scholarly journals A High-Performance Indirect Torque Control Strategy for Switched Reluctance Motor Drives

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Cunhe Li ◽  
Cunshan Zhang ◽  
Jian Liu ◽  
Dunxin Bian
Keyword(s):  
Control Strategy ◽  
High Performance ◽  
Switched Reluctance Motor ◽  
Torque Ripple ◽  
Torque Control ◽  
Modulation Method ◽  
Switched Reluctance ◽  
Current Controller ◽  
Torque Control Strategy ◽  
Reluctance Motor

This paper proposes a high-performance indirect control scheme for torque ripple minimization in the switched reluctance motor (SRM) drive system. Firstly, based on the nonlinear torque-angle characteristic of SRM, a novel torque sharing function is developed to obtain the optimal current profiles such that the torque ripple is minimized with reduced copper losses. Secondly, in order to track current accurately and indirectly achieve high-performance torque control, a robust current controller is derived through the Lyapunov stability theory. The proposed robust current controller not only considers the motor parameter modeling errors but also realizes the fixed frequency current control by introducing the pulse width modulation method. Further, a disturbance-observer-based speed controller is derived to regulate the motor speed accurately, and the load torque is considered an unknown disturbance. The simulations and experiments on a 1.5 kW SRM prototype are carried out to demonstrate the effectiveness of the proposed high-performance indirect torque control strategy. Results verify the superiority of the proposed strategy with respect to the torque ripple suppression, system efficiency, and antidisturbance.

scholarly journals Comparison of an Off-Line Optimized Firing Angle Modulation and Torque Sharing Functions for Switched Reluctance Motor Control

Energies ◽  
2020 ◽  
Vol 13 (10) ◽  
pp. 2435
Author(s):  
Peter Bober ◽  
Želmíra Ferková
Keyword(s):  
Switched Reluctance Motor ◽  
Torque Ripple ◽  
Modulation Method ◽  
Objective Functions ◽  
Fem Model ◽  
Switched Reluctance ◽  
Motor Efficiency ◽  
Reluctance Motor ◽  
Sharing Function ◽  
Angle Modulation

In this paper, a comparison of the simple firing angle modulation method (FAM) and the more advanced torque sharing function (TSF)-based control of switched reluctance motor (SRM) is presented. The off-line procedure to tailor and optimize the parameters of chosen methods for off-the-shelf SRM is explained. Objective functions for optimization are motor efficiency, torque ripple, and integral square error. The off-line optimization uses a finite element method (FEM) model of the SRM. The model was verified by measurement on the SRM. Simulation results showed that FAM has comparable efficiency to TSF, but has a much higher value of torque ripple. The presented off-line procedure can be used for single or multi-objective optimization.

scholarly journals Predictive Direct Torque Control of Switched Reluctance Motor for Electric Vehicles Drives

2020 ◽  
Author(s):  
Reyad Abdelfadil ◽  
László Számel
Keyword(s):  
Electric Vehicles ◽  
High Performance ◽  
Direct Torque Control ◽  
Switched Reluctance Motor ◽  
Power Converter ◽  
Torque Control ◽  
Switching Frequency ◽  
Suggested Approach ◽  
Switched Reluctance ◽  
Reluctance Motor

The electrical drive systems utilized in Electric Vehicles (EVs) applications must be reliable and high performance. To providing these specifications, it is essential to design high-efficiency electric motors and develop high-performance controllers. This study introduces direct torque control of Switched Reluctance Motor (SRM) for electric vehicle applications using Model Predictive Control (MPC) technique. The direct torque control using MPC is proposed to maintain the motor torque and motor speed to tracking desired signals with a satisfactory response. In this study, the MPC algorithm was programmed in C- language, and the simulation tests were performed using a non-linear model of 6/4 - 60 kW SRM that is fed with the symmetrical converter. The proposed controller was tested under different load conditions to verify the robustness of the controller, as well as at variable speeds to investigate the tracking performance. Thanks to the proposed method, the SRM torque ripples, stator copper losses, and average switching frequency of the power converter can reduce effectively due to applying a cost function that combines multiple objectives. The obtained outcomes show the effectiveness of the suggested approach compared to conventional direct torque control techniques.

scholarly journals Model Free Adaptive Control of Switched Reluctance Motor for Electric Vehicle

2021 ◽  
pp. 104-114
Author(s):  
Xifeng Mi , Yuanyuan Fan
Keyword(s):  
Neural Network ◽  
Control Strategy ◽  
Control Method ◽  
Rbf Neural Network ◽  
Switched Reluctance Motor ◽  
Torque Ripple ◽  
Torque Distribution ◽  
Switched Reluctance ◽  
Model Free ◽  
Reluctance Motor

In this paper, the model free adaptive control method of switched reluctance motor for electric vehicle is studied. Based on the torque distribution control of SRM, a SRM control strategy based on torque current hybrid model based on RBF neural network is proposed in this paper. Based on the deviation between the dynamic average value and instantaneous value of SRM output torque, the online learning of RBF neural network is realized. At the same time, this paper constructs a torque current hybrid model, obtains the current variation law of SRM under low torque ripple operation, and reduces the torque ripple of SRM. The SRM torque distribution control is realized on the SRM experimental platform. Compared with the voltage chopper control method, the experimental results show that the torque ripple of SRM can be reduced by adopting the torque distribution control strategy.

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