scholarly journals Predictive Control Using Active Aerodynamic Surfaces to Improve Ride Quality of a Vehicle

Electronics ◽  
2020 ◽  
Vol 9 (9) ◽  
pp. 1463
Author(s):  
Ejaz Ahmad ◽  
Jamshed Iqbal ◽  
Muhammad Arshad Khan ◽  
Wu Liang ◽  
Iljoong Youn
Keyword(s):  
Predictive Control ◽  
Control Strategy ◽  
Ride Comfort ◽  
Tracking Error ◽  
Vehicle Body ◽  
Ride Quality ◽  
Radius Of Curvature ◽  
Attitude Motion ◽  
Road Disturbance ◽  
Aerodynamic Surfaces

This work presents a predictive control strategy for a four degrees of freedom (DOF) half-car model in the presence of active aerodynamic surfaces. The proposed control strategy consists of two parts: the feedback control deals with the tracking error while the feedforward control handles the anticipated road disturbance and ensures the desired maneuvering. The desired roll and pitch angles are obtained by using disturbance, vehicle speed and radius of curvature. The proposed approach helps the vehicle to achieve better ride comfort by suppressing the amplitude of vibrations occurring in the vertical motion of the vehicle body, and enhances the road-holding capability by overcoming the amplitude of vibrations in tyre deflection. The control strategy also cancels out the hypothetical forces acting on the vehicle body to help the vehicle to track the desired attitude motion without compromising the ride comfort and road-holding capability. The simulations results show that the proposed control strategy successfully reduces the root mean square error (RMSE) values of sprung mass acceleration as well as tyre deflection.

Model Predictive Control Application to Flexible-Bodied Railway Vehicles for Vibration Suppression

2013 ◽  
Vol 10 ◽  
pp. 25-35
Author(s):  
P.E. Orukpe
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
High Speed ◽  
Ride Comfort ◽  
The Body ◽  
Ride Quality ◽  
Linear Matrix ◽  
Railway Vehicle ◽  
Railway Vehicles ◽  
Effective Manner

In this paper, we apply model predictive control (MPC) based on mixed H2/H to active vibration control of the flexibility of railway vehicle to improve ride quality. However, the flexibility in the body of high-speed railway vehicles creates difficulties which in practice may result in the body structure being heavier than what it is supposed to be. The use of active suspension helps to model the vehicle and its flexibility in an effective manner. Conventional control approaches are compared with linear matrix inequality MPC technique using flexible-bodied railway vehicle as an example. The result indicates that the MPC technique performs better in improving ride comfort compared to the passive and classical techniques when flexible modes are present.

Mixed H2/H∞ with Pole-Placement Control Design Outline for Active Suspension Systems

2014 ◽  
Vol 663 ◽  
pp. 152-157
Author(s):  
Aghil Shavalipour ◽  
Sallehuddin Mohamed Haris
Keyword(s):  
State Space ◽  
Ride Comfort ◽  
Control Method ◽  
Space Vehicle ◽  
Active Suspension ◽  
Optimization Techniques ◽  
Pole Placement ◽  
Vehicle Body ◽  
Linear Matrix ◽  
Road Disturbance

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.

Energy Harvesting, Ride Comfort, and Road Handling of Regenerative Vehicle Suspensions

2013 ◽  
Vol 135 (1) ◽  
Author(s):  
Lei Zuo ◽  
Pei-Sheng Zhang
Keyword(s):  
Energy Harvesting ◽  
Ride Comfort ◽  
Average Power ◽  
Great Influence ◽  
Vehicle Body ◽  
Ride Quality ◽  
Road Roughness ◽  
Tire Stiffness ◽  
Suspension Stiffness ◽  
The Mean

This paper presents a comprehensive assessment of the power that is available for harvesting in the vehicle suspension system and the tradeoff among energy harvesting, ride comfort, and road handing with analysis, simulations, and experiments. The excitation from road irregularity is modeled as a stationary random process with road roughness suggested in the ISO standard. The concept of system H2 norm is used to obtain the mean value of power generation and the root mean square values of vehicle body acceleration (ride quality) and dynamic tire-ground contact force (road handling). For a quarter car model, an analytical solution of the mean power is obtained. The influence of road roughness, vehicle speed, suspension stiffness, shock absorber damping, tire stiffness, and the wheel and chasses masses to the vehicle performances and harvestable power are studied. Experiments are carried out to verify the theoretical analysis. The results suggest that road roughness, tire stiffness, and vehicle driving speed have great influence on the harvesting power potential, where the suspension stiffness, absorber damping, and vehicle masses are insensitive. At 60 mph on good and average roads, 100–400 W average power is available in the suspensions of a middle-sized vehicle.

Mode control of electro-mechanical suspension systems for vehicle height, levelling and ride comfort

2019 ◽  
Vol 234 (2-3) ◽  
pp. 792-809
Author(s):  
Baek-soon Kwon ◽  
Young-jin Hyun ◽  
Kyongsu Yi
Keyword(s):  
Control Algorithm ◽  
Ride Comfort ◽  
Vehicle Body ◽  
State Estimator ◽  
Driving Mode ◽  
Suspension Systems ◽  
Mode Control ◽  
Road Disturbance ◽  
Upper Level ◽  
Mechanical Suspension

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.

