Gearshift control system development for direct-drive automated manual transmission based on a novel electromagnetic actuator

Mechatronics ◽  
2014 ◽  
Vol 24 (8) ◽  
pp. 1214-1222 ◽  
Author(s):  
Shusen Lin ◽  
Siqin Chang ◽  
Bo Li
2020 ◽  
Vol 10 (8) ◽  
pp. 2930 ◽  
Author(s):  
Wan-Soo Kim ◽  
Yong-Joo Kim ◽  
Yeon-Soo Kim ◽  
Seung-Yun Baek ◽  
Seung-Min Baek ◽  
...  

This study aims to develop and evaluate an automated manual transmission (AMT) for agricultural tractors with high efficiency and high convenience by using electric actuators. An AMT system to control manual-type shuttle gearboxes and transmissions for tractors is developed by adding a shuttle shifting actuator, a clutch actuator, and a control system to a conventional manual transmission (MT). The clutch actuator is designed using an electric motor and a reduction gear. The AMT control system is developed and experimental tests are conducted to evaluate the performance of the AMT. The results of the performance of the actuator position control demonstrate that the shuttle shifting actuator and clutch actuator are controlled appropriately, achieving a maximum overshoot of less than 5% and 0%, a settling time of less than 0.500 s and 1.50 s, and a steady-state error of less than 1% and 1%, respectively. The performance of the automatic forward and reverse control demonstrates a shift control time of less than 2.50 s and target revolutions per minute (RPM) reaching time of less than 3.00 s. Thus, AMT systems for tractors can be easily developed by applying shuttle shifting actuators, clutch actuators, and a control system to conventional manual transmissions.


Author(s):  
Shusen Lin ◽  
Siqin Chang ◽  
Bo Li

The existing electrically automated manual transmission employs DC motors to carry out gearshift events. It is relatively complicated and has potential to be improved both in structure and transmission efficiency. A novel gearshift system that utilizes a 2-DOF electromagnetic actuator to realize the automation of gearshift is proposed. The structure and working principle are introduced, and the coupling system model of the actuator is developed to investigate its characteristics. The results show that the utilization of the electromagnetic actuator in automated manual transmission gearshift system is appropriate. Multi-stage control strategy including PID algorithm and optimal control is introduced to improve the gearshift quality. A look-up table is developed to adjust the peak force of synchronization process according to the working condition. Finally, the conceptual gearshift system and the control strategy are verified on a test bench. The results show that the controller can adjust the peak force of the synchronization process timely and the designed control strategy achieves the compromise of indexes of gearshift quality. The novel gearshift system is technically feasible.


Actuators ◽  
2021 ◽  
Vol 10 (3) ◽  
pp. 65
Author(s):  
Der-Fa Chen ◽  
Shen-Pao-Chi Chiu ◽  
An-Bang Cheng ◽  
Jung-Chu Ting

Electromagnetic actuator systems composed of an induction servo motor (ISM) drive system and a rice milling machine system have widely been used in agricultural applications. In order to achieve a finer control performance, a witty control system using a revised recurrent Jacobi polynomial neural network (RRJPNN) control and two remunerated controls with an altered bat search algorithm (ABSA) method is proposed to control electromagnetic actuator systems. The witty control system with finer learning capability can fulfill the RRJPNN control, which involves an attunement law, two remunerated controls, which have two evaluation laws, and a dominator control. Based on the Lyapunov stability principle, the attunement law in the RRJPNN control and two evaluation laws in the two remunerated controls are derived. Moreover, the ABSA method can acquire the adjustable learning rates to quicken convergence of weights. Finally, the proposed control method exhibits a finer control performance that is confirmed by experimental results.


2012 ◽  
Author(s):  
Yulong Lei ◽  
Hongbo Liu ◽  
Jun Qiu ◽  
Jianguo Zhang ◽  
Youde Li

Sign in / Sign up

Export Citation Format

Share Document