Starting Control with Constant Engine Speed for AMT Automotive Based on Neural Network

2012 ◽  
Vol 184-185 ◽  
pp. 1637-1642
Author(s):  
Dong Ye Sun ◽  
Xue Feng Zhang ◽  
Qing Lin Wu ◽  
Lei Zhang
Keyword(s):  
Neural Network ◽  
Control Strategy ◽  
Engine Speed ◽  
Accelerator Pedal ◽  
Target Speed ◽  
Starting Time ◽  
The Neural Network ◽  
Clutch Engagement ◽  
Clutch Control ◽  
Starting Control

Starting control with constant engine speed of AMT automotive is a clutch control means based on the target accelerator pedal opening. According to the different accelerator pedal opening, the clutch engagement speed will be different. The neural network is used to estimate the target accelerator pedal opening by the start of the initial accelerator pedal opening variation. Thus completing the engine target speed and clutch engagement speed is to make sure the AMT start fast and smoothly. The results showed that: through estimating the target accelerator pedal opening, this control strategy can shorten the starting time and improved control quality significantly.

Study on Electro-Pneumatic Clutch for Automatic Mechanical Transmission

2011 ◽  
Vol 148-149 ◽  
pp. 1149-1153
Author(s):  
Wu Chao Zhang ◽  
Yong Zhai
Keyword(s):  
Diesel Engine ◽  
Field Experiment ◽  
Control Strategy ◽  
Engine Speed ◽  
Mechanical Transmission ◽  
Control Law ◽  
Clutch Engagement ◽  
Automotive Powertrain ◽  
System Requirements ◽  
Clutch Control

The clutch control is one of the cores and most difficult issues in the development of an AMT system. In this paper the pneumatic clutch engagement characteristic is analyzed. Thereto, a simulation model of an automotive powertrain comprises a diesel engine, drivetrain and wheels driving a vehicle through tire-road adhesion are built using Matlab/Simulink. In the simulation, a refined control law of constant engine speed in part process is proposed and tested. The engaging speed and displacement of the clutch vary with the accelerate paddle opening, engine speed, clutch driven plate speed and gears according the control law. Field experiment results show that the control strategy fulfills the system requirements.

scholarly journals Lookup Table and Neural Network Hybrid Strategy for Wind Turbine Pitch Control

2021 ◽  
Vol 13 (6) ◽  
pp. 3235
Author(s):  
J. Enrique Sierra-García ◽  
Matilde Santos
Keyword(s):  
Neural Network ◽  
Wind Turbine ◽  
Control Strategy ◽  
Neural Control ◽  
Mapping Function ◽  
Energy System ◽  
Lookup Table ◽  
Hybrid Strategy ◽  
Pitch Control ◽  
The Neural Network

Wind energy plays a key role in the sustainability of the worldwide energy system. It is forecasted to be the main source of energy supply by 2050. However, for this prediction to become reality, there are still technological challenges to be addressed. One of them is the control of the wind turbine in order to improve its energy efficiency. In this work, a new hybrid pitch-control strategy is proposed that combines a lookup table and a neural network. The table and the RBF neural network complement each other. The neural network learns to compensate for the errors in the mapping function implemented by the lookup table, and in turn, the table facilitates the learning of the neural network. This synergy of techniques provides better results than if the techniques were applied individually. Furthermore, it is shown how the neural network is able to control the pitch even if the lookup table is poorly designed. The operation of the proposed control strategy is compared with the neural control without the table, with a PID regulator, and with the combination of the PID and the lookup table. In all cases, the proposed hybrid control strategy achieves better results in terms of output power error.

Starting Control Strategy and Experimental Study of CNG Engine

2012 ◽  
Vol 562-564 ◽  
pp. 1044-1047
Author(s):  
Yi Tuan He ◽  
Fan Hua Ma ◽  
Zheng Liang Qi ◽  
Ren Zhe Chen
Keyword(s):  
Experimental Study ◽  
Control Strategy ◽  
Pulse Width ◽  
Engine Speed ◽  
Spark Timing ◽  
Cng Engine ◽  
Hc Emissions ◽  
Starting Control ◽  
Injection Pulse

To reduce the HC emissions of a CNG engine during starting period, starting experiments were carried out on a CNG engine. Injection pulse width (IPW) and spark advance angle () were controlled. The results indicate that wider injection pulse width and earlier spark timing cause higher HC emissions. To guarantee a reliable start and low HC emissions, the engine should start with relatively wider injection pulse width and earlier spark timing, and the injection pulse width and spark advance angle should be reduced gradually after the engine speed is steady.

