Analytical and Experimental Evaluation of Various Active Suspension Alternatives for Superior Ride Comfort and Utilization of Autonomous Vehicles

2020 ◽  
Vol 1 (1) ◽  
Author(s):  
Ivan Cvok ◽  
Mario Hrgetić ◽  
Matija Hoić ◽  
Joško Deur ◽  
Davor Hrovat ◽  
...  

Abstract Autonomous vehicles (AVs) give the driver opportunity to engage in productive or pleasure-related activities, which will increase AV’s utility and value. It is anticipated that many AVs will be equipped with active suspension extended with road disturbance preview capability to provide the necessary superior ride comfort resulting in almost steady work or play platform. This article deals with assessing the benefits of introducing various active suspensions and related linear quadratic regulator (LQR) controls in terms of improving the work/leisure ability. The study relies on high-performance shaker rig-based tests of a group of 44 drivers involved in reading/writing, drawing, and subjective ride comfort rating tasks. The test results indicate that there is a threshold of root-mean-square vertical acceleration, below which the task execution performance is similar to that corresponding to standstill conditions. For the given, relatively harsh road disturbance profile, only the fully active suspension with road preview control can suppress the vertical acceleration below the above critical superior comfort threshold. However, when adding an active seat suspension, the range of chassis suspension types for superior ride comfort is substantially extended and can include semi-active suspension and even passive suspension in some extreme cases that can, however, lead to excessive relative motion between the seat and the vehicle floor. The design requirements gained through simulation analysis, and extended with cost and packaging requirements related to passenger car applications, have guided design of two active seat suspension concepts applicable to the shaker rig and production vehicles.

Author(s):  
Sharifah Munawwarah Syed Mohd Putra ◽  
Fitri Yakub ◽  
Mohamed Sukri Mat Ali ◽  
Noor Fawazi Mohd Noor Rudin ◽  
Zainudin A. Rasid ◽  
...  

2014 ◽  
Vol 663 ◽  
pp. 146-151 ◽  
Author(s):  
Noraishikin Zulkarnain ◽  
Hairi Zamzuri ◽  
Saiful Amri Mazlan

The objective of this paper is to design a linear quadratic regulator (LQR) and linear quadratic Gaussian (LQG) controllers for an active anti-roll bar system. The use of an active anti-roll bar will be analysed from two different perspectives in vehicle ride comfort and handling performances. This paper proposed the basic vehicle dynamic modelling with four degree of freedom (DOF) on half car model and are described that show, why and how it is possible to control the handling and ride comfort of the car, with the external forces also control strategies on the front anti-roll bar. By simulation analysis, the design model is validity and the performance under control of linear quadratic regulator (LQR) and linear quadratic Gaussian (LQG) controller are achieved. Both two controllers are modeled in MATLAB/SIMULINK environment. It has to be determined which control strategy delivers better performance with respect to roll angle and the roll rate of half vehicle body. The result shows, however, that LQG produced better response compared to a LQR strategy.


Energies ◽  
2021 ◽  
Vol 14 (24) ◽  
pp. 8231
Author(s):  
Manbok Park ◽  
Seongjin Yim

This paper presents a method to design active suspension controllers for a 7-Degree-of-Freedom (DOF) full-car (FC) model from controllers designed with a 2-DOF quarter-car (QC) one. A linear quadratic regulator (LQR) with 7-DOF FC model has been widely used for active suspension control. However, it is too hard to implement the LQR in real vehicles because it requires so many state variables to be precisely measured and has so many elements to be implemented in the gain matrix of the LQR. To cope with the problem, a 2-DOF QC model describing vertical motions of sprung and unsprung masses is adopted for controller design. LQR designed with the QC model has a simpler structure and much smaller number of gain elements than that designed with the FC one. In this paper, several controllers for the FC model are derived from LQR designed with the QC model. These controllers can give equivalent or better performance than that designed with the FC model in terms of ride comfort. In order to use available sensor signals instead of using full-state feedback for active suspension control, LQ static output feedback (SOF) and linear quadratic Gaussian (LQG) controllers are designed with the QC model. From these controllers, observer-based controllers for the FC model are also derived. To verify the performance of the controllers for the FC model derived from LQR and LQ SOF ones designed with the QC model, frequency domain analysis is undertaken. From the analysis, it is confirmed that the controllers for the FC model derived from LQ and LQ SOF ones designed with the QC model can give equivalent performance to those designed with the FC one in terms of ride comfort.


