Improve Vehicle Stability Research Articles

Numerical simulation of bus aerodynamics on several classes of bridge decks

ABSTRACTThis paper is focused on improving traffic safety on bridges under crosswind conditions, as adverse wind conditions can increase the risk of traffic accidents. Two ways to improve traffic safety are investigated: improving vehicle stability by means of wind fences installed on the bridge deck and by modifying the design parameters of the infrastructure. Specifically, this study examines the influence of different parameters related to the bridge deck configuration on the aerodynamic coefficients acting on a bus model under crosswind conditions. The aerodynamic coefficients related to side force, lift force and rollover moment are obtained for three classes of bridge deck (box, girder and board) by numerical simulation. FLUENT was used to solve the Reynolds-averaged Navier–Stokes (RANS) equations along with the shear stress transport (SST) k–ω turbulence model. Two crash barriers located on the box bridge deck were replaced with an articulating wind fence model and the effect of the angle between the wind fence and the horizontal plane on the bus aerodynamic was investigated. The risk of rollover accidents was found to be slightly influenced by the bridge deck type for a yaw angle range between 75° and 120°. In order to study the effect of the yaw angle on the aerodynamic coefficients acting on bus, both the bus model and the bridge model were simultaneously rotated. The minimum value of the rollover coefficient was obtained for an angle of 60° between the wind fence slope and the horizontal plane. The only geometry parameter of the box bridge deck which significantly affects bus aerodynamics is the box height. The present research highlights the usefulness of computational fluid dynamics (CFD) for improving traffic safety, studying the performance of the articulating wind fence, and determining which geometry parameters of the box deck have a significant influence on the bus stability.

A method of evaluating vehicle controllability according to the dynamic factor

The study has explored one of the most important performance properties of the vehicle, which determines road traffic safety, – control in a steady mode. A method has been suggested for evaluating the stability of a vehicle against yaw with regard to the dynamic factor. We have found a dependence of the dynamic factor on the design and operational parameters of the vehicle. The dynamic factor can be reduced through achieving a neutral steering of the vehicle by controlling the ratio of the total lateral rigidity of the tires of the front and rear wheels. It has been determined that a change in the tire air pressure, measured by the developed algorithm, improves vehicle stability against yawing and thus contributes to traffic safety. In the example of the truck Ural-4320, the suggested method was used to determine the total lateral stiffness of the wheels under the condition of ensuring the vehicle’s neutral steering. The study has revealed that in the case of an equipped vehicle it is necessary to reduce the tire pressure in the wheels on the equalizer trolley in correlation to the air pressure in the tires of the front wheels. The research results can be used both in operating the existing vehicles and for designing new ones.

Novel stability control strategy for distributed drive electric vehicle based on driver operation intention

In this paper, a novel direct yaw control method based on driver operation intention for stability control of a distributed drive electric vehicle is proposed. It was discovered that the vehicle loses its stability easily under an emergency steering alignment (EA) problem. An emergent control algorithm is proposed to improve vehicle stability under such a condition. A driver operation intention recognition module is developed to identify the driving conditions. When the vehicle enters into an EA condition, the module can quickly identify it and transfer the control method from normal direct yaw control to emergency control. Two control algorithms are designed. The emergency control algorithm is applied to an EA condition while the adaptive control algorithm is applied to other conditions except the EA condition. Both simulation results and real vehicle results show that: The driver module can accurately identify driving conditions based on driver operation intention. When the vehicle enters into EA condition, the emergent control algorithm can intervene quickly, and it has proven to outperform normal direct yaw control for better stabilization of vehicles.