Study on Decreasing Vibration of High-Speed Train Semi-Active Suspension System

2011 ◽  
Vol 230-232 ◽  
pp. 1104-1109
Author(s):  
Zhen Ping Fan ◽  
Heng Zeng ◽  
Jian Wei Yang ◽  
Jie Li
Keyword(s):  
Neural Network ◽  
Control Strategy ◽  
High Speed ◽  
Driving Safety ◽  
High Speed Train ◽  
Proportional Valve ◽  
Joint Simulation ◽  
The Neural Network ◽  
Adaptive Control Strategy ◽  
Active Damper

Lateral semi-active damper is designed by author based on the electro-hydraulic proportional valve, from the perspective angle of improving vehicle comfort; its purpose is to ensure vehicle driving safety. At the same time, the neural network adaptive control strategy is used for joint simulation of semi-active damper. The results show that lateral semi-active damper with the train body has significantly improved compared to the traditional passive lateral damper acceleration.

Neural network inverse system decoupling control strategy of BLIM considering stator current dynamics

2018 ◽  
Vol 41 (3) ◽  
pp. 621-630 ◽  
Author(s):  
Wenshao Bu ◽  
Fangzhou He ◽  
Ziyuan Li ◽  
Haitao Zhang ◽  
Jingzhuo Shi
Keyword(s):  
Neural Network ◽  
Control System ◽  
Control Strategy ◽  
Displacement Component ◽  
Inverse System ◽  
Decoupling Control ◽  
Motor Speed ◽  
State Equations ◽  
Stator Current ◽  
The Neural Network

The bearingless induction motor (BLIM) is a multi-variable, non-linear, strong coupling system. To achieve higher performance control, a novel neural network inverse system decoupling control strategy considering stator current dynamics is proposed. Taking the stator current dynamics of the torque windings into account, the state equations of the BLIM system is established first. Then, the inverse system model of the BLIM is identified by a three-layer neural network; by means of the neural network inverse system method, the BLIM system is decoupled into four independent second-order linear subsystems, include a rotor flux subsystem, a motor speed subsystem and two radial displacement component subsystems. On this basis, the neural network inverse decoupling control system is constructed, the simulation verification and analyses are performed. From the simulation results, it is clear that when the proposed decoupling control strategy is adopted, not only can the dynamic decoupling control between relevant variables be achieved, but the control system has a stronger anti-load disturbance ability, smaller overshoot and better tracking performance.

Neural Network Adaptive Control of Free Floating Space Robot with Actuator Saturation

2014 ◽  
Vol 590 ◽  
pp. 380-385 ◽  
Author(s):  
Guo Liang Zhang ◽  
Ting Lei ◽  
Fan Yang ◽  
Zhuang Cai
Keyword(s):  
Neural Network ◽  
Adaptive Learning ◽  
Control Strategy ◽  
Actuator Saturation ◽  
Space Robot ◽  
Global Approximation ◽  
Neural Network Approach ◽  
The Neural Network ◽  
On Line ◽  
The Stability

This paper proposes an adaptive neural network law for trajectory tracking of a class of free-floating space robot with actuator saturation. Using neural network with global approximation, the control strategy design an on-line real time adaptive learning law to approach the uncertain model and the actuator saturation nonlinearity. The neural network approach errors and outside disturbance can be eliminated by a robust controller.The control strategy need not depend on the model, and can be used under actuator saturation.The control strategy can guarantee the stability of system and the asymptotic convergence of tracking errors based on the Lyapunov’s theory. The simulation results indicate that the proposed strategy can effectively work with actuator saturation.

scholarly journals An Islanding Detection and Control Strategy to Realize the Stable and Autonomous Operation of Microgrids Using the Virtual Synchronous Generator

2021 ◽  
Vol 9 (11) ◽  
pp. 1315-1333
Author(s):  
Illuru Sree Lakshmi
Keyword(s):  
Neural Network ◽  
Control Strategy ◽  
Synchronous Generator ◽  
Islanding Detection ◽  
Neural Network Approach ◽  
Autonomous Operation ◽  
The Neural Network ◽  
Control Stability ◽  
And Control ◽  
Virtual Synchronous Generator

