Coordinated Lateral Stability Control of Autonomous Vehicles Based on State Estimation and Path Tracking

Li, Jun; Liu, Haohao; Wang, Jingjing; Gu, Heng

doi:10.3390/machines11030328

Cited by 8 publications

(4 citation statements)

References 32 publications

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“…In order to suppress the power wastage of the drive system and improve trafficability, a robust and rapid-update identification method of adhesion coefficient (µ) is necessary. Researchers have estimated according to real-time updated measurement data from inertial measurement unit (IMU), GPS and extended Kalman filter [11][12][13], which demonstrated credible results through scrupulous verifications. However, the disparities of the wheels' slip ratios, which have become more distinct in off-road conditions, and the independent torque control of the four driving wheels were neglected in these studies.…”

Section: Introductionmentioning

confidence: 99%

Synthetic Optimization of Trafficability and Roll Stability for Off-Road Vehicles Based on Wheel-Hub Drive Motors and Semi-Active Suspension

Fu,

Wan,

Liu

et al. 2024

Mathematics

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Considering the requirements pertaining to the trafficability of off-road vehicles on rough roads, and since their roll stability deteriorates rapidly when turning violently or passing slant roads due to a high center of gravity (CG), an efficient anti-slip control (ASC) method with superior instantaneity and robustness, in conjunction with a rollover prevention algorithm, was proposed in this study. A nonlinear 14 DOF vehicle model was initially constructed in order to explain the dynamic coupling mechanism among the lateral motion, yaw motion and roll motion of vehicles. To acquire physical state changes and friction forces of the tires in real time, corrected LuGre tire models were utilized with the aid of resolvers and inertial sensors, and an adaptive sliding mode controller (ASMC) was designed to suppress each wheel’s slip ratio. In addition, a model predictive controller (MPC) was established to forecast rollover risk and roll moment in reaction to the change in the lateral forces as well as the different ground heights of the opposite wheels. During experimentation, the mutations of tire adhesion capacity were quickly discerned and the wheel-hub drive motors (WHDM) and ASC maintained the drive efficiency under different adhesion conditions. Finally, a hardware-in-the-loop (HIL) platform made up of the vehicle dynamic model in the dSPACE software, semi-active suspension (SAS), a vehicle control unit (VCU) and driver simulator was constructed, where the prediction and moving optimization of MPC was found to enhance roll stability effectively by reducing the length of roll arm when necessary.

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Section: Introductionmentioning

confidence: 99%

Synthetic Optimization of Trafficability and Roll Stability for Off-Road Vehicles Based on Wheel-Hub Drive Motors and Semi-Active Suspension

Fu,

Wan,

Liu

et al. 2024

Mathematics

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“…The Kalman filter (KF) is derived under the criterion of the linear minimum mean square error (LMMSE), which achieves an optimal state estimation when given precise a priori knowledge on the state-space model (SSM) and noise properties [13]. In order to improve the position and heading accuracy of agricultural machinery, many KF-based integrated navigation systems have been developed [14][15][16]. Han et al developed an integrated navigation system by fusing three single GPS receivers and an inertial measurement unit (IMU) based on the KF [17].…”

Section: Introductionmentioning

confidence: 99%

Improved Information Fusion for Agricultural Machinery Navigation Based on Context-Constrained Kalman Filter and Dual-Antenna RTK

Cui,

Zhang,

Wei

et al. 2024

Actuators

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Automatic navigation based on dual-antenna real-time kinematic (RTK) positioning has been widely employed for unmanned agricultural machinery, whereas GNSS inevitably suffers from signal blocking and electromagnetic interference. In order to improve the reliability of an RTK-based navigation system in a GNSS-challenged environment, an integrated navigation system is preferred for autonomous navigation, which increases the complexity and cost of the navigation system. The information fusion of integrated navigation has been dominated by Kalman filter (KF) for several decades, but the KF cannot assimilate the known knowledge of the navigation context efficiently. In this paper, the geometric characteristics of the straight path and path-tracking error were employed to formulate the constraint measurement model, which suppresses the position error in the case of RTK-degraded scenarios. The pseudo-measurements were then imported into the KF framework, and the smoothed navigation state was generated as a byproduct, which improves the reliability of the RTK positioning without external sensors. The experiment result of the mobile vehicle automatic navigation indicates that the tracking error-constrained KF (EC-KF) outperforms the trajectory-constrained KF (TC-KF) and KF when the RTK system outputs a float or single-point position (SPP) solution. In the case where the duration of the SPP solution was 20 s, the positioning errors of the EC-KF and TC-KF were reduced by 38.50% and 24.04%, respectively, compared with those of the KF.

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“…Numerous academic studies have investigated the control of AFS and DYC for fourwheel independent-drive trams. The focus has primarily been on integrated control [7][8][9] and coordinated control [10][11][12]. Zhang, L [13] developed a fast terminal sliding-mode AFS controller using the inverse stepping control method.…”

Section: Introductionmentioning

confidence: 99%

Distributed-Drive Vehicle Lateral-Stability Coordinated Control Based on Phase-Plane Stability Region

Liu,

Dai

2024

WEVJ

Self Cite

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The lateral stability control of vehicles is one of the most crucial aspects of vehicle safety. This article introduces a coordinated-control strategy designed to enhance the handling stability of distributed-drive electric vehicles. The upper controller uses active front steering and direct yaw moment-control controllers designed based on sliding-mode control theory. The lower controller optimally allocates control inputs to the upper controller, considering factors such as load transfer and tire load rate. It divides the stability region by relying on the phase plane and develops a coordinated-control strategy based on the degree of deviation of the vehicle state from the stability region. The results of the simulation experiments demonstrate that the proposed control strategy effectively improves handling stability under extreme working conditions.

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Coordinated Lateral Stability Control of Autonomous Vehicles Based on State Estimation and Path Tracking

Cited by 8 publications

References 32 publications

Synthetic Optimization of Trafficability and Roll Stability for Off-Road Vehicles Based on Wheel-Hub Drive Motors and Semi-Active Suspension

Synthetic Optimization of Trafficability and Roll Stability for Off-Road Vehicles Based on Wheel-Hub Drive Motors and Semi-Active Suspension

Improved Information Fusion for Agricultural Machinery Navigation Based on Context-Constrained Kalman Filter and Dual-Antenna RTK

Distributed-Drive Vehicle Lateral-Stability Coordinated Control Based on Phase-Plane Stability Region

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