H 2 control of a one-quarter semi-active ground vehicle suspension

Magneto-rheological (MR) dampers are effective solutions in improving vehicle stability and passenger comfort. However, handling these dampers implies a strong effort in modeling and control. This research proposes an H2 controller, based on a Takagi-Sugeno (T-S) fuzzy model, for a two-degrees-of-freedom (2-DOF) one-quarter vehicle semi-active suspension with an MR damper; a system with important applications in automotive industry. Regarding performance criteria (in frequency domain) handled herein, the developed controller considerably improves the passive suspension's efficiency. Moreover, nonlinear actuator dynamics usually avoided in reported work, is included in controller's synthesis; improving the relevance of research outcomes because the controller is synthesized from a closer-to-reality suspension model. Going further, outcomes of this research are compared (based on frequency domain performance criteria and a common time domain test) with reported work to highlight the outstanding results. H2 controller is given in terms of quadratic Lyapunov stability theory and carried out by means of Linear Matrix Inequalities (LMI), and the command signal is applied via the Parallel Distributed Compensation (PDC) approach. A case of study, with real data, is developed and simulation work supports the results. The methodology applied herein can be extended to include other vehicle suspension's dynamics towards a general chassis control

Electronic Stability Control Based on Motor Driving and Braking Torque Distribution for a Four In-Wheel Motor Drive Electric Vehicle

An electronic stability control (ESC) algorithm is proposed for a four in-wheel motor independent-drive electric vehicle (4MIDEV) utilizing motor driving and regenerative braking torque distribution control to improve vehicle stability. A stability judgment controller, an upper level controller, and a torque distribution algorithm are designed for the ESC system. The stability judgment controller is designed to generate the desired yaw rate and sideslip angle for vehicle stability, and the control mode, which is normal driving mode or ESC mode, is set according to the driver inputs and measurement signal inputs. The upper level controller consists of a speed tracking controller, a yaw moment controller, and four wheel-slip controllers to calculate the desired value of traction force, the desired value of yaw moment, and the four respective net torque inputs of the four in-wheel motors. The torque distribution algorithm is designed to generate each motor driving torque or regenerative braking torque input for each wheel. An average torque distribution strategy, a tire-dynamic-load-based torque distribution strategy, and a minimum-objective-function-based optimal torque distribution strategy are used separately in the torque distribution algorithm to control the motor driving torque or regenerative braking torque for vehicle stability enhancement. The proposed ESC algorithm was implemented and evaluated in a CarSim vehicle model and a MATLAB/Simulink control model. The three proposed torque distribution strategies can be used to regulate the vehicle to perform the following tasks: “single lane change,” “double lane change,” and “snake lane change.” The simulation studies show that the yaw rate error root mean square [RMS $(\gamma-\gamma_\mathrm{-des})$ ] decreased, on average, by 75 percent using the proposed optimal torque distribution algorithm compared with that without using stability control.

Multi-objective Optimisation of McPherson Strut Suspension Mechanism Kinematics Using Random Search Method

McPherson suspension mechanism is one of the widespread mounted mechanisms in front axle of Front Wheel Drive (FWD) vehicles with transverse engine. In this study the kinematics of McPherson suspension mechanism is optimised in order to achieve the desired kinematic behavior and improve vehicle stability. First, the mechanism was modeled in Mechanical Desktop software package and the model transferred to Working Model 3D software for kinematic analysis. Then results of kinematic simulation compared to design criteria and as target function is established, by choosing the optimal amount of optimisation variables the amount of cost function has been minimized. Because of simple implementability and also because of having the least influence on other specifications of the vehicle, the spatial location of joints selected as optimisation variables and changing range of variables is set in a rational interval. The aforementioned procedure done for determined numbers of iteration by use of Random Search Method to obtain the optimum results. Results show that the employed method has the ability to optimise the mechanism kinematics in suitable spent time. In addition, it is seen that after optimisation the alteration of toe angle, camber angle, and track width were improved noticeably. Finally, in order to validation the optimised mechanism modeled in ADAMS.

Adaptive integrated control design for vehicle dynamics using phase-plane analysis

This study designs an adaptive integrated control. The control system includes two strategies of individual optimal linear quadratic regulator: one to improve vehicle maneuverability and another to improve vehicle stability. The integration is based on the vehicle dynamic variables in the phase plane. The controller can adapt itself by changing gains and integration law as vehicle mass and road friction change. The proper gains and integration law are determined for four special conditions: dry road-curb weight, dry road-gross weight, wet road-curb weight, and wet road-gross weight. These conditions are then expanded for every value of vehicle mass and road friction through fuzzy logic and Sugeno estimator. Simulation results show that considerable improvements are achieved in vehicle dynamic performance through the adaptive integrated control system.

