Development of a vehicle stability control algorithm using velocity and yaw rate for an in-wheel drive vehicle

Author(s):  
Sungyeon Ko ◽  
Jiwon Ko ◽  
Sangmoon Lee ◽  
Jaeseung Cheon ◽  
Hyunsoo Kim
Author(s):  
Milad Jalali ◽  
Amir Khajepour ◽  
Shih-ken Chen ◽  
Bakhtiar Litkouhi

In this paper, a new approach is proposed to deal with the delay in vehicle stability control using model predictive control (MPC). The vehicle considered here is a rear-wheel drive electric (RWD) vehicle. The yaw rate response of the vehicle is modified by means of torque vectoring so that it tracks the desired yaw rate. Presence of delays in a control loop can severely degrade controller performance and even cause instability. The common approaches for handling delays are often complex in design and tuning or require an increase in the dimensions of the controller. The proposed method is easy to implement and does not entail complex design or tuning process. Moreover, it does not increase the complexity of the controller; therefore, the amount of online computation is not appreciably affected. The effectiveness of the proposed method is verified by means of carsim/simulink simulations as well as experiments with a rear-wheel drive electric sport utility vehicle (SUV). The simulation results indicate that the proposed method can significantly reduce the adverse effect of the delays in the control loop. Experimental tests with the same vehicle also point to the effectiveness of this technique. Although this method is applied to a vehicle stability control, it is not specific to a certain class of problems and can be easily applied to a wide range of model predictive control problems with known delays.


2007 ◽  
Vol 120 ◽  
pp. 223-228
Author(s):  
Dong Hyun Kim ◽  
Sung Ho Hwang ◽  
Hyun Soo Kim

Vehicle stability in 4 wheel drive(4WD) vehicles has been pursued by torque split based technology and brake based technology. The brake based methods are essentially brake maneuver strategies using the active control of the individual wheel brake. By comparison, the torque split based technologies realize stability by varying the traction torque split through powertrain to create an offset yaw moment. In the 4WD hybrid electric vehicle adopting separate front and rear motor, the vehicle stability enhancement algorithm using the rear motor control has some advantages such as faster response, braking energy recuperation, etc. However, since the left and right wheels are controlled by the same driving and regenerative torque from one motor, stability enhancement only by the front and rear motor control has a limitation in satisfying the required offset yaw moment. Therefore, to obtain the demanded offset yaw moment, a brake force distribution at each wheel is required. In this paper, a vehicle stability control logic using the front and rear motor and electrohydraulic brake(EHB) is proposed for a 4WD hybrid electric vehicle. A fuzzy control algorithm is suggested to compensate the error of the sideslip angle and the yaw rate by generating the direct yaw moment. Performance of the vehicle stability control algorithm is evaluated using ADAMS and MATLAB Simulink co-simulation.


ICTIS 2013 ◽  
2013 ◽  
Author(s):  
Jiansen Yang ◽  
Zhanqi Li ◽  
Duanfeng Chu ◽  
Fei Li ◽  
Tianji Feng

Author(s):  
Seyed Hossein Tamaddoni ◽  
Saied Taheri

A new control algorithm and the adaptation laws required for estimation of unknown vehicle parameters have been developed for vehicle stability control (VSC). This algorithm is based on the Lyapunov Direct Method. A vehicle model with two degrees of freedom (DOF) was used to develop the control algorithm. In developing the equations of motion for this simple model, a new approach for introducing the needed stabilizing forces and moments was developed. In addition, an eight DOF model was developed for control algorithm evaluation. The model includes lateral, longitudinal, yaw, and roll motions of the body plus the rotational DOFs for all of the four wheels. Also included in the model is a transient tire model taking into account the tire lateral relaxation length. Using the validated 8 DOF simulation model, the new control algorithm was evaluated and the results show the advantages of using such an approach for enhancing vehicle stability during emergency steering maneuvers.


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