Torque ripple minimization of a Switched Reluctance Motor using … · 2018-11-26 · Torque ripple minimization of a Switched Reluctance Motor using Fuzzy logic control Current compensating

Torque ripple minimization of a SwitchedReluctance Motor using Fuzzy logic

control Current compensating technique

P. Pranay Kumar1,1Department of Electrical and Electronics

Engineering.1Vaageswari college of Engineering,

Karimnagar, [email protected]

October 12, 2018

Abstract

Switched reluctance motors (SRMs) are attractive forindustrial applications because of their structural simplicityand low cost, ruggedness capability to cover a wide speedrange and relatively high torque-to-mass ratio. The pri-mary disadvantage of an SRM is the higher torque ripplecompared with conventional machines, which contributesto acoustic noise vibration. The origin of torque pulsa-tions in an SRM is due to the highly nonlinear discretenature of torque production mechanism. Torque-ripple re-duction in switched reluctance motors (SRM) has becomea major research theme. In servo control applications orwhen smooth control is required at low speeds, reductionof the torque ripple becomes the main issue in an accept-able control strategy. In this paperan intelligent controllersuch as Fuzzy Logic Controller (FLC) current compensat-ing technique is employed for minimizing the torque ripplesin switched reluctance motor. For the purpose of compari-son, the performance of conventional Proportional- Integral

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(PI) controller PID controller are also considered. The sta-tistical parameters like minimum, maximum, mean of totaltorque, torque ripple coefficient are reported. From the sim-ulation results, it is found that both FLC-PID FLC-PI con-troller gives better performance than conventional PI PIDcontrollers, thereby improves the dynamic performance ofSRM drives.Key Words:: SRM, FLC, PID controller, membershipfunctions, FLC-PID controller

1 Introduction

Switched reluctance motors (SRM) have many advantageous char-acteristics comparing to those of the conventional AC and DC ma-chines. The mechanical simplicity in construction of the SRM canbe seen through their purely laminated-steel structure without per-manent magnets, rotor windings and squirrel-cage bars. Thus, SRmachines offer high reliability and robustness in operation. Due totheir ruggedness, the SR motors are inherently suitable for high-speed drives and applications in high-temperature and hazardousenvironments. In addition, the SRM are efficient and suitable forsome applications which required high torque and high dynamics.The highly non-uniform reluctance torque is produced from mag-netic saliency between stator poles and rotor poles. Phase fluxlinkages and instantaneous phase torque are nonlinear functionsof phase currents and rotor positions. Therefore, without propercontrol, the inherent torque ripples, vibrations and acoustic noisecan become major problems of the SRM drives. The minimiza-tion of torque ripples is essential in high performance servo ap-plications which require smooth operation with minimum torquepulsations. The excellent positive features of an SRM may be uti-lized in a servo system by developing techniques for reducing thetorque ripples. The simple and popular current compensating tech-niques can be implemented using both classical and intelligent con-trollers. The classical controllers require exact mathematical modelof the systems and are very sensitive to parameter variations AsSRM presents strong non linear characteristics, the dynamic con-trol of SRM drive can be obtained by using intelligent controllersbased on artificial intelligent techniques such as fuzzy logic con-

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troller. However, in the case of servo control applications or whensmooth control is required at low speeds, the elimination of thetorque ripples becomes the main issue. In this case, the fuzzy logiccontroller is very useful. The application of a fuzzy logic based onadding a compensating current signal to the switched reluctancemotor to minimize the torque ripples is investigated. Its speed canbe controlled by various methods such as angle position control,phase current chopping control, fixed angle Pulse Width Modula-tion (PWM) control and variable angle PWM control. SRM drives,have been introduced for the past two decades, their applicationsare still limited. This is mainly due to its nonlinear electromagneticcharacteristic to control.

2 Equivalent electrical circuit

Voltage analysis canbeconducte donasingle phase of the switchedreluctancemotor,incorporating the dependence of inductanceon cur-rent and rotor position.

Fig.1:Single Phase Equivalent Circuit for Switched ReluctanceMotor

A single phase equivalent electrical circuit for a single phase of theswitched

Reluctance motor in corporating each of the sevoltage terms isshown in Figure1.The

single phase equivalent is representative of all phases of the mo-tor because each phase is

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Electrically independent of the others and all phases are verynearly identical in geometry,

Inductance,and resistance.

3 Mathematical Modeling Equations

4 SRM drive Block Diagram

Fig.2:.Block diagram of SRM with Controller

Because of the saliency of the stator and rotor,the torque ripple isproduced when the former phase is being excited opposite voltagewhen the latter phase has been excited. The point of intersection

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between the two excited phases must be advanced toa higher valueto minimize the torque ripple. Toattenuate the torque ripple, theaddition of acompensating current signal is proposed, as showninFigure 2. This signal is dependent of the rotorposition and the ref-erence current which in turndepends on the motor speed and thetorque load value. The output compensating current (Icomp) sig-nal produced by the controllers is added to the reference currentsignal, which ideally, should be constant in steady state, but pro-ducing significant ripple.The compensating signal should then be adjusted in order to pro-duce a ripple free out put torque.In this paper, intelligent controllersuch as fuzzylogic controller (FLC) is used to provide compensat-ing current Icompto minimize the torqueripples in SRM drives.The intelligent controller has two inputs, reference current (Iref),rotor position(θ) and one output, compensating current (Icomp),bymeans of a relation such as Icomp= f (θ, Iref).Consequently newreference current (Iref) isobtained by the addition of a phase current(Iph) and compensating current (Icomp) as shown in Figure.2.

