scholarly journals An Electric Simulator of a Vehicle Transmission Chain Coupled to a Vehicle Dynamic Model

10.5772/7095 ◽  
2010 ◽  
Author(s):  
A. Chaibet ◽  
C. Larouci ◽  
M. Boukhnifer
Keyword(s):  
Dynamic Model ◽  
Vehicle Dynamic ◽  
Transmission Chain ◽  
Vehicle Dynamic Model

Co-Simulation of Power Steering Control and Vehicle Dynamic Responses

2001 ◽  
Author(s):  
Gene Y. Liao
Keyword(s):  
Dynamic Model ◽  
General Purpose ◽  
Dynamic Responses ◽  
Steering Wheel ◽  
Vehicle Dynamic ◽  
Steering Control ◽  
Integrated Simulation ◽  
Full Vehicle ◽  
Power Steering ◽  
Vehicle Dynamic Model

Abstract Many general-purpose and specialized simulation codes are becoming more flexible which allows analyses to be carried out simultaneously in a coupled manner called co-simulation. Using co-simulation technique, this paper develops an integrated simulation of an Electric Power Steering (EPS) control system with a full vehicle dynamic model. A full vehicle dynamic model interacting with EPS control algorithm is concurrently simulated on a single bump road condition. The effects of EPS on the vehicle dynamic behavior and handling responses resulting from steer and road input are analyzed and compared with proving ground experimental data. The comparisons show reasonable agreement on tie-rod load, rack displacement, steering wheel torque and tire center acceleration. This developed co-simulation capability may be useful for EPS performance evaluation and calibration as well as for vehicle handling performance integration.

Investigation on a semi-active hydraulic damping strut to reduce vehicle in situ shift vibration

2019 ◽  
Vol 26 (1-2) ◽  
pp. 3-18
Author(s):  
Dao-Yong Wang ◽  
Wen-Can Zhang ◽  
Xia-Guang Zeng
Keyword(s):  
Dynamic Response ◽  
Dynamic Model ◽  
Automatic Transmission ◽  
Degree Of Freedom ◽  
Vehicle Dynamic ◽  
Response Evaluation ◽  
Evaluation Indexes ◽  
Engine Mount ◽  
Vehicle Dynamic Model

In order to reduce the shock and vibration caused by torque disturbance of the gearbox in vehicles equipped with automatic transmission in the process of in situ shift, a novel semi-active hydraulic damping strut is introduced in the powertrain mounting system. The dynamic response evaluation indexes of vehicle in situ shift are put forward, and a 13-degree of freedom vehicle dynamic model including the semi-active hydraulic damping strut is established. The optimized dynamic characteristic parameters are acquired according to the principle of sharing force and the 13-degree of freedom vehicle dynamic model. The dynamic response evaluation indexes with and without the semi-active hydraulic damping strut are calculated using the 13-degree of freedom vehicle dynamic model in the process of in situ shift, and the calculation results show that the vibration of a vehicle can be reduced by the introduction of a semi-active hydraulic damping strut. Experiments are carried out to analyze the vibration response of the vehicle with and without a semi-active hydraulic damping strut, and the results show that the shock and vibration of the vehicle are reduced by introducing the semi-active hydraulic damping strut. The theoretical calculation values of active-side acceleration of the engine mount and torque strut are consistent with the experimental values, which show that the 13-degree of freedom vehicle dynamic model is reasonable.

Lateral robust iterative learning control for unmanned driving robot vehicle

2020 ◽  
Vol 234 (7) ◽  
pp. 792-808
Author(s):  
Shuhua Su ◽  
Gang Chen
Keyword(s):  
Dynamic Model ◽  
Iterative Learning Control ◽  
Tracking Error ◽  
Learning Control ◽  
Steering System ◽  
Path Tracking ◽  
Iterative Learning ◽  
Control Law ◽  
Vehicle Dynamic ◽  
Vehicle Dynamic Model

In order to achieve stable steering and path tracking, a lateral robust iterative learning control method for unmanned driving robot vehicle is proposed. Combining the nonlinear tire dynamic model with the vehicle dynamic model, the nonlinear vehicle dynamic model is constructed. The structure of steering manipulator of unmanned driving robot vehicle is analyzed, and the kinematics model and dynamics model of steering manipulator of unmanned driving robot vehicle are established. The structure of vehicle steering system is analyzed, and the dynamic model of vehicle steering system is established. Vehicle steering angle model is established by taking vehicle path tracking error and vehicle yaw angle error as input. Combining with the typical iterative learning control law, the robust term is added to the control law, and a robust iterative learning controller for steering manipulator system of unmanned driving robot vehicle is designed. The proposed controller’s stability and astringency are proved. The effectiveness of the proposed method is verified by comparing it with other control methods and human driver simulation tests.

Development of a surrogate-based vehicle dynamic model to reduce computational delays in a driving simulator

SIMULATION ◽  
2016 ◽  
Vol 92 (12) ◽  
pp. 1087-1102 ◽  
Author(s):  
Nariman Fouladinejad ◽  
Nima Fouladinejad ◽  
Mohamad Kasim Abdul Jalil ◽  
Jamaludin Mohd Taib
Keyword(s):  
Real Time ◽  
Dynamic Model ◽  
Surrogate Model ◽  
Driving Simulator ◽  
Computational Time ◽  
Vehicle Dynamic ◽  
Approximation Techniques ◽  
Conventional Vehicle ◽  
Vehicle Simulation ◽  
Vehicle Dynamic Model

The development of a real-time driving simulator involves highly complex integrated and interdependent subsystems that require a large amount of computational time. When advanced hardware is unavailable for economic reasons, achieving real-time simulation is challenging, and thus delays are inevitable. Moreover, computational delays in the response of driving simulator subsystems reduce the fidelity of the simulation. In this paper, we propose a technique to decrease computational delays in a driving simulator. We used approximation techniques, sensitivity analysis, decomposition, and sampling techniques to develop a surrogate-based vehicle dynamic model (SBVDM). This global surrogate model can be used in place of the conventional vehicle dynamic model to reduce the computational burden while maintaining an acceptable accuracy. Our results showed that the surrogate model can significantly reduce computing costs compared to the computationally expensive conventional model. In addition, the response time of the SBVDM is nearly five times faster than the original simulation codes. Also, as a method to reduce hardware cost, the SBVDM was used and the results showed that most of the responses were accurate and acceptable in relation to longitudinal and lateral dynamics. Based on the results, the authors suggested that the proposed framework could be useful for developing low-cost vehicle simulation systems that require fast computational output.

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