Improving the gearshifts events in automated manual transmission by using an electromagnetic actuator

2014 ◽  
Vol 229 (9) ◽  
pp. 1548-1561 ◽  
Author(s):  
Shusen Lin ◽  
Siqin Chang ◽  
Bo Li
Keyword(s):  
Control Strategy ◽  
Transmission Efficiency ◽  
Peak Force ◽  
Manual Transmission ◽  
Electromagnetic Actuator ◽  
Synchronization Process ◽  
Pid Algorithm ◽  
Multi Stage ◽  
Coupling System ◽  
Automated Manual Transmission

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.

scholarly journals Control strategy of automated manual transmission based on active synchronisation of driving motor in electric bus

2019 ◽  
Vol 11 (4) ◽  
pp. 168781401984673
Author(s):  
Yulong Lei ◽  
Jianlong Hu ◽  
Yao Fu ◽  
Shaohua Sun ◽  
Xingzhong Li ◽  
...  
Keyword(s):  
Control Strategy ◽  
Manual Transmission ◽  
Electric Bus ◽  
Automated Manual Transmission

Simulation and Optimal Control of AMT Starting-up Process

2013 ◽  
Vol 380-384 ◽  
pp. 672-675
Author(s):  
Li Na Ren ◽  
Na Na Tang ◽  
Han Qi Yue ◽  
Bing Zhao Gao
Keyword(s):  
Optimal Control ◽  
Simulation Model ◽  
Control Strategy ◽  
Pid Control ◽  
Manual Transmission ◽  
Optimal Control Strategy ◽  
Automated Manual Transmission ◽  
Starting Process ◽  
Set Up ◽  
Experimental Values

For a vehicle with 5-speed AMT (Automated Manual Transmission), AMESim model of the powertrain is set up, and comparison of simulation and experimental values is carried out to test the reliability of the simulation model. Through the co-simulation of AMESim and Simulink, we use optimal control and PID control respectively to control the starting process. The simulation result indicates that the optimal control strategy can satisfy the requirement for the drivability and smoothness.

A novel multi-parameter coordinated shift control strategy for an automated manual transmission based on fuzzy inference

2016 ◽  
Vol 231 (5) ◽  
pp. 684-699 ◽  
Author(s):  
Lipeng Zhang ◽  
Xiaohong Zhang ◽  
Zongqi Han ◽  
Junyun Chen ◽  
Jingchao Liu
Keyword(s):  
Control Strategy ◽  
Dynamic Performance ◽  
Automatic Transmission ◽  
Rate Of Change ◽  
Manual Transmission ◽  
Vehicle Speed ◽  
Shift Control ◽  
Automated Manual Transmission ◽  
Shift Strategy ◽  
Driver’S Intention

For a vehicle equipped with an automatic transmission, the shift control strategy should reflect the driver’s intention in the dynamic performance and the economy performance of the vehicle. However, the driver’s intention is difficult to identify and involve in the shift strategy because of the complexity of driving environments, the diversity of powertrain parameters and the randomness of the driver’s behaviour. Therefore, in this paper, by considering a vehicle equipped with an automated manual transmission as the study object, a novel multi-parameter coordinated shift control strategy is proposed on the basis of identification of the driver’s intention. First, in order to predict the intention of the driver more effectively, the relative opening degree of the accelerator is defined on the basis of the dynamic analysis. Then, the characteristics of the driver’s expected acceleration, which involve the influence of the driving environment, are proposed. They can be classified into five categories, namely stop, deceleration, keep, acceleration and urgent acceleration. Next, a fuzzy control system is designed to identify the driver’s acceleration characteristics in real time. This considers the vehicle speed, the rate of change in the opening degree of the accelerator and the relative opening degree of the accelerator as the inputs and the quantitative intention of the driver as the output. Finally, the novel multi-parameter coordinated shift control strategy is formulated on the basis of the vehicle speed, the opening degree of the accelerator and the quantitative intention of the driver. The designed shift strategy is compared with conventional methods using simulations and is verified by road tests. The results show that the shift control strategy can make the vehicle shift much more effective.

Gear Shifting Control for Pure Electric Vehicle with Inverse-AMT

2012 ◽  
Vol 190-191 ◽  
pp. 1286-1289 ◽  
Author(s):  
Qiong Liang ◽  
Bing Zhao Gao ◽  
Hong Chen
Keyword(s):  
Electric Vehicle ◽  
Control Strategy ◽  
Drive Train ◽  
Manual Transmission ◽  
Precise Control ◽  
Clutch Engagement ◽  
Automated Manual Transmission ◽  
Set Up ◽  
Driving Torque ◽  
Train System

In this study, the gear shifting control strategy for pure electric vehicle with inverse automated manual transmission (I-AMT) is proposed. Based on a new drive train system of pure electric vehicle, an AMESim model of vehicle drive-train system is set up. Through the precise control of sliding sleeve, clutch engagement and separating time, gear shifting process is realized without driving torque interruption. The results show that, during up and down shift process, the driving torque keeps more than 50%, obviously improve the pure electric vehicle accelerating performance and the ability to climb.

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