Body attitude control strategy based on road level for heavy rescue vehicles

2020 ◽  
pp. 095440702096616
Author(s):  
Hao Chen ◽  
Mingde Gong ◽  
Dingxuan Zhao ◽  
Jianxu Zhu
Keyword(s):  
Control Strategy ◽  
Attitude Control ◽  
Ride Comfort ◽  
Active Suspension ◽  
Suspension System ◽  
Vehicle Body ◽  
Vertical Acceleration ◽  
Inference System ◽  
The Road ◽  
Body Attitude

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.

Energy Harvesting, Ride Comfort, and Road Handling of Regenerative Vehicle Suspensions

2011 ◽  
Author(s):  
Lei Zuo ◽  
Pei-Sheng Zhang
Keyword(s):  
Energy Harvesting ◽  
Ride Comfort ◽  
Average Power ◽  
Great Influence ◽  
Vehicle Body ◽  
Ride Quality ◽  
Vehicle Speed ◽  
Road Roughness ◽  
Tire Stiffness ◽  
Suspension Stiffness

This paper presents a comprehensive assessment of the power that is available for harvesting in the vehicle suspension system and the tradeoff among energy harvesting, ride comfort, and road handing with analysis, simulations and experiments. The excitation from road irregularity is modeled as a stationary random process with road roughness suggested in the ISO standard. The concept of system H2 norm is used to obtain mean value of power generation and the root mean square values of vehicle body acceleration (ride quality) and dynamic tire-ground contact force (road handling). For a quarter car model, analytical solution of the mean power is obtained. The influence of road roughness, vehicle speed, suspension stiffness, shock absorber damping, tire stiffness, wheel and chasses masses to the vehicle performances and harvestable power are studied. Experiments are carried out to verify the theoretical analysis. The results suggest that road roughness, tire stiffness, and vehicle driving speed have great influence to the harvesting power potential, where the suspension stiffness, absorber damping, vehicle masses are insensitive. At 60mph on good and average roads 100–400 watts average power is available in the suspensions of a middle-size vehicle.

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

2019 ◽  
Vol 234 (6) ◽  
pp. 1725-1745
Author(s):  
Baek-soon Kwon ◽  
Daejun Kang ◽  
Kyongsu Yi
Keyword(s):  
Simulation Study ◽  
Control Algorithm ◽  
Ride Comfort ◽  
Active Suspension ◽  
The Body ◽  
Vehicle Body ◽  
Preview Control ◽  
The Road ◽  
Road Disturbance ◽  
Suspension Control

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.

Potential field–based hierarchical adaptive cruise control for semi-autonomous electric vehicle

2018 ◽  
Vol 233 (10) ◽  
pp. 2479-2491 ◽  
Author(s):  
Yue Ren ◽  
Ling Zheng ◽  
Wei Yang ◽  
Yinong Li
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Potential Field ◽  
Adaptive Cruise Control ◽  
Ride Comfort ◽  
Tracking Error ◽  
Driving Safety ◽  
Vehicle Speed ◽  
Cruise Control ◽  
Collision Risk

Adaptive cruise control, as a driver assistant system for vehicles, can adjust the vehicle speed to keep the appropriate distance from other vehicles, which highly increases the driving safety and driver’s comfort. This paper presents hierarchical adaptive cruise control system that could balance the driver’s expectation, collision risk, and ride comfort. In the adaptive cruise control structure, there are two controllers to achieve the function. The one is the upper controller which is established based on the model predictive control theory and used to calculate the desirable longitudinal acceleration. The collision risk is described by the Gaussian distribution. A quadratic cost function for model predictive control is formulated based on the potential field method through the contradictions between the tracking error, collision risk, and the longitudinal ride comfort. The other one is the lower optimal torque vectoring controller which is constructed based on the vehicle longitudinal dynamics. And it can generate the desired acceleration considering the anti-wheel slip limitations. Several simulations under different road conditions demonstrate that the proposed adaptive cruise control has significant performance on balancing the tracking ability, collision avoidance, ride comfort, and adhesion utilization. It also maintains vehicle stability for the complex road conditions.

Combined CNF with LQR in Improving Ride and Handling for Ground Vehicle

2014 ◽  
Vol 575 ◽  
pp. 749-752 ◽  
Author(s):  
Noraishikin Zulkarnain ◽  
Hairi Zamzuri ◽  
Saiful Amri Mazlan
Keyword(s):  
Control Strategy ◽  
Ride Comfort ◽  
Dynamic Modelling ◽  
Performance Comparison ◽  
Roll Angle ◽  
Vehicle Body ◽  
Nonlinear Feedback ◽  
Linear Quadratic ◽  
Composite Nonlinear Feedback ◽  
Roll Rate

This paper presents and analyses a performance comparison between a Linear Quadratic Regulator (LQR) and Composite Nonlinear Feedback (CNF) controllers for an active anti-roll bar (ARB) system. The anti-roll bar system has to balance the trade-off involving ride comfort and handling performance. The basic vehicle dynamic modelling with four degree of freedom (DOF) on half car model is proposed. The design model is validity and the performances of roll angle and roll rate under control of LQR and CNF controller are achieved by using simulation analysis. 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 to achieve this goal. The result shows, the CNF LQR fusion control strategy improve the performance compared to LQR and CNF control strategy.

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