Abstract

The paper deals with nonlinear simulation models of a drive consisting of the four-phase 8/6 doubly salient switched reluctance motor (SRM), the four-phase dissymmetric bridge power converter and the closed-cycle rotor speed control strategy carried out by the pulse width modulation (PWM) with variable angle and combined control scheme with the PI algorithm. All presented considerations are based on a MATLAB-SIMULINK platform. The nonlinear mathematical model of the analyzed SRM drive was obtained as a combination of the two dimensional (2D) finite element model (FEM) of the motor and the nonlinear model of the electrical network of the power supply circuit. The main model and its seven sub-modules, such as the controller module, one phase simulation module, rotor position angle transformation module, power system module, phase current operation module, “subsystem” module, and electromagnetic torque of one phase operation module, are described. MATLAB functions store the magnetization curves data of the motor obtained by the 2D FEM electromagnetic field calculations, as well as the data of magnetic co-energy curves of the motor calculated from the magnetization curves. The 2D specimen insert method is adopted in MATLAB functions for operating the flux linkage and the magnetic co-energy at the given phase current and rotor position. The phase current waveforms obtained during simulations match with the tested experimentally phases current waveforms at the same rotor speed and the same load basically. The simulated rotor speed curves also agree with the experimental rotor speed curves. This means that the method of suggested nonlinear simulation models of the analyzed SRM drive is correct, and the model is accurate.

Highlights

  • Simulation model of the 4-phase 8/6 poles switched reluctance motor (SRM) drive has been developed on a MATLAB-SIMULINK platform, which is combined with the magnetization curves

  • The electrical presented nonlinear simulation model of the 4-phase 8/6 poles SRM drive has been developed closed-cycle rotor speed control strategy have been realized by the variable angle pulse width on a MATLAB-SIMULINK platform, which is combined with the magnetization curves data computed by the 2D electromagnetic field FE analysis (Figures 11 and 12)

  • The nonlinear electrical meshwork model of the 4-phase asymmetric bridge power electronics main circuit and the closed-cycle rotor speed control strategy have been realized by the variable angle pulse width modulation combined control scheme with the PI algorithm

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Summary

Introduction

The switched reluctance motor (SRM) drive, described comprehensively in [1], has been developed for mining equipment [2], electric vehicles [3], high speed equipment [4], different generators [5,6], wind generators [7], high speed and high power applications [8,9], flywheel energy storage applications [10], linear transportation [11], automotive applications [12], and so on, due to favorable conditions in the design of the motor and power supply, ease of four quadrants operation, high start torque with low start current, high efficiency within vast rotor speed ranges, high dependability with the independence of magnetic paths for each phase and the independence of circuits in each phase. The paper [31] states that a nonlinear model of SRM is characterized by state variables which are constant in the steady-state This in turn facilitates the high-speed simulation, control and design of the machine. In high-performance systems for the real-time control, models based on invertible equation can be very helpful This expression is useful when the set current is derived of the torque command and denoting the torque-phase current relationship [32]. The SRM power supply circuit and the closed-cycle rotor speed control strategy have been realized the by variable angle pulse width modulation control scheme together with the the simulation solution of phase current waveforms and rotor speed curves were compared with the the variable angle pulse width modulation control scheme together with the PI algorithm.

System
Cross-section
Simulation Models
It the power
The input “Constant”
12. Magnetic
17. Figure
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