A video based run-off-road training program with practice and evaluation in a simulator

A run-off-road (ROR) event occurs when one or more of a vehicle’s wheels leaves the roadway and begins to travel on the surface or shoulder adjacent to the road. Despite various countermeasures, ROR crashes continue to yield a large number of fatalities and injuries. Infrastructure-based solutions do not directly address the critical factor of driver performance preceding and during an ROR event. In this study, a total of 75 individuals participated in a pre–post experiment to examine the effect of a training video on improving driver performance during a set of simulated ROR scenarios (e.g., on a high speed highway, a horizontal curve, and a residential rural road). In each scenario, the vehicle was unexpectedly forced into an ROR scenario for which the drivers were instructed to recover as safely as possible. The treatment group then watched a custom ROR training video while the control group viewed a placebo video. The participants then drove the same simulated ROR scenarios. The results suggest that the training video had a significant positive effect on drivers’ steering response on all three roadway conditions as well as improvements in vehicle stability, subjectively rated demand on the driver, and self-evaluated performance in the highway scenario. Under the highway conditions, the treatment group reduced the frequency of spinouts from 70% in the pre-training events to 16% in the post-training events (χ2(1)=23.32, p<0.001) with no significant improvement found for the control group. In the horizontal curve, spinouts were reduced for the treatment group from 50% in the pre-training events to 30% in the post-training events (χ2(1)=8.45, p=0.004) with the control group also not showing any significant improvement. The results of this study suggest that even a short video about recovering from ROR events can significantly influence a driver’s ability to recover. It is possible that additional training may have further benefits in recovering from ROR events.

Optimal Distribution Control Of Non‐Linear Tire Force Of Electric Vehicles With In‐Wheel Motors

AbstractAn over‐actuated control system has the advantage of being able to use redundant actuators to reconfigure the control system and it can realize fault tolerant control. In order to achieve improved vehicle stability and handling performance for electric vehicles with in‐wheel steering and driving motors, the control of the vehicle body slip angle and yaw rate is actually an over‐actuated control problem. To obtain the optimal solution for this control problem, this study proposes a two‐level tire force distribution control method, where the upper level controller calculates the desired lateral and longitudinal forces generated by friction on the tire of each wheel according to the driver's steering and driving inputs. The lower level controller maps the desired tire forces into the input of each steering actuator and driving actuator. Unlike the linear mapping method applied in most of the current research, this study develops a proportional‐integral (PI) controller for each actuator so that the non‐linear tire characteristics can be counteracted. In addition, since the PI controllers for eight actuators (four steering actuators and four driving actuators) have a total of 16 control gains to be determined, a genetic algorithm is applied to accurately determine these control gains. The simulation results are presented to validate the control performance of the proposed tire force allocation method.

Constrained [formula omitted] control for road vehicles after a tire blow-out

Sudden tire blow-out of a road vehicle is a hazardous situation and frequently cited as the cause of a crash and fatality on the highway. As the uncertainties/disturbances caused by a tire blow-out are difficult to be measured or estimated, this study proposes a novel constrained H∞ coordinated control approach for the path-following and driving stability problem of the road vehicles after a tire blow-out. Simulation results and analyses for a variety of driving scenarios are conducted, based on a co-simulation between the proposed vehicle controller and vehicle dynamics simulation platform veDYNA. The dynamic analyses clearly demonstrate the effectiveness of the proposed coordinated controller in improving vehicle stability, as well as the robustness of the controller against the uncertainties/disturbances caused by a tire blow-out.

