Advanced Chassis Control Systems for Vehicle Handling and Active Safety

This paper proposed a full vehicle state estimation and developed an integrated chassis control by coordinating electronic stability control (ESC) and torque vectoring differential (TVD) systems to improve vehicle handling and stability in all conditions without any interference. For this purpose, an integrated TVD/ESC chassis system has been modeled in Matlab/Simulink and applied into the vehicle dynamics model of the 2003 Ford Expedition in carsim software. TVD is used to improve handling in routine and steady-state driving conditions and ESC is mainly used as the stability controller for emergency maneuvers or when the TVD cannot improve vehicle handling. By the β−β˙ phase plane, vehicle stable region is determined. Inside the reference region, the handling performance and outside the region the vehicle stability has been in question. In order to control the integrated chassis system, a unified controller with three control layers based on fuzzy control strategy, β−β˙ phase plane, longitudinal slip, and road friction coefficient of each tire is designed in Matlab/Simulink. To detect the control parameters, a state estimator is developed based on unscented Kalman filter (UKF). Bees algorithm (BA) is employed to optimize the fuzzy controller. The performance and robustness of the integrated chassis system and designed controller were conformed through routine and extensive simulations. The simulation results via a co-simulation of MATLAB/Simulink and CarSim indicated that the designed integrated ESC/TVD chassis control system could effectively improve handling and stability in all conditions without any interference between subsystems.

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Advanced Estimation Techniques for Vehicle System Dynamic State: A Survey

Sensors ◽

10.3390/s19194289 ◽

2019 ◽

Vol 19 (19) ◽

pp. 4289 ◽

Cited By ~ 10

Author(s):

Jin ◽

Yin ◽

Chen

Keyword(s):

Control Systems ◽

Steering System ◽

System Dynamic ◽

Dynamic State ◽

Future Research ◽

Active Safety ◽

Automated Driving ◽

Estimation Techniques ◽

Stability Performance ◽

Vehicle System

In order to improve handling stability performance and active safety of a ground vehicle, a large number of advanced vehicle dynamics control systems—such as the direct yaw control system and active front steering system, and in particular the advanced driver assistance systems—towards connected and automated driving vehicles have recently been developed and applied. However, the practical effects and potential performance of vehicle active safety dynamics control systems heavily depend on real-time knowledge of fundamental vehicle state information, which is difficult to measure directly in a standard car because of both technical and economic reasons. This paper presents a comprehensive technical survey of the development and recent research advances in vehicle system dynamic state estimation. Different aspects of estimation strategies and methodologies in recent literature are classified into two main categories—the model-based estimation approach and the data-driven-based estimation approach. Each category is further divided into several sub-categories from the perspectives of estimation-oriented vehicle models, estimations, sensor configurations, and involved estimation techniques. The principal features of the most popular methodologies are summarized, and the pros and cons of these methodologies are also highlighted and discussed. Finally, future research directions in this field are provided.

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