The Application of the Elman Network on the Vehicle Handling Stability Control

2011 ◽  
Vol 199-200 ◽  
pp. 1457-1461 ◽  
Author(s):  
Si Jia Zhou ◽  
Jiang Qi Long ◽  
Ke Gang Zhao
Keyword(s):  
Driving Force ◽  
Control Method ◽  
Control Strategies ◽  
Stability Control ◽  
Vehicle Stability ◽  
Elman Network ◽  
Vehicle Handling ◽  
Combined Control ◽  
One Step ◽  
Tracking Response

In this paper, an expanded Elman network is applied to forecast the vehicle dynamic characteristic and a one step predictive control is also put into use to reinforce its handling stability. The combined control strategy is established based on the conception of the distribution of the driving force between the front and rear driving axles that can be easily achieved in an EV. Moreover, in this research, the distribution proportion of longitudinal driving force defining as a parameter is introduced and the control method of vehicle stability with the aid of the distribution proportion between axles is investigated．Simu1ations have been carried out and the results indicate that the proposed control strategies achieve smooth control effects and rapid target tracking response. This method can be easily applied to the vehicles that are driven by motors, and is capable of improving the lateral dynamic stability of vehicles in most conditions．

A Fuzzy Synthesis Control Scheme and Optimization for Vehicle Dynamic Stability System

2007 ◽  
Author(s):  
Yunqing Zhang ◽  
Si Gao ◽  
Lingyang Li ◽  
Liping Chen ◽  
Jingzhou Yang ◽  
...  
Keyword(s):  
Fuzzy Control ◽  
Control Strategy ◽  
High Speed ◽  
Control Method ◽  
Stability Control ◽  
Surface Model ◽  
Vehicle Stability ◽  
Control Parameters ◽  
Vehicle Dynamic ◽  
Sideslip Angle

Vehicle stability control system can enhance the vehicle stability and handling in the emergency situations through the control of traction and braking forces at the individual wheels. This paper presents a Fuzzy synthesis control strategy with an ideal 2-DOF linear model and optimization of the control parameters. The control strategy consists of Fuzzy control of two control objectives (yaw velocity ω and sideslip angle β). Fuzzy functions can adjust and control these two objectives and through Matlab Fuzzy control unit & ADAMS multi-body vehicle dynamic model we obtain optimized simulation. The co-simulation scenario is on iced road with a single sine steering angle input and in a high speed. The control parameters are optimized and analyzed by a combined optimization algorithm (Genetic Algorithm (GA) and Nonlinear Programming Quadratic Line search (NLPQL) method) combined with response surface model (RSM). The simulation results show that the handling stability and safety of the vehicle can be enhanced by the Fuzzy control method that can adapt complex road and driving conditions.

Research on Vehicle Stability Based on DYC and AFS Integrated Controller

2013 ◽  
Vol 278-280 ◽  
pp. 1510-1515 ◽  
Author(s):  
Jie Tian ◽  
Ya Qin Wang ◽  
Ning Chen
Keyword(s):  
Control Method ◽  
Sliding Mode ◽  
Stability Control ◽  
Front Wheel ◽  
Vehicle Stability ◽  
Sideslip Angle ◽  
Stable Domain ◽  
Vehicle Stability Control ◽  
Integrated Controller ◽  
Yaw Moment

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.

The Simulation Study of the Car Curve Traveling Traction Control System

2013 ◽  
Vol 328 ◽  
pp. 639-643
Author(s):  
Wei Zhao ◽  
Ning Ning Wang ◽  
Yan Yan Duan ◽  
Jian Guo Xi
Keyword(s):  
Neural Network ◽  
Control Method ◽  
Fuzzy Controller ◽  
Stability Control ◽  
Driving Safety ◽  
Slip Angle ◽  
Vehicle Stability ◽  
Force Model ◽  
Slip Ratio ◽  
The Impact

Article on the basis of analysis the impact of changes on the braking force in the tire vertical load and slip angle when the car turns, using the generated neural network force model of the tire, to find the optimum value of the slip ratio of the tire under different parameters. For the case of deviating from the expected running track when the car curve traveling. It puts forward the control strategy of using yaw moment technology to control vehicle stability, vehicle stability fuzzy controller is designed, cars driving in curve conditions are simulated. The results showed that the use of neural network seeks to control of identification of the tire characteristics and longitudinal forces optimal slip rate, can reduce the risk of deviations from the expected running track when cars driving in curve, improve tracking ability of the car driving in curve, it proposed the stability control method for improve driving safety has a certain significance.

