scholarly journals Active Suspension Control Based on Estimated Road Class for Off-Road Vehicle

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.

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.


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.


2014 ◽  
Vol 644-650 ◽  
pp. 952-956 ◽  
Author(s):  
Hao Yang ◽  
An Qing You ◽  
Wen Wu Pan ◽  
Hai Long Tang

For vehicle-borne LiDAR, a mathematical model is built for the computation and reconstruction of laser point cloud with the scanning data, GPS data and IMU data. 3D point cloud of the road and the scenery on the both sides of the road is obtained. Then according to the trajectory of the vehicle, 3D roaming for the scenery on the both sides of the road is realized using OpenGL 3D engine technology. This technology provides a probably feasible way for anti-collision of vehicles and aircrafts when driven at night, in the heavy fog or flying between the mountains.


2021 ◽  
Vol 69 (6) ◽  
pp. 485-498
Author(s):  
Felix Anhalt ◽  
Boris Lohmann

Abstract By applying disturbance feedforward control in active suspension systems, knowledge of the road profile can be used to increase ride comfort and safety. As the assumed road profile will never match the real one perfectly, we examine the performance of different disturbance compensators under various deteriorations of the assumed road profile using both synthetic and measured profiles and two quarter vehicle models of different complexity. While a generally valid statement on the maximum tolerable deterioration cannot be made, we identify particularly critical factors and derive recommendations for practical use.


Sensors ◽  
2020 ◽  
Vol 20 (6) ◽  
pp. 1573 ◽  
Author(s):  
Haojie Liu ◽  
Kang Liao ◽  
Chunyu Lin ◽  
Yao Zhao ◽  
Meiqin Liu

LiDAR sensors can provide dependable 3D spatial information at a low frequency (around 10 Hz) and have been widely applied in the field of autonomous driving and unmanned aerial vehicle (UAV). However, the camera with a higher frequency (around 20 Hz) has to be decreased so as to match with LiDAR in a multi-sensor system. In this paper, we propose a novel Pseudo-LiDAR interpolation network (PLIN) to increase the frequency of LiDAR sensor data. PLIN can generate temporally and spatially high-quality point cloud sequences to match the high frequency of cameras. To achieve this goal, we design a coarse interpolation stage guided by consecutive sparse depth maps and motion relationship. We also propose a refined interpolation stage guided by the realistic scene. Using this coarse-to-fine cascade structure, our method can progressively perceive multi-modal information and generate accurate intermediate point clouds. To the best of our knowledge, this is the first deep framework for Pseudo-LiDAR point cloud interpolation, which shows appealing applications in navigation systems equipped with LiDAR and cameras. Experimental results demonstrate that PLIN achieves promising performance on the KITTI dataset, significantly outperforming the traditional interpolation method and the state-of-the-art video interpolation technique.


Author(s):  
M Montazeri-Gh ◽  
M Soleymani

Optimization of a vehicle fuzzy active suspension (AS) controller was previously performed on the basis of the amplitude of transmitted vibrations to the body. However, ride comfort depends strongly on the human sensitivity, which is a function of not only the amplitude but also the frequency contents of the transmitted vibrations. In this paper, genetic optimization of a fuzzy AS system based on the human sensitivity to the transmitted vibrations is presented. For this purpose, a fuzzy logic controller (FLC) is initially proposed for the AS system control. The FLC parameters are then tuned using a genetic algorithm (GA). The tuning process is first formulated as a single-objective optimization problem based on the human sensitivity and conventional r.m.s. amplitude criteria separately. The simulation results reveal that the optimization of a fuzzy AS based on the common r.m.s. amplitude criterion not only does not result in the optimal ride index, but also causes a considerable increase in the energy consumption. Moreover, in order to accommodate the conflicting characteristics of the AS system, the FLC parameters are tuned on the basis of a multi-objective fitness function incorporating human sensitivity, suspension travel, and energy consumption. The simulation results prove the effectiveness of the optimized FLC in hitting the simultaneous targets of ride comfort improvement as well as suspension travel and energy consumption reduction.


Author(s):  
Mohammad Javad Mahmoodabadi ◽  
Mohammad Javanbakht

This paper presents optimal adaptive fuzzy approaches combined by the predictive models for five degrees of freedom vehicle systems having a control force constraint of 1000 N on both front and rear suspensions in order to minimize the road disturbances. First, two separate adaptive fuzzy controllers are designed for the rear and front tires using the singleton fuzzifier, center average defuzzifier and product inference engine. The constructed fuzzy systems implement the adaptation laws based on the Lyapunov theory to guarantee the stability of the system. Afterward, a gravitational search optimization algorithm is applied to calculate the optimal values of the controller’s gains. The weighted summation of four objectives, as the relative displacement between the sprung mass and the front tire, the relative displacement between the sprung mass and the rear tire, the acceleration of the body and the acceleration of the seats, are regarded in the optimization process. Two different predictive models are employed to find the optimal design variables for the circumstances where the stability of the system is under variation. The first model is a fuzzy predictive system while the second one is based on the moving least squares interpolation. Eventually, the resultant online models are compared with the offline systems when the vehicle mass varies. These simulations obviously illustrate the efficiency and ability of the suggested strategy to remove the effect of the road disturbances on the ride comfort.


Author(s):  
Chengleng Han ◽  
Lin Xu ◽  
Junyi Zou ◽  
Mohamed AA Abdelkareem ◽  
Enkang Cui

This paper designs and manufactures a new type of arm suspension institution named In-Arm Torsional Electromagnetic Active Suspension (ITEAS) according to the structure and characteristic. The paper introduces the function and application scenarios of ITEAS and narrates the research value and scientific significance of the system. At first, the structure and principle of ITEAS are presented briefly, based on which the mathematical model of ITEAS suspension and height adjustment is built and analyzed. Next, the paper studies three critical components of ITEAS respectively. The mathematical solution is found to calculate the stiffness of the torsion bar. The structure and hydrodynamic model of the vane damper is researched, and the simulation model of the absorber is built in AMESim. The paper studies the theoretical principle of height adjustment and obtains the frequency characteristic of “Motor-Load” through the transfer function solved in MATLAB. Therefore, simulation models are built in AMESim in allusion to the three functions in the next chapter to verify the suspension characteristic, the height adjustment and the active displacement control of ITEAS independently. At last, several experiments are conducted on the test bench to check the feasibility of ITEAS. The results show that ITEAS is capable of being used as a vehicle suspension system and has a good impact on mitigation ability under road surface excitation, which enables us to adjust the body height and control the displacement actively according to the road condition.


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.


2008 ◽  
Vol 15 (5) ◽  
pp. 493-503 ◽  
Author(s):  
S. Hossein Sadati ◽  
Salar Malekzadeh ◽  
Masood Ghasemi

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.


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