered in the present work to analyze vehicle traversing over various road profiles for ride comfort. Mathematical model of a 7 DoF passenger car is formulated using Newton’s method. A semi-active suspension system with skyhook linear control strategy avoids the road excitations at resonant frequencies by shifting the natural frequencies of the model by varying damping coefficients based on the vehicle response for different road conditions where the excitations could be harmonic, transient and random. Modal analysis is carried out to identify the un-damped natural frequencies and mode shapes for different values of damping. The above analyses are carried out through analytical and numerical methods using MATLAB and ANSYS software respectively and the results obtained from both are in good agreement.

A Computer Aided Engineering Approach for the Optimal Design of an Active Suspension System

2009 ◽  
Author(s):  
Marco Gubitosa ◽  
Jan Anthonis ◽  
Nicolas Albarello ◽  
Wim Desmet
Keyword(s):  
Optimal Design ◽  
Control Strategy ◽  
Degrees Of Freedom ◽  
System Modeling ◽  
Active Suspension ◽  
Suspension System ◽  
Design Parameters ◽  
Design Development ◽  
Detailed Model ◽  
Multidisciplinary System

Within companies dealing with the automotive market, and in particular for product designers, the usage of numerical simulations is a well established technique to help achieving faster development cycles. Focusing on the very first phase of the design development chain conceptual (ID) modeling software is better suited. Furthermore considering the multiphysics nature of vehicle subsystems, a multidisciplinary system modeling tool is required, which has to be enriched with optimization capabilities in order to produce a suitable design of complex systems involving multiphysics functionalities (for instance for active safety and energy management). The purpose of this paper is to summarize a procedure that has been applied for the optimal design of an active suspension with hydraulic actuation, governed by a general control strategy based on the sky-hook approach, to be manufactured by Tenneco. A 15 Degrees of Freedom (DOF) vehicle model, built in a commercially available 1D simulation environment, has been validated as a first step towards achieving a good correlation with experimental results obtained on the test tracks. As a next step, the sky-hook based control strategy was implemented to take into account the active behavior of the system, and to define the load profiles acting on the suspension dampers while the vehicle is virtually tested on ride roads. Optimization loops were performed in a nested architecture in order to define the optimal gains needed to meet certain performance requirements dictated by the vehicle manufacturer. A detailed model of the damping system was implemented in LMS Imagine.Lab AMESim capturing its multidisciplinary nature including mechanical, hydraulic and electrical aspects. The mission profiles (force-velocity couples at the dampers) were used as input to the simulations to investigate the damping system design parameters considering performance achievement and energy efficiency goals. The results of this project have been used by Tenneco as guidelines for the physical prototype implementation of the active suspension system.

scholarly journals Optimal Control of an 8-DOF Vehicle Active Suspension System Using Kalman Observer

2008 ◽  
Vol 15 (5) ◽  
pp. 493-503 ◽  
Author(s):  
S. Hossein Sadati ◽  
Salar Malekzadeh ◽  
Masood Ghasemi
Keyword(s):  
Optimal Control ◽  
Ride Comfort ◽  
Active Suspension ◽  
Suspension System ◽  
The Body ◽  
Control Approach ◽  
Seat Suspension ◽  
Handling Characteristics ◽  
Road Profile ◽  
Passive Suspension System

In this paper, an 8-DOF model including driver seat dynamics, subjected to random road disturbances is used in order to investigate the advantage of active over conventional passive suspension system. Force actuators are mounted parallel to the body suspensions and the driver seat suspension. An optimal control approach is taken in the active suspension used in the vehicle. The performance index for the optimal control design is a quantification of both ride comfort and road handling. To simulate the real road profile condition, stochastic inputs are applied. Due to practical limitations, not all the states of the system required for the state-feedback controller are measurable, and hence must be estimated with an observer. In this paper, to have the best estimation, an optimal Kalman observer is used. The simulation results indicate that an optimal observer-based controller causes both excellent ride comfort and road handling characteristics.

A Practical Control Concept for Passenger Car Active Suspensions with Preview

1989 ◽  
Vol 203 (4) ◽  
pp. 221-230 ◽  
Author(s):  
W Foag
Keyword(s):  
Short Distance ◽  
Controller Design ◽  
Active Suspension ◽  
Performance Criteria ◽  
Control Law ◽  
Active Suspensions ◽  
Passenger Car ◽  
Simulation And Optimization ◽  
Road Profile ◽  
Control Concept

The message of this simulation and optimization-based design study is threefold: first, short-distance (below 2 m) road profile preview substantially improves all relevant performance criteria of an active suspension; second, controller design for such a preview suspension can be done in a pragmatic, yet systematic way; and third, the preview (feedforward) part of the control law can co-operate harmonically with the controller of an already conceived or existing feedback-only active suspension.

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