Based the Active Defense Substation Domain Strategy Control Method to against Blackout

2014 ◽  
Vol 1070-1072 ◽  
pp. 687-692
Author(s):  
Qing Wei Zhang ◽  
Sheng Yang ◽  
Ying Dai
Keyword(s):  
Control Strategy ◽  
Control Method ◽  
Control Strategies ◽  
Stability Control ◽  
Simulation Software ◽  
System Stability ◽  
Active Defense ◽  
Real Time Analysis ◽  
Strategy Control ◽  
Building Program

In the previous blackout, overload components out of operation often leaded to the expansion of the accident. One active defense substation domain strategy control system was proposed to prevent the N-1 contingencies to N-2 contingencies caused blackout. Through the substation elements states real time analysis , the active defense control strategy was created by learn from the principles and action messages of backup switching equipment, protection and automatic stability control devices. In order to keep the overall system stability, the active defense control strategy was completed by actively put in the standby element or quit part of the overload elements, to make the system into a new equilibrium state. Contrasting these control strategies by PSCAD/EMTDC simulation software, the results presented that this strategy could quickly change the “Close to collapse” zone into the stability states and the building program simple and practical.

Design of Direct Yaw Moment Control System to Enhance Vehicle Stability Based on Fuzzy Logic

2011 ◽  
Vol 383-390 ◽  
pp. 1326-1332 ◽  
Author(s):  
Zhe Xu ◽  
Min Xiang Wei ◽  
Yang Wang ◽  
Jian Wei Wei
Keyword(s):  
Control System ◽  
High Speed ◽  
Control Method ◽  
Reference Value ◽  
Stability Control ◽  
Slip Angle ◽  
Vehicle Stability ◽  
Handling Performance ◽  
Model Following Control ◽  
Yaw Moment

Vehicle running at high speed if affected by crosswind or steering handling may spin or drift out since the yaw moment produced is not big enough to stabilize it. In order to prevent these dangerous situations, a fuzzy direct yaw moment controller is designed in this paper, since it is simple and suitable for nonlinear system. This vehicle stability control system is based on model following control method. The side slip angle and yaw rate which indicate the vehicle’s stability and handling performance are chosen as the control variables. The response of the bicycle model is selected as the reference value. In order to evaluate the performance of the controller, simulations of lane change and J-turn maneuver are carried out. The results show that the stability and handling performance of the vehicle are improved.

Vehicle Steering Stability Simulation Based on G-Vectoring Control

2014 ◽  
Vol 898 ◽  
pp. 914-918
Author(s):  
Yun Yin Zhang ◽  
Chun Guang Liu ◽  
Zi Li Liao
Keyword(s):  
Vehicle Dynamics ◽  
Driving Force ◽  
Control Method ◽  
Stability Control ◽  
Lateral Acceleration ◽  
System Control ◽  
Dynamics Model ◽  
Sideslip Angle ◽  
Vehicle System ◽  
Simulation Based

A new kind of control method named "G-Vectoring control" is used in vehicle steering stability control, which uses the lateral acceleration to control the longitudinal acceleration, and improves the steering stability by redistributing the driving force. The motor and its control system as well as the vehicle system control are modeled by Matlab, the vehicle dynamics model is designed by adams. After the co-simulation of snakelike tests, the results shows that the sideslip angle is well controlled by G-Vectoring control.

Structure Analysis and Pressure Control of Electro-Hydraulic Braking System

2013 ◽  
Vol 760-762 ◽  
pp. 1288-1292 ◽  
Author(s):  
Dong Mei Wu ◽  
Hai Tao Ding ◽  
Kong Hui Guo ◽  
Yang Li ◽  
Hu Zhang
Keyword(s):  
Electric Vehicles ◽  
Pid Control ◽  
Control Method ◽  
Pressure Control ◽  
Stability Control ◽  
Structure Design ◽  
Vehicle Stability ◽  
Braking System ◽  
Vehicle Stability Control ◽  
Braking Energy Recovery

The structure design and pressure control of electro-hydraulic braking system (EHB) is essential for electric vehicles, which is critical to the braking energy recovery and vehicle stability control. In this paper, the overall structure of the electro-hydraulic braking system is analyzed, and classification method according to how the braking pedal is decoupled with the braking pressure is proposed. Through the PID control method to achieve pressure following control, it lays the foundation for electric vehicle stability control.

An Analytical Transient Tire Model

2001 ◽  
Vol 29 (2) ◽  
pp. 108-132 ◽  
Author(s):  
A. Ghazi Zadeh ◽  
A. Fahim
Keyword(s):  
Transient Behavior ◽  
Stability Control ◽  
Vehicle Stability ◽  
Tire Model ◽  
Steering Angle ◽  
First Order ◽  
Vehicle Stability Control ◽  
Proposed Model ◽  
Depth Study ◽  
And Performance

Abstract The dynamics of a vehicle's tires is a major contributor to the vehicle stability, control, and performance. A better understanding of the handling performance and lateral stability of the vehicle can be achieved by an in-depth study of the transient behavior of the tire. In this article, the transient response of the tire to a steering angle input is examined and an analytical second order tire model is proposed. This model provides a means for a better understanding of the transient behavior of the tire. The proposed model is also applied to a vehicle model and its performance is compared with a first order tire model.

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