Multi-Stage Gear Shifting Control Scheme for Electric Mechanical Transmission: Design and Experiment

Bao, Chunjiang; Guo, Hongwei; Kong, Lingzhi; Cheng, Xingqun

doi:10.1109/access.2019.2926311

Cited by 5 publications

(3 citation statements)

References 29 publications

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“…2 . By substituting (16) and (17) into (12) and (13), F cn1 , F cf1 , F cn2 and F cf2 can be obtained respectively. Thus, the combined axial force F czx and the combined circumferential force F czy received by SL from DG can be obtained as follows:…”

Section: ) the Force From The Detent Pinmentioning

confidence: 99%

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Modeling and Analysis of Gear Shifting Process of Non-Synchronizer AMT Based on Collision Model

Luo

2021

IEEE Access

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In the gear shifting process of a clutchless automated mechanical transmission (AMT), the potential collision between sleeve and dog gear may increase both vehicle jerk and gear changing duration. Therefore, the gear shifting process's mechanism analysis and dynamic modeling are the essential prerequisites to improve gear shifting quality. This paper analyzes the potential collision between the sleeve and the dog gear which both with concave-convex profiles, the tooth-side chamfer considered. To model the collision process, a fast-determining collision face method based on an intersection map is proposed, and the Monte Carlo method and equivalent depth are employed to calculate the collision stiffness. Then, the stiffness-damping model of the collision process and an 8-degree-of-freedom dynamic model of the gear-shifting system are established. Finally, taking a two-speed clutchless and non-synchronizer automated mechanical transmission (NSAMT) as an example, the established dynamic model of the gear-shifting system is applied, and simulation verification is performed in Matlab/Simulink. The simulation results show that the established model can accurately reflect the changes of forces, speeds, and displacements of sleeve and dog gears during the collision and effectively reflect processes of the disengagement of the sleeve, the speed changes in active synchronization, the engagement of sleeve and gear keeping. Besides, the results also show that the tooth-side chamfer will increase the disengagement time, while it is conducive to gear keeping, and that unloading the drive motor can decrease the disengagement time due to the existence of the tooth-side chamfer.

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Section: ) the Force From The Detent Pinmentioning

confidence: 99%

“…Although CLAMT/NSAMT has many advantages, its shift control is difficult [13]- [16]. Many researchers divide the gear shifting process into five stages: torque unloading, gear disengagement, active synchronization (including speed synchronization and angle synchronization), gear engagement, and torque recovery [17]- [19].…”

Section: Introductionmentioning

confidence: 99%

Modeling and Analysis of Gear Shifting Process of Non-Synchronizer AMT Based on Collision Model

Luo

2021

IEEE Access

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“…Iswanto, Second-order Integral Fuzzy Logic Control Based Rocket Tracking Control configuration controller P-I-D was investigated by Guo [22]. Multi-stage shift control scheme for electrical mechanical transmission: design and experiment was researched by Bao [23]. Static Output Feedback Control for Fuzzy Systems with stochastic fading channels and actuator errors was investigated by Chen [24].…”

Section: Extended Fuzzy Adaptive Event Trigger Compensationmentioning

confidence: 99%

Second Order Integral Fuzzy Logic Control Based Rocket Tracking Control

Iswanto

Ahmad

2021

jrc

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Fuzzy logic is a logic with a degree of vulnerability ranging from 0 to 1. Fuzzy logic is used to convert a quantity into language. It is used as a control system because it is a versatile and simple control process that does not require complex mathematical models. The paper aimed to present a fuzzy control system implemented in a rocket tracking control system as the controller because it could work well on non-linear systems and offered convenience in program design. The fuzzy control system worked to keep the rocket on track and travel at a fixed speed. The signal from the fuzzy logic control system served to control the rocket thrust. However, the process of the fuzzy logic control system is slow and time-consuming, not proper for the one that required rapid control, such as rockets, and is not applicable for tracking ramp and parabolic signals. The fuzzy logic, therefore, was modified by adding second-order integral control. The proposed algorithm showed that, by adding second-order integral control, the rocket glided 12.78m at 12 seconds with a steady-state error of 0.78 according to the setpoint of ramp path 12 m; 10.68m at 10 seconds with a steady-state error of 0.68 according to the setpoint of ramp path 10m; and 4.689m at 4 seconds with a steady-state error of 0.689 according to the setpoint of ramp path 4m. In accordance with the parabolic path, the rocket glided 15.47m at the 4th minute with 0 steady-state error.

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Torque Control Based Speed Synchronization for Two-Speed Gear Electric Vehicle

Lee

Nam

2021

IEEE Access

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Multi-Stage Gear Shifting Control Scheme for Electric Mechanical Transmission: Design and Experiment

Cited by 5 publications

References 29 publications

Modeling and Analysis of Gear Shifting Process of Non-Synchronizer AMT Based on Collision Model

Modeling and Analysis of Gear Shifting Process of Non-Synchronizer AMT Based on Collision Model

Second Order Integral Fuzzy Logic Control Based Rocket Tracking Control

Torque Control Based Speed Synchronization for Two-Speed Gear Electric Vehicle

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