Electromagnetic torque control for six-phase induction motor expelled continuously variable transmission clumped system using sage dynamic control system

2020 ◽  
pp. 1-30
Author(s):  
Der-Fa Chen ◽  
An-Bang Cheng ◽  
Shen-Pao-Chi Chiu ◽  
Jung-Chu Ting
Keyword(s):  
Control System ◽  
Induction Motor ◽  
Dynamic Control ◽  
Continuously Variable Transmission ◽  
Torque Control ◽  
Electromagnetic Torque ◽  
Variable Transmission ◽  
Dynamic Control System

An intelligent dynamic control of continuously variable transmission system using modified particle swarm optimization

2015 ◽  
Vol 230 (13) ◽  
pp. 2181-2207 ◽  
Author(s):  
Chih-Hong Lin
Keyword(s):  
Neural Network ◽  
Particle Swarm Optimization ◽  
Control System ◽  
Orthogonal Polynomials ◽  
Dynamic Control ◽  
Continuously Variable Transmission ◽  
Transmission System ◽  
Swarm Optimization ◽  
Modified Particle Swarm Optimization ◽  
Variable Transmission

In order to capture nonlinear and dynamic behaviors of the V-belt continuously variable transmission system with lots of unknown nonlinear and time-varying characteristics, an intelligent dynamic control system using modified particle swarm optimization is proposed for controlling a permanent magnet synchronous motor servo-drive V-belt continuously variable transmission system to raise robustness. The intelligent dynamic control system comprised an inspector control system, a recurrent Laguerre-orthogonal-polynomials neural network controller with adaptive law and a recouped controller with estimation law. The adaptive law of parameters in the recurrent Laguerre-orthogonal-polynomials neural network is derived according to Lyapunov stability theorem. To achieve better learning performance and faster convergence, the modified particle swarm optimization is employed to regulate two varied learning rates of the parameters in the recurrent Laguerre-orthogonal-polynomials neural network. At last, comparative studies shown by experimental results are illustrated to demonstrate the control performance of the proposed control scheme.

Investigation of Motor-Generator Integration System for Electric Vehicle Based on Induction Motor and Fuzzy Control

2011 ◽  
Vol 328-330 ◽  
pp. 2172-2180 ◽  
Author(s):  
Zhi Long Xing ◽  
Yang Liu ◽  
Yun Feng Liu
Keyword(s):  
Control System ◽  
Fuzzy Control ◽  
Induction Motor ◽  
Electric Vehicle ◽  
Control Strategy ◽  
Energy Recovery ◽  
Direct Torque Control ◽  
Torque Control ◽  
Torque Control Strategy ◽  
Ac Induction Motor

Aiming to solve the energy saving problem in modern electric vehicle, we propose a motor-generator integration control system based on the induction motor and the fuzzy control theory in this paper. A motor-generator hardware platform is built up using the four quadrant characteristic of AC induction motor. The AC induction motor works both as driving motor of the electric vehicle and as well as the energy recovery generator. Specifically, the fuzzy direct torque control strategy is adopted in the motor state, and fuzzy instantaneous torque control strategy in power generation state. A simulation is carried out to analyze the practicality of the proposed control method, the simulation results show that the fuzzy torque control technology is well performed. Finally, a simulative energy recovery experimental platform is built up to test the proposed integration control system, and results shown that the efficiency of energy recovery could be up to 97.3%.

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