Research on Decoupled Optimal Control of Straight-Line Driving Stability of Electric Vehicles Driven by Four-Wheel Hub Motors

Yang, Shunkun; Feng, Jianmei; Song, Bao

doi:10.3390/en14185766

Cited by 6 publications

(4 citation statements)

References 42 publications

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“…The utilization rate of the tire's longitudinal force can characterize the tire's stability margin, which should be considered when designing the vehicle stability controller. Controlling the utilization of tire force within a reasonable range is also the basis of and fundamental to achieving vehicle stability control [42,43].…”

Section: Tire Utilization Constraintmentioning

confidence: 99%

Decoupling Control of Yaw Stability of Distributed Drive Electric Vehicles

Wang,

Liu,

Yang

et al. 2024

WEVJ

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Most of the research on driving stability control of distributed drive electric vehicles is based on a yaw motion design controller. The designed controller can improve the lateral stability of the vehicle well but rarely mentions its changes to the roll and pitch motion of the body, and the uneven distribution of the driving force will also cause instability in the vehicle speed, resulting in wheel transition slip, wheel sideslip, and vehicle stability loss. In order to improve the spatial stability of distributed-driven electric vehicles and resolve the control instability caused by their motion coupling, a decoupled control strategy of yaw, roll, and pitch motion based on multi-objective constraints was proposed. The strategy adopts hierarchical control logic. At the upper level, a yaw motion controller based on robust model predictive control, a roll motion controller, and a pitch motion controller based on feedback optimal control are designed. In the lower level, through the motion coupling analysis of the vehicle yaw control process, based on the coupling analysis, the vehicle yaw, roll, and pitch decoupling controller based on multi-objective constraints is designed. Finally, the effectiveness of the decoupling controller is verified.

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Section: Tire Utilization Constraintmentioning

confidence: 99%

Decoupling Control of Yaw Stability of Distributed Drive Electric Vehicles

Wang,

Liu,

Yang

et al. 2024

WEVJ

Self Cite

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“…The slip rate of the driving wheel is defined as the relative error between the wheel speed of the driving wheel and the absolute speed of the vehicle body [29]. In this article, the rotational speed data of the driving wheel are collected under the working condition of the lawn mower through pre-experiments, the real-time slip rate of the lawn mower during a certain working cycle is calculated according to Equation (29), and the target slip rate of the driving wheel is analyzed based on this. In general, whether wheel slippage occurs is measured by the slip rate of the driving wheel.…”

Section: Target Slip Rate Range Of Lawn-mowing Robotsmentioning

confidence: 99%

“…According to the design of the slip rate measurement experiment in Section 2.2.1, the lawn mower is controlled to perform repeated working experiments on the working path, recording the real-time speed and motor-related parameters of the lawn mower on this working path. The real-time slip rate of the lawn mower is calculated according to Equation (29), and the relationships between the motor parameters and slip rate are analyzed, as shown in the following figures.…”

Section: Target Slip Rate Range Of Lawn-mowing Robotsmentioning

confidence: 99%

Research on Path Tracking for an Orchard Mowing Robot Based on Cascaded Model Predictive Control and Anti-Slip Drive Control

Wang

Zhang

et al. 2023

Agronomy

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In complex orchard environments, orchard mowing robots are prone to longitudinal slippage because of the characteristics of tires and the adhesion conditions of the road surface, which makes it difficult for the robots to maintain high-precision path tracking and autonomous navigation positioning. This not only affects the accuracy of path tracking but also leads to unstable motion for the mowing robots. To solve the above problems, we take an orchard mowing robot as the control object and establish a cascaded path-tracking controller and an adaptive time domain model based on a kinematics model. By designing a linear error model, an objective function, and constraint conditions for the mowing robot, the optimal linear velocity and angular velocity of the mower are obtained and converted into the speed of the driving wheel. Then, an anti-slip driving controller is designed based on fuzzy control of the slip rate. The slip-rate-based fuzzy controller is constructed according to the real-time speed of the mower and the reference speed of the driving wheel solved by the model predictive controller, and anti-slip driving control is implemented through a combination of a PID controller and a tire dynamics model. To verify the effectiveness of the proposed method, simulation and field experiments are conducted. The experimental results show that the slip rate of the driving wheel of the mower remains within the target slip rate range in the orchard working environment, avoiding excessive driving wheel sliding. Furthermore, the average lateral error of the path-tracking controller is controlled within 0.05 m, and the average value of the longitudinal error is kept within 0.04 m, which satisfies the control accuracy requirements of lawn mower operations. The proposed method provides a reference optimization scheme for improving the path-tracking and motion stability of a mowing robot.

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“…In [4], the establishment of Ackerman mathematical model under the ideal condition of low speed static is proposed, so the realization of four-wheel hub vehicle low-speed steering, and has a certain reference value. In [5], a new P-fuzzy PID control system is proposed to improve the response speed and avoid overshoot control performance, considering the advantages of PID control and fuzzy control. In [6], for unstable signals, the neural network PID control method is proposed, which greatly reduces the overshoot compared with the traditional control strategy.…”

mentioning

confidence: 99%

Electronic Differential Control System Based on Particle Swarm Optimization and PID Control

Dong-xue

Chenyan

2022

J. Phys.: Conf. Ser.

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For the front wheel steering, the control effect of the four-wheel hub-driven electric vehicle driven by the rear wheel is not accurate and stable. It is proposed to replace the traditional PID control system with the particle swarm algorithm to realize the online optimization of the PID regulator parameters. The simulation model of the improved system is built in MATLAB. Compared with the conventional PID control method, the results show that the improved four-wheel drive system has a smaller slip ratio between the left rear wheel and the right rear wheel, which improves the directional stability and braking efficiency of the wheel electric vehicle.

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Research on Decoupled Optimal Control of Straight-Line Driving Stability of Electric Vehicles Driven by Four-Wheel Hub Motors

Cited by 6 publications

References 42 publications

Decoupling Control of Yaw Stability of Distributed Drive Electric Vehicles

Decoupling Control of Yaw Stability of Distributed Drive Electric Vehicles

Research on Path Tracking for an Orchard Mowing Robot Based on Cascaded Model Predictive Control and Anti-Slip Drive Control

Electronic Differential Control System Based on Particle Swarm Optimization and PID Control

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