Wheelbase preview control of an active suspension with a disturbance-decoupled observer to improve vehicle ride comfort

Author(s):  
Baek-soon Kwon ◽  
Daejun Kang ◽  
Kyongsu Yi

This article deals with the design of a partial preview active suspension control algorithm for the improvement of vehicle ride comfort. Generally, while preview-controlled active suspension systems have even greater potential than feedback-controlled systems, their main challenge is obtaining preview information of the road profile ahead. A critical drawback of the “look-ahead” sensors is an increased risk of incorrect detection influenced by water, snow, and other soft obstacles on the road. In this work, a feasible wheelbase preview suspension control algorithm without information about the road elevation has been developed based on a novel 3-degree-of-freedom full-car dynamic model which incorporates only the vehicle body dynamics. The main advantage of the employed vehicle model is that the system disturbance input vector consists of vertical wheel accelerations that can be measured easily. The measured acceleration information of the front wheels is used for predictive control of the rear suspension to stabilize the body motion. The suspension state estimator has also been designed to completely remove the effect of unknown road disturbance on the state estimation error. The estimation performance of an observer is verified via a simulation study and field tests. The performance of the proposed suspension controller is evaluated on a frequency domain and time domain via a simulation study. It is shown that the vehicle ride comfort can be improved more by the proposed wheelbase preview control approach than by the feedback approach.

2021 ◽  
Vol 2129 (1) ◽  
pp. 012014
Author(s):  
M H Ab Talib ◽  
I Z Mat Darus ◽  
H M Yatim ◽  
M S Hadi ◽  
N M R Shaharuddin ◽  
...  

Abstract The semi-active suspension (SAS) system is a partial suspension device used in the vehicle system to improve the ride comfort and road handling. Due to the high non-linearity of the road profile disturbances plus uncertainties derived from vehicle dynamics, a conventional Skyhook controller is not deemed enough for the vehicle system to improve the performance. A major problem of the implementation of the controller is to optimize a proper parameter as this is an important element in demanding a good controller response. An advanced Firefly Algorithm (AFA) integrated with the modified skyhook (MSky) is proposed to enhance the robustness of the system and thus able to improve the vehicle ride comfort. In this paper, the controller scheme to be known as MSky-AFA was validated via MATLAB simulation environment. A different optimizer based on the original firefly algorithm (FA) is also studied in order to compute the parameter of the MSky controller. This control scheme to be known as MSky-FA was evaluated and compared to the proposed MSky-AFA as well as the passive suspension control. The results clearly exhibit more superior and better response of the MSky-AFA in reducing the body acceleration and displacement amplitude in comparison to the MSky-FA and passive counterparts for a sinusoidal road profile condition.


1995 ◽  
Vol 7 (4) ◽  
pp. 307-311
Author(s):  
Hideo Tobata ◽  
◽  
Takeshi Kimura ◽  
Yohsuke Akatsu

It is known that the ride comfort of a vehicle equipped with active suspension can be further improved if a priori information about the road surface, i.e., preview control, is used. This paper discusses the application of preview control to the rear wheels of a vehicle with active suspension. Information about the front wheels' vertical motion is used to estimate the vertical travel of the rear wheels. Vibration transmitted from the road surface to the vehicle body through the rear suspension can be estimated from the vertical motion of the wheels. Thus, the control force that should be generated by the rear suspension actuators can be obtained. Simulation results reveal that preview control provides an accurate estimate of road force inputs, enabling the vertical acceleration of the vehicle body to be reduced for further improvement in ride comfort. The results of vehicle driving tests also confirm that the preview-control force serves to reduce the vertical acceleration of the vehicle body. Cooperation between preview control and a skyhook damper is also discussed and shown to be effective in reducing vehicle body vibration.


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.


2019 ◽  
Vol 2019 ◽  
pp. 1-17
Author(s):  
Mingde Gong ◽  
Haohao Wang ◽  
Xin Wang

Road input can be provided for a vehicle in advance by using an optical sensor to preview the front terrain and suspension parameters can be adjusted before a corresponding moment to keep the body as smooth as possible and thus improve ride comfort and handling stability. However, few studies have described this phenomenon in detail. In this study, a LiDAR coupled with global positioning and inertial navigation systems was used to obtain the digital terrain in front of a vehicle in the form of a 3D point cloud, which was processed by a statistical filter in the Point Cloud Library for the acquisition of accurate data. Next, the inverse distance weighting interpolation method and fractal interpolation were adopted to extract the road height profile from the 3D point cloud and improve its accuracy. The roughness grade of the road height profile was utilised as the input of active suspension. Then, the active suspension, which was based on an LQG controller, used the analytic hierarchy process method to select proper weight coefficients of performance indicators according to the previously calculated road grade. Finally, the road experiment verified that reasonable selection of active suspension’s LQG controller weightings based on estimated road profile and road class through fractal interpolation can improve the ride comfort and handling stability of the vehicle more than passive suspension did.


2014 ◽  
Vol 592-594 ◽  
pp. 2165-2178 ◽  
Author(s):  
M.W. Trikande ◽  
Vinit V. Jagirdar ◽  
Muraleedharan Sujithkumar

Comparative performance of vehicle suspension system using passive, and semi-active control (on-off and continuous) has been carried out for a multi-axle vehicle under the source of road disturbance. Modelling and prediction for stochastic inputs from random road surface profiles has been carried out. The road surface is considered as a stationary stochastic process in time domain assuming constant vehicle speed. The road surface elevations as a function of time have been generated using IFFT. Semi active suspension gives better ride comfort with consumption of fraction of power required for active suspension. A mathematical model has been developed and control algorithm has been verified with the purpose/objective of reducing the unwanted sprung mass motions such as heave, pitch and roll. However, the cost and complexity of the system increases with implementation of semi-active control, especially in military domain. In addition to fully passive and fully semi-active a comparison has been made with partial semi-active control for a multi-axle vehicle to obviate the constraints. The time domain response of the suspension system using various control logics are obtained and compared. Simulations for different class of roads as defined in ISO: 8608 have been run and the ride comfort is evaluated and compared in terms of rms acceleration at CG in vertical direction (Z), which is the major contributor for ORV (Overall Ride Value) Measurement.


