Sensorless Landing Control Strategy of Bistable Permanent Magnet Actuator

Li, Bo; Tan, Cao; Wang, Geng; Ge, Wenqing; Sun, Bin

doi:10.1155/2019/7652438

Cited by 3 publications

(2 citation statements)

References 22 publications

(39 reference statements)

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“…The electromagnetic linear actuator (ELA) was controlled and driven by a driving device control system. The three-phase asynchronous motor output different speeds according to the driving requirements for the input shaft [22,23]. The inertia simulator on the test-control platform could simulate the range of rotational inertia from 0.04 to 0.09 kg•m 2 .…”

Section: The Synchronizer Test-control Platformmentioning

confidence: 99%

Friction Coefficient Compensation Control in Synchronizer Synchronization Process for Transmission

Yuan

et al. 2019

Applied Sciences

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In the synchronization process of a synchronizer, the friction coefficient of the friction cone is changed because of friction heat. In this paper, the influence of a changing friction coefficient on shift quality was analyzed. The quantitative relationship between friction coefficient and its influencing factors was studied through a synchronizer synchronization process test bench. Based on the quantitative analysis and an optimal shift force control method, a compensation control strategy for friction coefficient was established. Moreover, the effectiveness of the compensation control was verified through simulation and experiment. The results showed that the friction coefficient was maintained near the expected value of 0.08 after the compensation control, the shifting speed difference the synchronous time was shortened by nearly 0.12 s, and the sliding friction was reduced by 4.64 J under the experimental conditions. The analysis and compensation of the friction coefficient provide a theoretical reference for improving shift quality.

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Section: The Synchronizer Test-control Platformmentioning

confidence: 99%

Friction Coefficient Compensation Control in Synchronizer Synchronization Process for Transmission

Yuan

et al. 2019

Applied Sciences

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“…Sensorless control provides many advantages over a single actuator/sensor system, such as low cost, simplicity, and robustness [13,14]. In this context, a great number of papers had been presented for the piezoelectric actuator [15], bistable permanent magnet actuator [16,17], induction motor [18,19], and permanent magnet synchronous machines [20]. Sensorless technology is applied to the prediction of rotation angle, rotation speed, position, and other variables of various rotary and linear motion systems, showing good results in different fields.…”

Section: Introductionmentioning

confidence: 99%

Gearshift Sensorless Control for Direct-Drive-Type AMT Based on Improved GA-BP Neural Network Algorithm

et al. 2020

Mathematical Problems in Engineering

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The automated mechanical transmission (AMT) based on the electromagnetic linear driving device (EMLDD) has good potential for shift performance. However, the direct-drive shifting mechanism based on the displacement sensor is difficult to meet the compactness of the structure and control robustness in complex environment. Through analyzing the working principle of the electromagnetic linear driving device and features of sensorless control strategy, a new displacement prediction method based on the improved GA-BP neural network is proposed to replace the displacement sensor. With current, voltage, and input shaft speed of the electromagnetic linear driving device as input, displacement prediction is obtained by the GA-BP neural network with improved selection factor. Finally, the experiment validated the effectiveness of displacement prediction based on the improved GA-BP neural network of shift control. The results showed that prediction accuracy of the improved GA-BP neural network was greater than 96% under all shift working conditions. The average RMSE was reduced by 21.8%, absolute error of displacement prediction was controlled within ±0.5 mm, and average shift time was less than 0.18 s. In this paper, the BP neural network is applied to complex linear displacement prediction, which has important application and popularization value.

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Bistable permanent magnet actuator based on double wing magnetic flux

Zhao

Shen

2021

JAE

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This letter presents a bistable permanent magnet actuator, based on double wing magnetic fluxes (DWMF) formed by the structure of welding sleeve and slotted armature. The double wing magnetic fluxes consist of high wing magnetic flux (HWMF) and low wing magnetic flux (LWMF), resulting in bistable performance under differentiating control. Parameters improvement around DWMF is analyzed based on modeling, and optimized results for a prototype actuator are obtained. The experimental and simulation results agree well, and show that the prototype actuator can realize bistable performance under the DC step voltage drive, with the holding force of 8.2 N (without current) and the restoring force of −31.7 N (with negative current), the dynamic results show that the displacement response time within 8 mm is 28 ms, of which the actuation time is 16.5 ms, the transient maximum power consumption of the restoring period is 18 W.

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Sensorless Landing Control Strategy of Bistable Permanent Magnet Actuator

Cited by 3 publications

References 22 publications

Friction Coefficient Compensation Control in Synchronizer Synchronization Process for Transmission

Friction Coefficient Compensation Control in Synchronizer Synchronization Process for Transmission

Gearshift Sensorless Control for Direct-Drive-Type AMT Based on Improved GA-BP Neural Network Algorithm

Bistable permanent magnet actuator based on double wing magnetic flux

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