Abstract: An islanding detection and based control strategy is created in this exploration to accomplish the steady and independent activity of microgrids using the neural network based Virtual Synchronous Generator (VSG) idea during unplanned grid reconfigurations . Maybe of utilizing a design-orientedmethodology, this paper gives a rigorous and extensive hypothetical investigation and reaches a concise conclusion that is easy to execute and successful even in complex situations. Based on the results of the mutation sequence and voltage wavering, a neural network based islanding identification calculation is proposed, which requires less constraint strategy. The proposed neural network approach outperforms the thefrequency measured passive detection method in terms of detection speed and reliability. Broad recreations affirm the reasonableness of the proposed islanding location and control methodology. Additionally, think about the results of the reproductions for the PI regulator, fluffy organizations, and neural organizations. Keywords: Virtual Synchronous Generator, Islanding detection, Islanding operation, Droop control, Stability, Microgrids.

Optimal Fuzzy Control of Automated Mechanical Transmission Clutch Engagement during Start-Up Process

2013 ◽  
Vol 694-697 ◽  
pp. 2089-2093 ◽  
Author(s):  
Han Yu Jin ◽  
Xiu Sheng Cheng ◽  
Yong Dao Song
Keyword(s):  
Control Strategy ◽  
Control Unit ◽  
Mechanical Transmission ◽  
Subtle Change ◽  
Start Up ◽  
Clutch Engagement ◽  
Driver’S Intention ◽  
Starting Process ◽  
Clutch Control ◽  
The Impact

Engagement control of the clutch in the starting process is the core part and difficulty of the Automated Mechanical Transmission (AMT) control strategy, which was directly related to the clutch disc lifetime and riding. Engine speed, clutch speed and throttle angle are the only signals to develop clutch control strategy in the entire start-up process made by Transmission Control Unit (TCU) in a vehicle equip with AMT. The TCU even need to determine the driver's intention to select different control schemes. In this paper, fuzzy logic control was adopted in order to eliminate the impact of subtle change during driver operation, thus the start quality was optimized.

Hybrid Neural Network for Modeling Automotive Clutches

1999 ◽  
Author(s):  
V. Parvataneni ◽  
M. Cao ◽  
K. W. Wang ◽  
Y. Fujii ◽  
W. Tobler
Keyword(s):  
Neural Network ◽  
Hybrid Model ◽  
Hybrid Network ◽  
Hybrid Neural Network ◽  
Physical Knowledge ◽  
The Neural Network ◽  
Clutch Engagement ◽  
Wet Clutch ◽  
Engagement Process ◽  
Artificial Neural Network Ann

Abstract In this paper, artificial neural network (ANN) based models to capture the dynamic engagement torque of a wet clutch system are developed and analyzed. A two-layer recurrent ANN with output feedback is chosen as the baseline architecture since its simplicity allows easy implementation and efficient execution. Although this model exhibits good performance in capturing the overall mean level of the engagement torque as a function of time, it is unable to predict some of the important clutch dynamics behaviors. To improve the performance, additional neurons that represent the first principles of the clutch engagement process are incorporated into the neural network model. In other words, a hybrid model in which physical knowledge is implicitly embedded within the ANN architecture is derived. This hybrid model is trained and tested with experimental data. The results show that the performance of the hybrid network is much superior to that of the baseline ANN. It can successfully capture not only the trends, but also the detailed characteristics of the clutch engagement torque as a function of time.

Dual Clutch Automatic Transmission Two Clutch Starting Control and Simulation

2013 ◽  
Vol 372 ◽  
pp. 538-542
Author(s):  
Guo Zhong Jia ◽  
Xin Ping Wu ◽  
Zhen Hua Jia
Keyword(s):  
Simulation Model ◽  
Control Strategy ◽  
Control Strategies ◽  
Automatic Transmission ◽  
Control Model ◽  
Launch Strategy ◽  
Simulation Results ◽  
Clutch Control ◽  
The Impact ◽  
Starting Control

According to the special structure of DCT, the control strategy of launch with two clutches has been proposed to share the friction work and extend the life of both clutches. The dynamic model of launch with two clutches and the clutch control model have been built. the control strategies of both clutches have been proposed respectively according to the requirement of the different driver intention and the limitation of the impact of vehicle. The simulation model of launch with two clutches has been built using the Matlab/Simulink platform, and the simulation has been carried out. The Simulation results show that the balance of friction work based on this launch strategy with two clutches has been validated.

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