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

2021 ◽  
pp. 157-164
Author(s):  
Xiaoliang Zhang
Keyword(s):  
Electric Vehicle ◽  
Electric Vehicles ◽  
High Efficiency ◽  
Good Control ◽  
Switched Reluctance Motor ◽  
Regulation System ◽  
Network Parameter ◽  
Switched Reluctance ◽  
Speed Regulation ◽  
Reluctance Motor

Based on the analysis of the related theories of switched reluctance motor, this paper designs and implements the intelligent speed regulation system of switched reluctance motor for electric vehicle. The speed regulation system has the characteristics of high efficiency and energy saving, wide speed regulation range and small starting current. The system also has the advantages of large starting torque, frequent start and stop, forward and reverse switching, high torque / inertia ratio and four quadrant operation. The system can provide a good solution for variable speed drive. The digital controller of the system is composed of TMS320F2812 DSP and EPM7128S CPLD, which can realize the starting, electric and braking functions of electric vehicles. Experiments show that the switched reluctance motor drive system for electric vehicle has good control performance and strong fault tolerance. The system can meet the requirements of various working conditions of electric vehicles and has broad development prospects.

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.

Modeling and Performance Analysis of Switched Reluctance Motor in Electric Vehicles

2014 ◽  
Vol 532 ◽  
pp. 26-30
Author(s):  
Yue Ying Zhu ◽  
Jiang Feng Mou
Keyword(s):  
Performance Analysis ◽  
Electric Vehicle ◽  
Electric Vehicles ◽  
Dynamic Performance ◽  
Switched Reluctance Motor ◽  
Power Performance ◽  
Nonlinear Dynamic Model ◽  
Switched Reluctance ◽  
Reluctance Motor ◽  
And Performance

The power performance of the Switched Reluctance Motor (SRM) drive used in electric vehicles is very important for improving the dynamic performance of the vehicle and matching the parameters of the vehicle power train. In order to analyses the drive performance of the SRM drive under the electric vehicle, the nonlinear dynamic model of the SRM drive is established in the MATLAB/Simulink environment. Then the vehicle dynamic load model is designed to connect with the SRM drive model, and the performance analysis of the SRM used in the developing electric vehicle is carried out based on power output and equivalent power factor. The analysis results are significant for the design and improvement of the electric vehicle.

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