Author(s):  
Alireza Rezaee ◽  
Mazyar Pajohesh

In this paper, fuzzy logic is used to control active suspension of one-quarter car model. The main role of a car suspension system is to improve the ride comfort and to better the handling property. It usually consists of a spring and a damper to improve the properties of suspension system. The fuzzy logic method is one of the most active research and developments areas on artificial and intelligence at the present time, particularly in the automobile industry. One quarter of car if modeled by springs, masses, dampers and force actuator and the state space equations are derived by lagrangian method. The ride comfort is improved by means of the reduction of the body acceleration caused by the car body when road disturbance from uneven road surfaces, pavement point etc. act on the tires of running car. Here, a logic fuzzy controller is designed in which, the number of rule bases are reduced in comparison with some traditional one which have been introduced in other papers. At the end, a comparison of active suspension fuzzy control and traditional passive suspension is shown using MATLAB simulations. Results show that, active suspension improves the ride comfort by reducing acceleration, compared with the performance of passive suspension.


2017 ◽  
Vol 40 (8) ◽  
pp. 2611-2621 ◽  
Author(s):  
Mingxing Cheng ◽  
Xiaohong Jiao

This paper presents a novel idea processing the complex non-linear dynamics of a magneto-rheological (MR) damper and the external road disturbance based on the linear extended state observer (LESO) technology, and further verifies its reasonability by application of linear active disturbance rejection control (LADRC) in the quarter-car non-linear semi-active suspension system. In order to optimize the body acceleration and dynamic tyre load to improve the ride comfort and road-handling ability, a modified active disturbance rejection control, the double linear active disturbance rejection control (DLADRC), is further proposed based on the idea of the hybrid skyhook–groundhook control strategy. LESO is used to estimate the total disturbance including the external road disturbance and the internal non-linear dynamic of the MR damper. For effectiveness validation of the proposed control scheme, comparison results with the existing linear quadratic regulation (LQR) control, hybrid skyhook–groundhook control and adaptive control strategies are presented for the same quarter-car semi-active suspension. It is shown from the simulation comparisons among these several control strategies that the semi-active suspension system with DLADRC has a better control performance on the ride comfort and road-handling ability corresponding to the body acceleration and dynamic tyre load.


Author(s):  
M. A. Ajaj ◽  
A. M. Sharaf ◽  
S. A. Hegazy ◽  
Y. H. Hossamel-deen

This paper presents a comprehensive investigation of automotive semi-active suspension control algorithms and compares their characteristics in terms of ride comfort and tire-road holding ability. Particular attention has been paid to the semi-active suspension systems fitted with a shock absorber of dual damping characteristics. Different mathematical models are presented to investigate the ride response considering both simplified and complex vehicle models. Numerical simulation has been carried out through the MATLAB/SIMULINK environment which aids the future development of controllable suspension systems to improve vehicle ride comfort. The results show a considerable improvement of the vehicle ride response using different schemes of semi-active suspension system in particular the modified groundhook control algorithm.


Author(s):  
Baek-soon Kwon ◽  
Young-jin Hyun ◽  
Kyongsu Yi

This paper proposes a mode control algorithm of electro-mechanical suspension for vehicle height, attitude control and improvement of ride quality. The proposed control algorithm consists of mode selector, upper-level and lower-level controllers, and suspension state estimator. The mode selector determines the present driving mode using vehicle signals, such as longitudinal speed, steering wheel angle, accelerator pedal position, brake pedal position and vertical acceleration of wheels. The upper-level controller determines the desired suspension state using the present driving mode. The lower-level controller derives the desired stroke speed of the actuator in each suspension by linear quadratic control theory. The suspension state estimator has been designed using accessible sensor measurement by discrete-time Kalman filter theory. The control and estimation algorithms have been developed based on a novel reduced-order vehicle model that includes only the vehicle body dynamics. The model enables the observer to completely remove the effect of unknown road disturbance on the estimation error. The performance of the proposed control algorithm has been evaluated via computer simulation study. The simulation results show that the proposed control algorithm is effective at controlling the electro-mechanical suspension systems. The paper also shows that the considered actuator is suited for vehicle height and levelling control, but not for improvement of ride comfort, due to voltage input constraints.


Author(s):  
Hao Chen ◽  
Mingde Gong ◽  
Dingxuan Zhao ◽  
Jianxu Zhu

This paper proposes an attitude control strategy based on road level for heavy rescue vehicles. The strategy aims to address the problem of poor ride comfort and stability of heavy rescue vehicles in complex road conditions. Firstly, with the pressure of the suspension hydraulic cylinder chamber without a piston rod as the parameter, Takagi–Sugeno fuzzy controller classification and adaptive network-based fuzzy inference system controller classification are used to recognise the road level. Secondly, particle swarm optimisation is adopted to obtain the optimal parameters of the active suspension system of vehicle body attitude control under different road levels. Lastly, the parameters of the active suspension system are selected in accordance with the road level recognised in the driving process to improve the adaptive adjustment capability of the active suspension system at different road levels. Test results show that the root mean square values of vertical acceleration, pitch angle and roll angle of the vehicle body are reduced by 59.9%, 76.2% and 68.4%, respectively. This reduction improves the ride comfort and stability of heavy rescue vehicles in complex road conditions.


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