A novel integrated chassis controller for full drive-by-wire vehicles

In this paper, a systematic design with multiple hierarchical layers is adopted in the integrated chassis controller for full drive-by-wire vehicles. A reference model and the optimal preview acceleration driver model are utilised in the driver control layer to describe and realise the driver's anticipation of the vehicle's handling characteristics, respectively. Both the sliding mode control and terminal sliding mode control techniques are employed in the vehicle motion control (MC) layer to determine the MC efforts such that better tracking performance can be attained. In the tyre force allocation layer, a polygonal simplification method is proposed to deal with the constraints of the tyre adhesive limits efficiently and effectively, whereby the load transfer due to both roll and pitch is also taken into account which directly affects the constraints. By calculating the motor torque and steering angle of each wheel in the executive layer, the total workload of four wheels is minimised during normal driving, whereas the MC efforts are maximised in extreme handling conditions. The proposed controller is validated through simulation to improve vehicle stability and handling performance in both open- and closed-loop manoeuvres.

Vehicle Stability Integrated Control Based on Adaptive Optimal Approach

An adaptive optimal control system for vehicle stability integrated control was proposed based on a hierarchical integrated control system. The generalized lateral force and moment required to achieve vehicle motion was calculated based on sliding mode control method. Through the control allocation, the desired yaw moment will be properly distributed to each wheel by using nonlinear weighted least-squares (WLS) algorithm . The simulation results show that the proposed control system can effectively improve vehicle stability and handling performances by taking full advantage of the tire force.

A study on tyre force distribution controls for full drive-by-wire electric vehicle

Feed-forward types of tyre force distribution controls with some norms for motion controls of a full drive-by-wire electric vehicle are presented. One of the norms for the distribution control introduced is minimising tyre workload and another one is minimising tyre dissipation energy due to tyre slip during vehicle motion. The effects of the distribution controls are substantiated using an experimental vehicle on a proving ground. Especially the effects of the tyre force distribution norms on improving vehicle stability and on reducing the tyre energy dissipation caused by tyre slip are investigated.

Improving Vehicle Lateral Stability Based on Variable Stiffness and Damping Suspension System via MR Damper

The capability of a variable stiffness and damping (VSVD) suspension system via a magnetorheological (MR) damper on improving vehicle lateral stability is investigated in this paper. First, a type of the VSVD suspension system is briefly introduced with the application of variable damping to realize the capability of VSVD. Then, variable damping via the MR damper is extended, and the characteristics of damping force are presented with the Bouc-Wen model. Then, the proposed VSVD system is inserted into a full vehicle model as a front suspension system to control tire normal forces. A control strategy composed of a fuzzy controller that the output is wheel slip ratio and a simple on/off controller to model the application of VSVD is developed to illustrate its ability in improving vehicle stability. It is shown from simulation that VSVD can increase tire normal forces and make vehicles present better performance on lateral stability.

Advanced Motion Control of Electric Vehicles Based on Robust Lateral Tire Force Control via Active Front Steering

This paper presents a new motion control method based on robust lateral tire force control (LTFC) to improve vehicle stability or maneuverability. During cornering, vehicle motion is totally governed by lateral forces acting on tires. Thus, the real-time information on tire forces provides advantages in vehicle motion control. Since the lateral tire force measurements are available by using multisensing hub (MSHub) units which were invented by NSK Ltd., the direct LTFC is realizable via active front steering. In control design, a robust control method, e.g., two degree-of-freedom control (2-DOF) with a disturbance observer, is used for improving the reference tracking performance. Moreover, the stability of the proposed control system is discussed by using small gain theorem. The proposed motion controller is implemented on an experimental in-wheel-motor-driven electric vehicle and its performance and effectiveness are verified by field tests. Finally, practical applications of lateral tire force sensors to vehicle motion control systems are discussed.

