Lateral Stability Control of a Tractor-Semitrailer at High Speed

Cai, Haohao; Xu, Xiaomei

doi:10.3390/machines10080716

Cited by 14 publications

(10 citation statements)

References 34 publications

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“…There is a certain delay effect in the internal transmission of ACC system, and problems such as instruction lag may occur. In this paper, the direction preview [ 21 ] is used to obtain the road information and the front vehicle trajectory in advance, and the front wheel steering angle required for the next moment is judged according to the driving state of the vehicle and used as the input of the 2‐DOF vehicle model. The yaw rate and sideslip angle can effectively compensate the system delay problem.…”

Section: Upper‐level Controller Designmentioning

confidence: 99%

Research on Curving Acc System for Electric Vehicle Driven by In‐wheel Motors Based on Fmpc And Smc

Yang,

Tian

2023

Advcd Theory and Sims

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In order to ensure the lateral stability of adaptive cruise control (ACC) vehicles during curve following, this paper proposes a hierarchical multi‐objective coordinated control ACC system structure for in‐wheel motor drive electric vehicles. Different control strategies are designed for the cruise mode and car‐following mode of the ACC system. A proportion integral differential (PID) controller is used to meet the need for speed control in cruise mode. For the car‐following mode, a multi‐objective ACC system distance control strategy is proposed considering the performance of car following, passenger comfort, driving safety and driving economy of ACC vehicles. The weight coefficients in the objective function are updated in real time by using the fuzzy model predictive control (FMPC) strategy to meet the needs of different road conditions and improve the driving economy. Then, the desired front wheel steering angle is obtained by preview control theory. According to the theory of sliding mode control (SMC), a lateral stability controller is designed to track the desired yaw rate and sideslip angle. Simulation results show that the electric vehicle driven by in‐wheel motors based on FMPC and SMC has better car‐following performance and lateral stability performance under variable curvature curved road conditions.

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Section: Upper‐level Controller Designmentioning

confidence: 99%

Research on Curving Acc System for Electric Vehicle Driven by In‐wheel Motors Based on Fmpc And Smc

Yang,

Tian

2023

Advcd Theory and Sims

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“…In terms of the selection of the control parameters, the yaw rate, the sideslip angle of the centroid, and the lateral acceleration are generally taken for stability control [16]. When these variables are used for the control, the vehicle's yaw stability will be greatly improved, but the driving path deviation would be produced compared with the path under steady-state driving.…”

Section: Selection Of Control Parameters For Yaw Stability Control Of...mentioning

confidence: 99%

Research on Yaw Stability Control Method of Liquid Tank Semi-Trailer on Low-Adhesion Road under Turning Condition

Zhao

2022

Applied Sciences

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To ensure that a liquid tank semi-trailer has good yaw stability and path-following performance on low-adhesion roads under turning conditions, a multi-object PID differential braking-control method is proposed, which takes the tractor yaw rate, semi-trailer yaw rate, and articulation angle as the control parameters. According to the principle of equivalence, the trammel pendulum (TP) model is used to simulate the liquid sloshing effect in the liquid tank, and the Fluent software is used to identify the key parameters of the trammel pendulum model and verify the correctness of its simulation effect. Then, a co-simulation model is built based on TruckSim and MATLAB/Simulink. Based on the simplified six degrees of freedom model and the co-simulation model of a liquid tank semi-trailer, a multi-object PID differential braking-control method is designed, and the vehicle state responses with and without control are compared when it is turning on a low-adhesion road. The simulation results show that the proposed multi-object PID differential braking-control method can effectively improve the yaw stability and path-following performance of the liquid tank semi-trailer when turning on a low-adhesion road.

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“…The autonomous vehicle represents the most advanced technology in the industry’s development. It encompasses three main components, including environmental perception [ 4 ], path planning [ 5 ], and tracking control [ 6 ]. The first part relies on various sensors to detect the external environment and input this information into the autonomous vehicle system [ 7 , 8 , 9 ], thereby establishing the foundation for subsequent planning and control [ 10 ].…”

Section: Introductionmentioning

confidence: 99%

Research on Path Planning and Path Tracking Control of Autonomous Vehicles Based on Improved APF and SMC

Zhang,

Liu,

Gao

et al. 2023

Sensors

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Path planning and tracking control is an essential part of autonomous vehicle research. In terms of path planning, the artificial potential field (APF) algorithm has attracted much attention due to its completeness. However, it has many limitations, such as local minima, unreachable targets, and inadequate safety. This study proposes an improved APF algorithm that addresses these issues. Firstly, a repulsion field action area is designed to consider the velocity of the nearest obstacle. Secondly, a road repulsion field is introduced to ensure the safety of the vehicle while driving. Thirdly, the distance factor between the target point and the virtual sub-target point is established to facilitate smooth driving and parking. Fourthly, a velocity repulsion field is created to avoid collisions. Finally, these repulsive fields are merged to derive a new formula, which facilitates the planning of a route that aligns with the structured road. After path planning, a cubic B-spline path optimization method is proposed to optimize the path obtained using the improved APF algorithm. In terms of path tracking, an improved sliding mode controller is designed. This controller integrates lateral and heading errors, improves the sliding mode function, and enhances the accuracy of path tracking. The MATLAB platform is used to verify the effectiveness of the improved APF algorithm. The results demonstrate that it effectively plans a path that considers car kinematics, resulting in smaller and more continuous heading angles and curvatures compared with general APF planning. In a tracking control experiment conducted on the Carsim–Simulink platform, the lateral error of the vehicle is controlled within 0.06 m at both high and low speeds, and the yaw angle error is controlled within 0.3 rad. These results validate the traceability of the improved APF method proposed in this study and the high tracking accuracy of the controller.

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Lateral Stability Control of a Tractor-Semitrailer at High Speed

Cited by 14 publications

References 34 publications

Research on Curving Acc System for Electric Vehicle Driven by In‐wheel Motors Based on Fmpc And Smc

Research on Curving Acc System for Electric Vehicle Driven by In‐wheel Motors Based on Fmpc And Smc

Research on Yaw Stability Control Method of Liquid Tank Semi-Trailer on Low-Adhesion Road under Turning Condition

Research on Path Planning and Path Tracking Control of Autonomous Vehicles Based on Improved APF and SMC

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