Switched reluctance motor modelling with on-line parameter identification

2002 ◽  
Author(s):  
S. Mir ◽  
I. Husain ◽  
M. Elbuluk
Keyword(s):  
Parameter Identification ◽  
Switched Reluctance Motor ◽  
Switched Reluctance ◽  
Line Parameter ◽  
Reluctance Motor ◽  
On Line

A simple turn-on and turn-off angles searching method for copper loss minimization of the switched reluctance motor

2017 ◽  
Vol 36 (4) ◽  
pp. 1059-1074
Author(s):  
Hai-Jin Chen ◽  
Jin-Yang Li
Keyword(s):  
Switched Reluctance Motor ◽  
Loss Minimization ◽  
Content Type ◽  
Switched Reluctance ◽  
Analytical Computation ◽  
Copper Loss ◽  
Turn On ◽  
Reluctance Motor ◽  
On Line ◽  
Optimal Turn

Purpose The purpose of this paper is to present a simple and effective method to search the optimal turn-on and turn-off angles on-line for the control of the switched reluctance motor (SRM). The optimal turn-on and turn-off angles are defined as the ones that can meet torque production requirements with minimum copper loss. Design/methodology/approach The optimal turn-on and turn-off angles are first defined based on the analysis of the SRM losses and torque production principles. Then the algorithm for optimal angles searching is developed, and the searching parameters are determined through analytical computation. The optimal angles are approached on-line with iterative process. Simulation and experiments are finally performed to verify the proposed method. Findings The presented method can meet torque production requirements while copper loss is minimized. The optimal turn-on and turn-off angles are generally approached within five phase cycles for most of the SRM operation modes. Furthermore, the SRM drive system using the presented method exhibits good dynamics during starting and sudden load operations. Practical implications The presented method is simple, and implementation of it is easy. It is an eligible candidate for industrial applications where energy conversion efficiency is crucial. Originality/value The optimal turn-off angle definition that considers both torque production and copper loss minimization is proposed. The turn-on and turn-off angles are searched independently on-line with little SRM geometrical information. The searching steps are derived through analytical computation and qualitative analysis so that both the searching speed and algorithm convergence are balanced.

On-line estimation of switched reluctance motor parameters

2018 ◽  
Vol 32 (6) ◽  
pp. 950-966 ◽  
Author(s):  
Missie Aguado-Rojas ◽  
Paul Maya-Ortiz ◽  
Gerardo Espinosa-Pérez
Keyword(s):  
Switched Reluctance Motor ◽  
Switched Reluctance ◽  
Reluctance Motor ◽  
On Line

scholarly journals Intelligent Speed Regulation Control in Switched Reluctance Motor of Electric Vehicle Based on Neural Network Parameter Identification

2021 ◽  
pp. 173-180
Author(s):  
Huang Zongjian
Keyword(s):  
Neural Network ◽  
Parameter Identification ◽  
Electric Vehicle ◽  
Bp Neural Network ◽  
Switched Reluctance Motor ◽  
Network Parameter ◽  
Nonlinear Simulation ◽  
Switched Reluctance ◽  
Speed Regulation ◽  
Reluctance Motor

This paper studies the intelligent speed regulation control of switched reluctance motor of electric vehicle based on neural network parameter identification. Starting with the analysis of the performance of switched reluctance motor, the nonlinear flux linkage characteristic inversion model and torque characteristic model of switched reluctance motor are established based on BP neural network. This paper studies and improves the fast self configuration algorithm of BP neural network. Finally, the nonlinear simulation model of switched reluctance motor is established under Matlab/Simulink. The model can be used for further control research. In this paper, the integrated control method of instantaneous torque control based on torque observation and three-step commutation control is studied, and the simulation analysis is carried out. The results show that this method can effectively reduce the torque ripple of switched reluctance motor and improve the performance of its drive system.

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