2021 ◽  
pp. 095745652110003
Author(s):  
VSV Satyanarayana ◽  
LVV Gopala Rao ◽  
B Sateesh ◽  
N Mohan Rao

This article aims to determine the optimum parameters of a half-car model passive suspension vehicle passing on a random road. The optimum parameters are obtained based on the response of linear quadratic regulator control with a look-ahead preview for attaining the passive suspension performance nearly equivalent to the active suspension performance. The optimum parameters are estimated by equalizing mean square suspension controlling forces of passive and active vehicle models and subsequently minimizing the performance error between the two systems. The response of passive suspension with optimized parameters matches approximately with the active suspension response, with respect to ride comfort and road holding.


2011 ◽  
Vol 2-3 ◽  
pp. 1067-1070
Author(s):  
Hai Jun Xing ◽  
Shao Pu Yang ◽  
Yong Jun Shen

This research aims at the vibration control of vehicle seat suspension system. A three degree of freedom quarter vehicle model is used for semi-active control system in which a magnetorheological damper (MRD) is installed at the position between the vehicle body and the seat. A fully active linear quadratic regulator (LQR) control strategy is used to determine the optimized control force which is then matched by MRD to compute the semi-active control result. Computation result proves that semi-active control with MRD can alleviate the vehicle seat acceleration to improve ride comfort.


Author(s):  
Jialing Yao ◽  
Meng Wang ◽  
Yanan Bai

Automobile roll control aims to reduce or achieve a zero roll angle. However, the ability of this roll control to improve the handling stability of vehicles when turning is limited. This study proposes a direct tilt control methodology for automobiles based on active suspension. This tilt control leans the vehicle’s body toward the turning direction and therefore allows the roll moment generated by gravity to reduce or even offset the roll moment generated by the centrifugal force. This phenomenon will greatly improve the roll stability of the vehicle, as well as the ride comfort. A six-degrees-of-freedom vehicle dynamics model is established, and the desired tilt angle is determined through dynamic analysis. In addition, an H∞ robust controller that coordinates different performance demands to achieve the control objectives is designed. The occupant’s perceived lateral acceleration and the lateral load transfer ratio are used to evaluate and explain the main advantages of the proposed active tilt control. To account the difference between the proposed and traditional roll controls, a simulation analysis is performed to compare the proposed tilt H∞ robust control, a traditional H∞ robust control for zero roll angle, and a passive suspension system. The analysis of the time and frequency domains shows that the proposed controller greatly improves the handling stability and anti-rollover ability of vehicles during steering and maintains acceptable ride comfort.


2020 ◽  
Vol 10 (22) ◽  
pp. 8060
Author(s):  
Ahmad Fares ◽  
Ahmad Bani Younes

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.


Author(s):  
Mingchun Liu ◽  
Yuanzhi Zhang ◽  
Juhua Huang ◽  
Caizhi Zhang

This study addresses the challenges of ride comfort improvement and in-wheel-motor vibration suppression in in-wheel-motor-driven electric vehicles. First, a mathematical model of a quarter vehicle equipped with a dynamic vibration absorber and an active suspension is developed. Then, a two-stage optimization control method is proposed to improve the coupled dynamic vibration absorber–suspension performance. In the first stage, a linear quadratic regulator controller based on particle swarm optimization is designed for the dynamic vibration absorber to suppress the in-wheel-motor vibration, in which the dynamic vibration absorber parameters and linear quadratic regulator controller weighting factors are optimally matched by using the particle swarm optimization algorithm. In the second stage, a finite-frequency H∞ controller is designed in the framework of linear matrix inequality optimization for the active suspension to improve vehicle ride comfort. Suspension performance factors, including suspension working space and road-holding ability, are taken as constraints in both stages. The proposed method simultaneously improves vehicle ride comfort and suppresses in-wheel-motor vibration. Finally, the effectiveness and superiority of the proposed method are illustrated through comparison simulations.


2014 ◽  
Vol 663 ◽  
pp. 152-157
Author(s):  
Aghil Shavalipour ◽  
Sallehuddin Mohamed Haris

This paper consider the control of active automotive suspensions applying Mixed (H2/H∞) state-space optimization techniques. It is well known that the ride comfort is improved by reducing vehicle body acceleration generated by road disturbance. In order to study this phenomenon, Two Degrees of Freedom (DOF) in state space vehicle model was built in. However, the H∞ control method attenuates the agitation effect on the output while H2 is employed to improve the input of the controller. Linear Matrix Inequality (LMI) technique is employed to calculate the dynamic controller parameters. The outcome of the simulation revealed that ride comfort for the vehicle upgraded adequately by applying mixed H2/H∞ Control method for active suspension system, and also the mixed H2/H∞ Control method was more effective than the H∞ Control method.


Sign in / Sign up

Export Citation Format

Share Document