A Novel Method of Phase Current Compensation for Switched Reluctance Motor System Based on Finite Element

Zhang, Haijun; Zhang, Jingjun; Gao, Ruizhen

doi:10.4304/jcp.4.10.1064-1071

Cited by 4 publications

(3 citation statements)

References 20 publications

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“…The basic principles of the compensation theory have been discussed in different issues as in [11] and [12]. Actually, the SRM driving system as shown in Figure 7 is running in a speed control mode.…”

Section: The Compensation Proceduresmentioning

confidence: 99%

A New Phase Current Profiling with FLC f or Torque Optimization of 12/8 SRM

Saidani¹,

Hachicha²,

Ghariani³

2016

IJECE

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The switched reluctance machine against its several merits such as simplicity, robustness, less cost manufacturing and large speed still suffers from its undesirable torque ripple and acoustic noise. Compared to different candidates of hybrid and electric vehicle engine, the frequency of use of SRM in traction drives is improved with the different optimizing torque oscillation solutions. Most of studies used the generic or specific model of switched reluctance machine in the Simulink library (6/4,8/6 and 10/8). Despite, a new non linear model simply implemented in Simulink tool using a static finite element analysis a previous study is used in this work. Hence, a 12/8 non linear SRM drive system is simulated using MATLAB toolbox tested with an intelligent controller (FLC) in order to minimize the torque ripple of an oriented starter -alternator application of a hybrid vehicle.

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Section: The Compensation Proceduresmentioning

confidence: 99%

A New Phase Current Profiling with FLC f or Torque Optimization of 12/8 SRM

Saidani¹,

Hachicha²,

Ghariani³

2016

IJECE

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“…Zhang et al [9] also used fuzzy controller to compute the current compensating signal that added to the main current value in order to reduce torque ripple. While Shang et al [10] introduced flux-linkage controller using sliding mode technique (SM) with integral compensation (I).…”

Section: Introductionmentioning

confidence: 99%

Adaptive Neuro-fuzzy Controller for Multi-layered Switched Reluctance Motor

Arakat¹,

Haikal²,

Kassem³

2012

IJCA

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There has been big interest in switched reluctance motor (SRM) due to its simplicity and reasonable cost, however excessive torque ripple is one of the major disadvantages of switched reluctance motor. This paper attempts to reduce torque ripples of Switched Reluctance Motor through building multi-layered motor controlled by a hybrid intelligent system known as Adaptive Neuro-fuzzy Inference System ANFIS. Simulation of the proposed motor is conducted using Matlab Simulink environment 2011 and comparison results with single layer switched reluctance motor for both PI and ANFIS controllers show improvement in behavior of MSRM controlled by ANFIS through reduction in speed settling time as well as torque ripples.

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“…These papers [6], [7] describes the design, modeling and control of Switched Reluctance Motor Drive using DSP processor for steady state conditions only the problem of harmonics not to be considered, in these papers a novel method of torque closed loop control and fuzzy compensation control based on finite element model for SRM drive is described. In these [8], [9], [10] papers a new sensor less control scheme using finite element package MAXWELL has been explained and it is compared with sensor mode. The Switched Reluctance Motor is a doubly salient machine with no rotor windings.…”

Section: Introductionmentioning

confidence: 99%