Design of robust speed and slip controllers for a hybrid electromagnetic brake system

Yazdanpanah, Reza; Mirsalim, Mojtaba

doi:10.1049/iet-epa.2014.0256

Cited by 18 publications

(5 citation statements)

References 30 publications

(62 reference statements)

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“…The amount of braking torque is directly proportional to the density of the magnetic flux in the air gap, so the braking torque can be increased by increasing the addition of permanent magnets as an additional magnetic field source. Yazdanpanah (2015) [9] uses two magnetic field sources simultaneously. Permanent magnets are at once used as a winding core.…”

Section: Literature Reviewmentioning

confidence: 99%

“…In addition, the ECB can also be adopted as a braking support system. Furthermore, compared to using resistive loads on regenerative braking, the ECB has a superior braking performance because the torque components produced by the ECB are more effective in terms of braking performance [9]. The ECB has been widely used in various scientific and application fields.…”

Section: Introductionmentioning

confidence: 99%

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Application of Multiple Unipolar Axial Eddy Current Brakes for Lightweight Electric Vehicle Braking

et al. 2020

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The braking system in a vehicle has the main role of slowing down the speed or stopping the moving vehicle. Compared to mechanical braking, which utilizes friction, non-contact braking has several advantages, including longer lifetime and less maintenance. One form of non-contact braking systems is the eddy current brake (ECB), an electric braking system that employs eddy currents to operate. This research focuses on the impact of magnetic field sources used in the ECB. In addition, the number of magnetic field sources is also observed. In order to achieve an ECB design that can be easily applied in any types of vehicles, including motorcycles and compact cars, a compact ECB design with an excellent braking torque is required. In this study, a compact design of the ECB is obtained by distributing the required braking torque from the disc brake into multiple electromagnets. Finite element method-based modeling has been performed to study ECB parameters, including the number of coil winding, the number of electromagnets, and the electric current. The results of this study show that the developed compact ECB could produce 93.66% of the torque required for braking.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Application of Multiple Unipolar Axial Eddy Current Brakes for Lightweight Electric Vehicle Braking

et al. 2020

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“…Through the improvement, the anti-interference ability of the electromagnetic clutch is improved and has better adaptability. Yazdanpanah [17] proposed a robust speed and slip control scheme for a hybrid electromagnetic brake (HEB) system based on a neural network for uncertain system parameters and unknown external disturbance conditions. The controller does not need accurate information about braking, and the control algorithm can effectively track the performance and ensure the stability of the closed-loop system.…”

Section: Introductionmentioning

confidence: 99%

Research on Dynamic Control Method of Loom Spindle Braking System Based on Fuzzy Neural Network

et al. 2022

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Aiming at the problems of slow response speed of loom electromagnetic braking system and low accuracy of parking angle after braking, resulting in driving marks and thin and dense roads of fabrics, a braking control system based on fuzzy theory and BP neural network is proposed to improve the response speed and control accuracy of the braking system. Firstly, the transmission torque in the braking process of the loom is dynamically analyzed by establishing the mathematical model of electromagnetic braking and the Ansoft electromagnetic finite element model. The causes of braking angle slip are explored, and the driving mechanism of the electromagnetic clutch control circuit based on PWM pulse is analyzed. Based on the control strategy of excitation current, by introducing the fuzzy theory and BP neural network, a fuzzy electromagnetic braking control system based on a neural network is proposed to improve the adaptive ability of the system. At the same time, the IBA-BP algorithm is used to train the neural network to avoid the generation of local optimization and improve the control accuracy of the system. The simulation and experimental results show that compared with PID control and fuzzy PID control, the neural network method based on fuzzy theory has a smaller braking slip angle, and the accuracy of parking angle after braking action is less than 10 °, which improves the control accuracy of loom electromagnetic braking system and weaving quality.

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“…In terms of active safety functions, the anti-lock brake system (ABS), which actively intervenes in the braking force, plays an important role in improving the car’s wheel adhesion capacity and driving stability during heavy braking, and the control strategy of ABS can be mainly divided into rule-based control strategy [ 8 , 9 , 10 ] and model-based control strategy [ 11 , 12 , 13 ]. Among them, the rule-based control strategy considers the state of the vehicle driving with the slip rate as the limit and also considers the angular deceleration rate for the decision of discontinuous control such as increase, pressure preservation, and decompression.…”

Section: Introductionmentioning

confidence: 99%

A Data-Driven Method for the Estimation of Truck-State Parameters and Braking Force Distribution

Chu

Sun

Zhang

2022

Sensors

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In the study of braking force distribution of trucks, the accurate estimation of the state parameters of the vehicle is very critical. However, during the braking process, the state parameters of the vehicle present a highly nonlinear relationship that is difficult to estimate accurately and that seriously affects the accuracy of the braking force distribution strategy. To solve this problem, this paper proposes a machine-learning-based state-parameter estimation method to provide a solid data base for the braking force distribution strategy of the vehicle. Firstly, the actual collected complete vehicle information is processed for data; secondly, random forest is applied for the feature screening of data to reduce the data dimensionality; subsequently, the generalized regression neural network (GRNN) model is trained offline, and the vehicle state parameters are estimated online; the estimated parameters are used to implement the four-wheel braking force distribution strategy; finally, the effectiveness of the method is verified by joint simulation using MATLAB/Simulink and TruckSim.

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Design of robust speed and slip controllers for a hybrid electromagnetic brake system

Cited by 18 publications

References 30 publications

Application of Multiple Unipolar Axial Eddy Current Brakes for Lightweight Electric Vehicle Braking

Application of Multiple Unipolar Axial Eddy Current Brakes for Lightweight Electric Vehicle Braking

Research on Dynamic Control Method of Loom Spindle Braking System Based on Fuzzy Neural Network

A Data-Driven Method for the Estimation of Truck-State Parameters and Braking Force Distribution

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