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Particle swarm optimization technique for speed control and torque ripple minimization of switched reluctance motor using PID and FOPID controllers

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Abstract

Switched Reluctance Motors has become one of the best solutions for EV applications because of its numerous benefits over other electric drive systems. Its excellent qualities are the robust design, double saliency, fault tolerance, and ability to withstand the heat of SRM drives. In order to minimize torque ripple and provide an exact speed response in SRM, this article mainly presents a speed and current control technique. The accurate speed control and torque ripple reduction of a SRM is controlled using the particle swarm optimization technique (PSO) with speed and current control mechanisms. The PID and FOPID speed controllers in the outer loop and current controller in the inner loop, respectively, are regulated, as are the 3-\(\varnothing\), 6/4 SRM turn-on (\({T}_{O}\)), and turn-off (\({T}_{F}\)), angles. The results were compared with existing optimization methods such as the SHO, LUS, GA, Ant-Lion, NSGA-II, MOLGSA, GSA, Hybrid MOLGSA, and RGA-SBX algorithms, show that a cascaded Fractional order PID(FOPID) controller offers better speed, current, and torque responses, as well as smaller current and torque ripples, under numerous different load and speed conditions. Under all load conditions, it has been demonstrated that the PSO-FOPID controller has the best speed response and minimal torque ripples when compared to the PSO-PID controller.

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Abbreviations

PSO:

Particle Swam optimization

ACO:

Ant Colony optimization

GSA:

Gravitational search algorithm

MOL:

Many optimizations Liaison

ALO:

Ant-Lion optimization

NSGA-II:

Non-dominated sorting genetic algorithm

RGA-SBX:

Real coded genetic algorithm simulated binary cross over

SHO:

Spotted hyena optimizer

LUS:

Local unimodal sampling

PID:

Proportional-integral derivative

FOPID:

Fractional order PID

GA:

Genetic algorithm

SRM:

Switched reluctance Motor

TSF:

Torque Sharing Function

DTC:

Direct Torque Control

ATC:

Average Torque Control

ISE Speed:

Integral squared error of speed

ISE Current:

Integral squared error of current

FF:

Fitness Function

T O :

Turn-on angle

T F :

Turn-off angle

μ :

Derivative order

λ :

Integral order

Kds, Kdi :

Derivative gains of Cascaded controller

K is, K ii :

Integral gains of cascaded controller

K ps, K pi :

Proportional gains of cascaded controller

R s :

Per phase resistance

λ :

Per phase flux linkage

V :

Per Phase Voltage

e :

Induced Electromotive force(emf)

K b :

Emf constant

L :

Inductance

P i :

Instantaneous input power

i s :

Instantaneous DC current

ω m :

Rotor speed (rad sec)

∅:

Rotor position (rad)

P a :

Air gap Power

P:

Differential operator

t :

Time

T e :

Electromagnetic Torque

e ω :

Speed error in per unit

ω refp .u :

Reference speed in per unit i.e., is 1 p.u

ω actp .u :

Actual speed in per unit

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Authors and Affiliations

  1. Electrical and Electronics Engineering Department, The National Institute of Engineering, Mysuru, Karnataka, 570008, India

    M. Naveen Kumar & R. Chidanandappa

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  1. M. Naveen Kumar
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Correspondence to M. Naveen Kumar.

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The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Appendix

Appendix

SRM Drive Parameters

Ratings

Power

60KW

Voltage

240Volts

stator pole arc

30Deg

rotor pole arc

32Deg

stack length

51 mm

stator diameter

82.1 mm

rotor diameter

40 mm

number of windings per pole

72 turns

stator resistance

0.05Ω

inertia

0.05 kg.m2

friction

0.02 N.m.s

No of rotor poles

4

No of stator poles

6

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Kumar, M.N., Chidanandappa, R. Particle swarm optimization technique for speed control and torque ripple minimization of switched reluctance motor using PID and FOPID controllers. Int. j. inf. tecnol. 16, 1185–1201 (2024). https://doi.org/10.1007/s41870-023-01656-2

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