Coordinated Vehicle Lateral Stability Control Based on Direct Yaw Moment and Engine Torque Regulation under Complicated Road Conditions

Gang, Liu; Lin-Yan, Qiao

doi:10.1155/2022/4934723

Cited by 2 publications

(2 citation statements)

References 32 publications

(33 reference statements)

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“…For example, a fuzzy PI control strategy is used with continuous optimization of the PI parameters (Cai et al , 2022). A direct yaw moment control algorithm based on sliding mode control is developed, incorporating inertial delay control (Gang and Lin-Yan, 2022; Patil et al , 2021). To achieve directional stability for heavy commercial road vehicles, a robust reaching law-based sliding mode controller is proposed, considering the combined effects of cornering and emergency braking (Patil et al , 2022).…”

Section: Introductionmentioning

confidence: 99%

Coordinated torque control for enhanced steering and stability of independently driven mobile robots

Wang,

Wang

2024

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Purpose Mobile robots with independent wheel control face challenges in steering precision, motion stability and robustness across various wheel and steering system types. This paper aims to propose a coordinated torque distribution control approach that compensates for tracking deviations using the longitudinal moment generated by active steering. Design/methodology/approach Building upon a two-degree-of-freedom robot model, an adaptive robust controller is used to compute the total longitudinal moment, while the robot actuator is regulated based on the difference between autonomous steering and the longitudinal moment. An adaptive robust control scheme is developed to achieve accurate and stable generation of the desired total moment value. Furthermore, quadratic programming is used for torque allocation, optimizing maneuverability and tracking precision by considering the robot’s dynamic model, tire load rate and maximum motor torque output. Findings Comparative evaluations with autonomous steering Ackermann speed control and the average torque method validate the superior performance of the proposed control strategy, demonstrating improved tracking accuracy and robot stability under diverse driving conditions. Research limitations/implications When designing adaptive algorithms, using models with higher degrees of freedom can enhance accuracy. Furthermore, incorporating additional objective functions in moment distribution can be explored to enhance adaptability, particularly in extreme environments. Originality/value By combining this method with the path-tracking algorithm, the robot’s structural path-tracking capabilities and ability to navigate a variety of difficult terrains can be optimized and improved.

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Section: Introductionmentioning

confidence: 99%

Coordinated torque control for enhanced steering and stability of independently driven mobile robots

Wang,

Wang

2024

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“…The results showed that the ARS system facilitated the active safety performance of human drivers. Liu G. [32] et al proposed a control method for a vehicle lateral stability control system. The complex friction condition operating conditions were simulated and analyzed by joint simulation in MATLAB and CarSim.…”

Section: Introductionmentioning

confidence: 99%

Vehicle Stability Analysis under Extreme Operating Conditions Based on LQR Control

Zhou

Bao³

et al. 2022

Sensors

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Under extreme working conditions such as high-speed driving on roads with a large road surface unevenness coefficient, turning on a road with a low road surface adhesion coefficient, and emergency acceleration and braking, a vehicle’s stability deteriorates sharply and reduces ride comfort. There is extensive existing research on vehicle active suspension control, trajectory tracking, and control methods. However, most of these studies focus on conventional operating conditions, while vehicle stability analysis under extreme operating conditions is much less studied. In order to improve the stability of the whole vehicle under extreme operating conditions, this paper investigates the stability of a vehicle under extreme operating conditions based on linear quadratic regulator (LQR) control. First, a seven degrees of freedom (7-DOF) dynamics model of the whole vehicle is established based on the use of electromagnetic active suspension, and then an LQR controller of the electromagnetic active suspension is designed. A joint simulation platform incorporating MATLAB and CarSim was built, and the CarSim model is verified by real vehicle tests. Finally, the stability of the vehicle under four different ultimate operating conditions was analyzed. The simulation results show that the root mean square (RMS) values of body droop acceleration and pitch angle acceleration are improved by 57.48% and 28.81%, respectively, under high-speed driving conditions on Class C roads. Under the double-shift condition with a low adhesion coefficient, the RMS values of body droop acceleration, pitch acceleration, and roll angle acceleration are improved by 58.25%, 55.41%, and 31.39%, respectively. These results indicate that electromagnetic active suspension can significantly improve vehicle stability and reduce driving risk under extreme working conditions when combined with an LQR controller.

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Coordinated Vehicle Lateral Stability Control Based on Direct Yaw Moment and Engine Torque Regulation under Complicated Road Conditions

Cited by 2 publications

References 32 publications

Coordinated torque control for enhanced steering and stability of independently driven mobile robots

Coordinated torque control for enhanced steering and stability of independently driven mobile robots

Vehicle Stability Analysis under Extreme Operating Conditions Based on LQR Control

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