Path-following and tire loss investigation of a front in-wheel-drive electric vehicle with off-centre CG

Ghazali, Mohammad

doi:10.1016/j.mechmachtheory.2023.105422

Cited by 4 publications

(2 citation statements)

References 40 publications

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“…An essential requirement of driverless monorail cranes is the accurate recognition of actual monorail track slopes, which is necessary to guaranteeing their safe driving and energy efficiency. A variety of research studies have shown that vehicle stability control, traction control, and brake control all have a significant effect on vehicle safety and energy efficiency [4,5].…”

Section: Introductionmentioning

confidence: 99%

DFFRLS-FAUKF: accurate and reliable monorail longitudinal slope identification method

Liu,

Li,

Zheng

et al. 2024

Meas. Sci. Technol.

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Monorail cranes have always played an important role in mine auxiliary transportation systems owing to their excellent transportation performance and are therefore a desirable area in which to apply driverless technologies. However, the low-accuracy recognition of monorail track slopes and the poor reliability of recognition results make it difficult and dangerous to implement fully driverless monorail cranes. Aiming to solve these problems, a method for the accurate identification of longitudinal monorail slopes based on the use of a dynamic forgetting factor for recursive least squares (DFFRLS) and a fuzzy adaptive unscented Kalman filter (FAUKF) is proposed. First, acquired acceleration and velocity data are pre-processed using a rolling window. Second, the real-time longitudinal track-curvature value is calculated using the DFFRLS algorithm with the processed data and an established track-curvature model. Finally, based on existing track-curvature values, dynamic recognition of the monorail track slope is realised using the FAUKF algorithm with a fuzzy control factor, improving the accuracy of track gradient recognition. Experiments show that the DFFRLS-FAUKF algorithm improves the accuracy of track-slope recognition by up to 21.26% and 33.93% on average compared with that of DFFRLS with an adaptive extended Kalman filter (DFFRLS-AEKF) or an adaptive unscented Kalman filter (DFFRLS-AUKF).

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Section: Introductionmentioning

confidence: 99%

DFFRLS-FAUKF: accurate and reliable monorail longitudinal slope identification method

Liu,

Li,

Zheng

et al. 2024

Meas. Sci. Technol.

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“…With considerations of driver safety, maneuverability, and trajectory tracking performance, integrating an AFS system in AGEV will offer substantial benefits [5]. AFS's intrinsic characteristics, such as its quick reactivity and exact execution, can also be dedicated to AGEV's active safety and brilliant trajectory-tracking performance [4][5][6][7][8].…”

Section: Introductionmentioning

confidence: 99%

Design of Active Disturbance Rejection Controller for Trajectory-Following of Autonomous Ground Electric Vehicles

Jin,

Lv,

et al. 2023

Symmetry

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In this paper, the concept of symmetry is utilized in the promising trajectory-following control design of autonomous ground electric vehicles—that is, the construction and the solution of active disturbance rejection controllers are symmetrical. This paper presents an active disturbance rejection controller (ADRC) for improving the trajectory-following performance of autonomous ground electric vehicles (AGEV) with an advanced active front steering system. Since AGEV trajectory dynamics are inherently affected by complex traffic conditions, various driving maneuvers, and other road environment, the main control objective is to deal with the AGEV trajectory control challenges of system uncertainties, system nonlinearities, and external disturbance. First, the vehicle dynamics trajectory-following model and its state space representation system are established. Then, the augmented control-oriented vehicle-trajectory-following system with dynamic error is developed. The resulting active disturbance rejection controller of the vehicle-trajectory-following system is finally designed using the trajectory performance index and active disturbance compensation, and the stability of the active disturbance rejection controller is also analyzed and derived via Lyapunov stability theory. The effectiveness of the proposed controller is validated through double lane change and serpentine maneuvers under the co-simulation platform of MATLAB/Simulink-Carsim®. Simulation results show that the designed controller provides enhanced vehicle-trajectory-following performance compared to the linear quadratic regulator controller (LQR) and model predictive controller (MPC). It will provide a certain guidance for the controller engineering design of the AGEV trajectory-following system.

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Pitch motion suppression of electric vehicle active suspensions based on multibody dynamics

Wu,

Pan,

Wang

et al. 2024

Mechanism and Machine Theory

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Path-following and tire loss investigation of a front in-wheel-drive electric vehicle with off-centre CG

Cited by 4 publications

References 40 publications

DFFRLS-FAUKF: accurate and reliable monorail longitudinal slope identification method

DFFRLS-FAUKF: accurate and reliable monorail longitudinal slope identification method

Design of Active Disturbance Rejection Controller for Trajectory-Following of Autonomous Ground Electric Vehicles

Pitch motion suppression of electric vehicle active suspensions based on multibody dynamics

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