Design of a Parameterized Model Predictive Control for Electric Power Assisted Steering

Murilo, André; Rodrigues, Rafael Antonio; Teixeira, Evandro Leonardo Silva; Santos, Max Mauro Dias

doi:10.1016/j.conengprac.2019.07.010

Cited by 21 publications

(15 citation statements)

References 13 publications

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“…Usually, when the form of the characteristic equation is (s + v) 3 , the stability is good and can provide a good transition process. To make the state estimation of the controlled object more ideal, this article configures the control parameters b 01 , b 02 , b 03 to the form of 3v, 3v 2 , v 3 .…”

Section: Active Disturbance Rejection Controllermentioning

confidence: 99%

“…To improve the tracking effect of assist torque, Murilo et al Andre proposed an EPS control strategy based on parameterized model predictive control (MPC). 3 The MPC algorithm provided lower computational complexity, and the results showed that the control strategy had good torque tracking performance. Liu designed power compensation control and damping control strategies for the changes in control methods of heavy-duty vehicle EPS at different driving speeds, providing a theoretical basis for the development of heavy-duty vehicle EPS systems.…”

Section: Introductionmentioning

confidence: 95%

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Research on active disturbance rejection control strategy of electric power steering system under extreme working conditions

Zheng,

Wei

2023

Measurement and Control

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In response to the influence of motor interference, damping, friction, and other uncertain factors on the operation of electric power steering systems under extreme working conditions, this study proposes a control strategy for electric power steering systems based on an active disturbance rejection algorithm. In ADRC, the fastest tracking differentiator is used to arrange the transition process for the target signal, and the extended state observer compensates for the total disturbance in the system. Phase compensation has been performed on the monitoring torque by using the torque differentiation method. The Simulink/Carsim simulation results show that ADRC has significantly improved anti-disturbance performance compared to PID and fuzzy PID. When using ADRC, the tracking accuracy of the assisted current is enhanced by 45.8%–75.8%, and the current adjustment time is reduced by 35.6%–61.7%. After phase compensation, the monitoring torque overshoot is reduced by 83.3%. Therefore, the proposed control strategy improves EPS’s robustness and steering feel.

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Section: Active Disturbance Rejection Controllermentioning

confidence: 99%

Section: Introductionmentioning

confidence: 95%

Research on active disturbance rejection control strategy of electric power steering system under extreme working conditions

Zheng,

Wei

2023

Measurement and Control

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“…EPS model established the relationship between mechanical steering system, electromechanical dynamic and road reaction force. In order to make the simulation model more close to the real component stress, the corresponding viscous damping coefficient and rigidity coefficient are added in the model [10]. The model of literature [11] is applied in this study.…”

Section: Eps System Dynamic Modelmentioning

confidence: 99%

Control strategy of electric power steering system based on super-twisting algorithm

Wang

He²

2022

6th International Workshop on Advanced Algorithms and Control Engineering (IWAACE 2022)

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With the development of new energy vehicles, the demand for auto parts is also rising. It is difficult to design the control strategy of EPS system because of multiple control objectives. In this study, a control strategy is introduced which is based on the super twisting algorithm. The control objectives are to provide ideal assist torque, respond quickly and return road information. The EPS dynamic analysis and built model in order to generate the desired motor angle. In order to achieve control objectives, the controller based on super-twisting algorithm is designed. To estimate the EPS system state and unknow inputs, the observer with unknow input is employed. Auxiliary outputs are constructed because the EPS system is not satisfied the observer-matching condition. Using of the second order SM differentiators estimate the auxiliary outputs. Finally, the performance of the controller, observer and differentiator is verified by simulation, and the controller can provide expected the assist torque. The result of simulation show that the control strategy is effectiveness and robustness.

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“…At altitudes above 4.3 km above sea level, it may negatively affect engine power, load capacity, and operator well-being. 10 Vehicles are equipped with power steering for ease of operation. The cars may be pneumatically, hydraulically, and electrically driven.…”

Section: Introductionmentioning

confidence: 99%

Design and analysis of electric power-assisted steering in vehicles for mountain forests

Kalyashov

Михеев

Kunickaya

et al. 2022

Proceedings of the Institution of Mechanical Engineers, Part D:

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This study investigates the problem of vehicle exploitation in the mountainous and wooded regions of the Russian Federation. Considering how critical rollover accidents are in the logging industry, it is vital to ensure safe and stable driving. This study aims to develop a model of electric power steering (EPS) control using a quasi-continuous sliding-mode controller in MATLAB/Simulink. Experiments were carried out under the following conditions: maximum slope angle, 30°; maximum steering angle, 30°; maximum driving speed, 7 m/s. The dynamic characteristics of the suspension and EPS systems were optimized using the receding horizon optimization technique. The theoretical and experimental results suggest that the model reaches its critical state of stability (−0.2) at a speed range of 0–7 m/s with a steering angle of 25°. After optimization, critical stability (0.3) occurs at the driving speed of 7 m/s when the steering angle is 30°. The paper discussed the possibility of installing the EPS control system into vehicles that operate in mountainous wooded areas.

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Design of a Parameterized Model Predictive Control for Electric Power Assisted Steering

Cited by 21 publications

References 13 publications

Research on active disturbance rejection control strategy of electric power steering system under extreme working conditions

Research on active disturbance rejection control strategy of electric power steering system under extreme working conditions

Control strategy of electric power steering system based on super-twisting algorithm

Design and analysis of electric power-assisted steering in vehicles for mountain forests

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