5 Simulink model of SRM drive

Fig.3:Simulink model of SRM drive with FLC-PID control

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5.1 Fuzzy Logic Controller (FLC)

Fuzzy control is one of the appropriate control schemes for torquecontrol of SRM drives.The mamdani fuzzy controller uses the rotorpositionand reference current as input sand produces the compen-sating current as the output. The in put sare divided into member-ship functions which are designed to give an optimum number ofrules and allow the SRM to conduct over the entire positive torqueproducing region.Max-product rule of inference scheme is used andthe outputis determinedusing the center of average for defuzzifica-tion.

Fig.4:Fuzzy logic controller block

5.2 Implementation of Fuzzy Logic Controller

For this model, a DC supply voltage of 220 V is used. The con-verter turn-on and turn-off angles are kept constant at 40 deg and80deg, respectively, over the speed ranges. The reference currentis limited to 60 Amps and the hysteresis band is chosen as 10Amps. In FLC, reference current (Iref), rotor position (θ) are con-sidered as inputs and compensating current (Icomp) as output. Thefuzzy rules act on reference current (with seven memberfunctionsfor 50-70 Amps) and angular position (with seven member functionfor 40-80 Degrees) as inputs and compensating current (with sevenmember functions for +10 to -10 Amps) as output as shown be-low. Consequently, new reference current (Iref) is obtained by theaddition of the phase current (Ipha) and the compensating current(Icomp).

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Fig.5: Membership functions of reference current

Fig6: Membership functions of Rotor Position

Fig.7: Membership functions of Compensated Current

Linguistic Variables for Inputs: ES-ExtremelySmall; VS-Very Small;S-Small; M-Medium; H-High; VH-Very High; EH-Extremely High.Linguistic Variables for Output: Z-Zero; PS-Positive Small; PM-Positive Medium; PL-Positive Large; PB-Positive Big; PVB-PositiveVery Big; PVVB-Positive Very Very Big. The rule base developedfor the control of SRM drive is given in Table.1. In the regions of ES,VS and S of both inputs, ripples are more and for torque ripple min-imization, fuzzy rules PVB or PVVB are developed. However, inthe VH and EH regions, torque reduces by far slowly; consequently,fuzzy rules PB and PM have been determined. In addition, fuzzylogic rules for maximum compensation in near zero speeds up torated speed has been used. Even in higher speed, fuzzy logic rulesfor compensating current is limited to PB because high ripple inhigh current will damage the SRM.

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Table.1 Fuzzy Rules for SRM drive control.

6 Torque ripple

There are many factors to affect the torque ripple, such as rotor,stator shape, air length, commutation strategy, control strategy andso on, but the most important factor is phase current. It is definedas the amount of torque measured by subtracting the minimumtorque during one revolution from the maximum torque from thesame motor revolution.

7 Simulation results

Fig.8:Toque waveform without any control

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Fig.9:Toque waveform with PID controller

Fig.10: Toque waveform with FLC-PI controller

8 Simulation Output results

9 Conclusion

In this paper the performance of SRM drive without with PID, PI,FLC-PID, FLC-PI controllers.Fuzzy logic controller (FLC)current

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compensating techniques are employed for minimizing the torqueripples inswitched reluctance motor. The statistical parameters oftorque ripple are reported.Simulation results shows that FLC-PID,FLC-PI controllers give better performance than conventional con-trollers. FLC improves the dynamic performance of SRMdrives,due to its good learning andgeneralization capabilities.Without us-ing any controller, the Torque ripple is very high and is 77.69%.By using only PI controller Torque ripple is reduced to 62.64% ,byusing only PID controller Torque ripple is reduced to 60.37%, withFLC-PI controller Torque ripple is further reduced to 40.6% byusing FLC-PI controller the Torque ripple is further reduced to23.96%.

References

[1] Krishnan, R., 2001. Switched Reluctance Motors Drives,(Modeling, Simulation, Analysis, Design and Application),Florida: CRC Press LLC

[2] IqbalHusain Minimization of Torque Ripple in SRM DrivesIEEE Trans. Power Electron., vol. 49, pp. 8388, Feb 2002.

[3] T. J. E. Miller, Ed., Switched Reluctance Motors andtheir Control, Lebanon, OH:Magna Physics/Oxford UniversityPress (1993)

[4] M. Divandari and M.M. Kabir,Acoustic Noise Reduction ofSwitched Reluctance Motor Drives,

[5] M. Nagrial, J. Rizk and W. AljaismDynamic Simulation ofSwitched Reluctance Motor usingMatlab and Fuzzy Logic

[6] Suying Zhou, Hui Lin Modeling and Simulation of SwitchedReluctance Motor Double Closed Loop Control System.

[7] RameshKumar, Dhivya, Sundar, PI Controller Based Torqueand Speed Control of Five Phase Switched Reluctance Motor.

[8] F. Soares, P.J. Costa Branco, Simulation of a 6/4 switched re-luctance motor based on Matlab/Simulink environment, IEEE

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transaction on aerospace and electronic systems, vol. 37 ,no.3, pp.989-1009, July 2002.

[9] MATLAB, Users guide: fuzzy logic toolbox, The Math-worksInc; 2010.

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Torque ripple minimization of a Switched Reluctance Motor using … · 2018-11-26 · Torque ripple minimization of a Switched Reluctance Motor using Fuzzy logic control Current compensating