A Study of Control Strategy for Vehicle Semi-Active Suspension System

Author(s):  
Yiming Zhang ◽  
Ye Lin

Abstract This paper investigates a reference control strategy for Vehicle semi-active suspension. The control is conducted by following the idea optimal active controller. The passive actuator is set to optimal whenever the active and passive actuators have the same signs; and set to zero output whenever the two signs are opposite. The simulation results of a 2DoF vehicle show that the semi -active suspension system can follow the ideal active system very well, both are superior to conventional passive systems. In this paper, a 2DoF vehicle model was also used to study a statistical optimal control strategy of the semi-active suspension system. The statistical optimal concept is the result of the combination of the nonlinear programming and controllable damper. A way of estimating statistical characteristics of road irregularities was also proposed. Vehicle active, suspension, due to its perfect v i bra t i on isolation performance, gets moreand more attention. Active suspension can be generally divided into two categories, totally active suspension system and semi-active suspension system. From the published results it is known that active suspension can surpass the performance limit of conventional passive suspension and greatly improve the vehicle riding comfort and steering ability. But active suspension has a critical disadvantage of less applicability, due to its high cost and low reliability. Also it consumes large amount of energy as it works. The idea of semi-active suspension was put forward to overcome the shortcoming of active suspension. It is a compromise between active suspension and passive suspension. Semi-active suspension has approximately the same behavior as active suspension, and almost consumes no energy as it works. So semi-active suspension possesses a great potential in application. At. present, in the field of suspension research over the world, a great deal of attention is paied to semi-active suspension. At present, for the cotrol of semi-active suspension the widely studied strategy is “on off” control [1] [2], which is first put forward by Karnopp. “On-off” control can eliminate the phenomenon of vibration amplification for passive suspension, thus it can improve the suspension performance to certain extent. At present, no substantive result has been obtained yet in the field of optimal control of semi-active suspension. This paper will investigate a reference control strategy on the basis of linear optimal control. The control is conducted by following the optimal ctive controller. The referrence control result is optimal when the outputs of the active and semi-active force generators have the same signs.

Author(s):  
Sorin MARCU ◽  
◽  
Dinel POPA ◽  
Nicolae-Doru STANESCU ◽  
Nicolae PANDREA

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.


2019 ◽  
Vol 11 (2) ◽  
pp. 55
Author(s):  
Nur Uddin

The optimal control design of the ground-vehicle active suspension system is presented. The active suspension system is to improve the vehicle ride comfort by isolating vibrations induced by the road profile and vehicle velocity. The vehicle suspension system is approached by a quarter car model. Dynamic equations of the system are derived by applying Newton’s second law. The control law of the active suspension system is designed using linear quadratic regulator (LQR) method. Performance evaluation is done by benchmarking the active suspension system to a passive suspension system. Both suspension systems are simulated in computer. The simulation results show that the active suspension system significantly improves the vehicle ride comfort of the passive suspension system by reducing 50.37% RMS of vertical displacement, 45.29% RMS of vertical velocity, and 1.77% RMS of vertical acceleration.


2017 ◽  
Vol 40 (13) ◽  
pp. 3617-3624
Author(s):  
Fengchen Wang ◽  
Decheng Wang ◽  
Jia Sun ◽  
Jianzhu Zhao

This paper proposes a novel intelligent optimal control strategy for crawler vehicles with semi-active suspension. The proposed control strategy aims at improving vehicle ride comfort by addressing contradictory suspension properties requirements of ride comfort and handling stability simultaneously. After establishing seven degrees of freedom dynamic model of the crawler vehicle, a comprehensive evaluation index is developed to trade off among various vehicle performances, which include ride comfort, damper thermal reliability, elastic element fatigue and handling stability. Then, using modified staged continuous tabu search (MSCTS) algorithm, the optimal control efforts of semi-active suspension, damping ratios, are determined by minimizing the cost function defined by the comprehensive evaluation index. Demonstrated by simulations with triangle convex block and random ground roughness excitations, MSCTS control strategy can successfully improve ride comfort performance and achieve the optimal comprehensive performance as well.


2012 ◽  
Vol 38 (6) ◽  
pp. 1017 ◽  
Author(s):  
Jia-Yan ZHANG ◽  
Zhong-Hai MA ◽  
Xiao-Bin QIAN ◽  
Shao-Ming LI ◽  
Jia-Hong LANG

2021 ◽  
Vol 145 ◽  
pp. 110789
Author(s):  
Parthasakha Das ◽  
Samhita Das ◽  
Pritha Das ◽  
Fathalla A. Rihan ◽  
Muhammet Uzuntarla ◽  
...  

Energies ◽  
2021 ◽  
Vol 14 (2) ◽  
pp. 271
Author(s):  
Yusung Lee ◽  
Woohyun Kim

In this study, an optimal control strategy for the variable refrigerant flow (VRF) system is developed using a data-driven model and on-site data to save the building energy. Three data-based models are developed to improve the on-site applicability. The presented models are used to determine the length of time required to bring each zone from its current temperature to the set point. The existing data are used to evaluate and validated the predictive performance of three data-based models. Experiments are conducted using three outdoor units and eight indoor units on site. The experimental test is performed to validate the performance of proposed optimal control by comparing between conventional and optimal control methods. Then, the ability to save energy wasted for maintaining temperature after temperature reaches the set points is evaluated through the comparison of energy usage. Given these results, 30.5% of energy is saved on average for each outdoor unit and the proposed optimal control strategy makes the zones comfortable.


Sign in / Sign up

Export Citation Format

Share Document