scholarly journals An Optimization Design of Adaptive Cruise Control System Based on MPC and ADRC

Actuators ◽  
2021 ◽  
Vol 10 (6) ◽  
pp. 110
Author(s):  
Zengfu Yang ◽  
Zengcai Wang ◽  
Ming Yan
Keyword(s):  
Dynamic Model ◽  
Optimization Design ◽  
Adaptive Cruise Control ◽  
External Disturbance ◽  
Vehicle Dynamic ◽  
Cruise Control ◽  
The Road ◽  
Control Precision ◽  
Compensatory Control ◽  
Vehicle Dynamic Model

In this paper, a novel adaptive cruise control (ACC) algorithm based on model predictive control (MPC) and active disturbance rejection control (ADRC) is proposed. This paper uses an MPC algorithm for the upper controller of the ACC system. Through comprehensive considerations, the upper controller will output desired acceleration to the lower controller. In addition, to increase the accuracy of the predictive model in the MPC controller and to address fluctuations in the vehicle’s acceleration, an MPC aided by predictive estimation of acceleration is proposed. Due to the uncertainties of vehicle parameters and the road environment, it is difficult to establish an accurate vehicle dynamic model for the lower-level controller to control the throttle and brake actuators. Therefore, feed-forward control based on a vehicle dynamic model (VDM) and compensatory control based on ADRC is used to enhance the control precision and to suppress the influence of internal or external disturbance. Finally, the proposed optimal design of the ACC system was validated in road tests. The results show that ACC with APE can accurately control the tracking of the host vehicle with less acceleration fluctuation than that of the traditional ACC controller. Moreover, when the mass of the vehicle and the slope of the road is changed, the ACC–APE–ADRC controller is still able to control the vehicle to quickly and accurately track the desired acceleration.

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.

A First Investigation of Truck Drivers’ Preferences and Behaviors using a Prototype Cooperative Adaptive Cruise Control System

2018 ◽  
Vol 2672 (34) ◽  
pp. 39-48 ◽  
Author(s):  
Shiyan Yang ◽  
Steven E. Shladover ◽  
Xiao-Yun Lu ◽  
Hani Ramezani ◽  
Aravind Kailas ◽  
...  
Keyword(s):  
Adaptive Cruise Control ◽  
Aerodynamic Drag ◽  
Truck Drivers ◽  
Cruise Control ◽  
Fuel Savings ◽  
The Road ◽  
Cooperative Adaptive Cruise Control ◽  
And Behaviors ◽  
On The Road ◽  
And Performance

Cooperative adaptive cruise control (CACC) is a driver-assist technology that uses vehicle-to-vehicle wireless communication to realize faster braking responses in following vehicles and shorter headways compared with adaptive cruise control. This technology not only enhances road safety, but also offers fuel savings benefits as a result of reduced aerodynamic drag. The amount of fuel savings is dictated by the following distances and the driving speeds. So, the overarching goal of this work is to explore driving preferences and behaviors when following in “CACC mode,” an area that remains largely unexplored. While in CACC mode, the brake and throttle actions are automated. A human factors study was conducted to investigate truck drivers’ experiences and performance using CACC at shorter-than-normal vehicle following time gaps. “On-the-road” experiments were conducted by recruiting drivers from commercial fleets to operate the second and third trucks in a three-truck CACC string. The driving route spanned 160 miles on freeways in Northern California and five different time gaps between 0.6 and 1.8 seconds were tested. Factors such as cut-ins by other vehicles, road grades, and traffic conditions were found to influence the drivers’ opinions about use of CACC. The findings presented in this paper provide insights into the factors that will influence driver reactions to the deployment of CACC in their truck fleets.

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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