A Study on In-wheel Motor Control to Improve Vehicle Stability Using Human-in-the-Loop Simulation

In this study, an integrated motor control algorithm for an in-wheel electric vehicle is suggested. It consists of slip control that controls the in-wheel motor torque using the road friction coefficient and slip ratio; yaw rate control that controls the in-wheel motor torque according to the road friction coefficient and the yaw rate error; and velocity control that controls the vehicle velocity by a weight factor based on the road friction coefficient and the yaw rate error. A co-simulator was developed, which combined the vehicle performance simulator based on MATLAB/Simulink and the vehicle model of CarSim. Based on the co-simulator, a human-in-the-loop simulation environment was constructed, in which a driver can directly control the steering wheel, the accelerator pedal, and the brake pedal in real time. The performance of the integrated motor control algorithm for the in-wheel electric vehicle was evaluated through human-in-the-loop simulations.

Research on Vehicle Stability Based on DYC and AFS Integrated Controller

A new vehicle stability control method integrated direct yaw moment control (DYC) with active front wheel steering (AFS) was proposed. On the basis of the vehicle nonlinear model, vehicle stable domain was determined by the phase plane of sideslip angle and sideslip angular velocity. When the vehicle was outside the stable domain, DYC was firstly used to produce direct yaw moment, which can make vehicle inside the stable domain. Then AFS sliding mode control was used to make the sideslip angle and yaw rate track the reference vehicle model. The simulation results show that the integrated controller improves vehicle stability more effectively than using the AFS controller alone.

Development of Integrated Control of Electronic Stability Control, Continuous Damping Control and Active Anti-Roll Bar for Vehicle Yaw Stability

This paper describes an investigation into coordinated control of electronic stability control (ESC), continuous damping control (CDC) and active roll control system (ARC). The coordinated control is suggested to improve the vehicle stability and agility features by yaw rate control. At first, the relation of roll moment distribution and yaw dynamics is analyzed based on simplified tire model. The proposed integrated chassis control algorithm consists of a supervisor, control algorithms, and a coordinator. The supervisor monitors the vehicle status and determines desired vehicle motions such as a desired yaw rate and desired roll motion based on control modes to improve vehicle stability. According to the corresponding the desired vehicle dynamics, the control algorithm calculated a desired yaw moment and desired roll moment, respectively. Based on the desired yaw moment and the desired roll moment, the coordinator determines the brake pressures, the ARC motor torques and damper current based on control strategies. The ARC motor torque has been calculated to generate the roll moment and yaw moment simultaneously. Closed loop simulations with a driver-vehicle-controller system were conducted to investigate the performance of the proposed control strategy using CarSim vehicle dynamics software and the integrated controller coded using Matlab/Simulink.

Study on Vehicle Stability Based on Coordinated Control of Direct Yaw Moment Control and Slip Rate Control

A coordinated control strategy based on Direct Yaw Moment Control (DYC) and slip rate control was proposed aiming at improving vehicle stability. The system was divided into two layers: an upper layer and a lower layer. DYC was the upper-layer control, which calculates the additional yaw moment exerted on the vehicle based on the working condition of the vehicle. A simplified arithmetic of transferring additional yaw moment to desired slip rate was adopted in order to achieve differential braking. Slip rate controller was the lower-layer control that exerts braking force on the braking wheels to achieve the desired slip rate and to achieve desired yaw moment.

Vehicle dynamics control of four in-wheel motor drive electric vehicle using gain scheduling based on tyre cornering stiffness estimation

This paper focuses on the vehicle dynamic control system for a four in-wheel motor drive electric vehicle, aiming at improving vehicle stability under critical driving conditions. The vehicle dynamics controller is composed of three modules, i.e. motion following control, control allocation and vehicle state estimation. Considering the strong nonlinearity of the tyres under critical driving conditions, the yaw motion of the vehicle is regulated by gain scheduling control based on the linear quadratic regulator theory. The feed-forward and feedback gains of the controller are updated in real-time by online estimation of the tyre cornering stiffness, so as to ensure the control robustness against environmental disturbances as well as parameter uncertainty. The control allocation module allocates the calculated generalised force requirements to each in-wheel motor based on quadratic programming theory while taking the tyre longitudinal/lateral force coupling characteristic into consideration. Simulations under a variety of driving conditions are carried out to verify the control algorithm. Simulation results indicate that the proposed vehicle stability controller can effectively stabilise the vehicle motion under critical driving conditions.