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Design optimization of ferrite assisted synchronous reluctance motor using multi-objective differential evolution algorithm

Nagarajan V.S. (Department of Electrical and Electronics Engineering, SSN College of Engineering, Chennai, India)
Balaji Mahadevan (Department of Electrical and Electronics Engineering, SSN College of Engineering, Chennai, India)
Kamaraj V. (Department of Electrical and Electronics Engineering, SSN College of Engineering, Chennai, India)
Arumugam R. (Department of Electrical and Electronics Engineering, SSN College of Engineering, Chennai, India)
Ganesh Nagarajan (Renault-Nissan Technology and Business Centre India Private Ltd, Chennai, India)
Srivignesh S. (Department of Electrical and Electronics Engineering, SSN College of Engineering, Chennai, India)
Suudharshana M. (Department of Electrical and Electronics Engineering, SSN College of Engineering, Chennai, India)

COMPEL - The international journal for computation and mathematics in electrical and electronic engineering

ISSN: 0332-1649

Publication date: 3 January 2017

Abstract

Purpose

The purpose of this paper is performance enhancement of ferrite-assisted synchronous reluctance (FASR) motor using multi-objective differential evolution (MODE) algorithm, considering the significant geometric design parameters.

Design/methodology/approach

This work illustrates the optimization of FASR motor using MODE algorithm to enhance the performance of the motor considering barrier angular positions, magnet height, magnet axial length, flux barrier angles of the rotor and air gap length. In the optimization routine to determine the performance parameters, generalized regression neural network-based interpolation is used. The results of MODE are validated with multi-objective particle swarm optimization algorithm and multi-objective genetic algorithm.

Findings

The design optimization procedure developed in this work for FASR motor aims at achieving multiple objectives, namely, average torque, torque ripple and efficiency. With multiple objectives, it is essential to give the designer the tradeoff between different objectives so as to arrive at the best design suitable for the application. The results obtained in this work justify the application of the MODE approach for FASR motor to determine the various feasible solutions within the bounds of the design.

Research limitations/implications

Analysis, design and optimization of synchronous reluctance motor has been explored in detail to establish its potential for variable speed applications. In recent years, the focus is toward the electromagnetic design of hybrid configurations such as FASR motor. It is in this preview this work aims to achieve optimal design of FASR motor using multi-objective optimization approach.

Practical/implications

The results of this work will supplement and encourage the application of FASR motor as a viable alternate for variable speed drive applications. In addition, the application of MODE to arrive at better design solutions is demonstrated.

Originality/value

The approach presented in this work focuses on obtaining enhanced design of FASR motor considering average torque, torque ripple and efficiency as performance measures. The posteriori analysis of optimization provides an insight into the choice of parameters involved and their effects on the design of FASR motor. The efficacy of the optimization routine is justified in comparison with other multi-objective algorithms.

Keywords

  • FEA
  • FASR motor
  • GRNN
  • MODE
  • Multi-objective design optimization

Acknowledgements

This research was supported and funded by Department of Science and Technology, Government of India, and SSN Trust.

Citation

V.S., N., Mahadevan, B., V., K., R., A., Nagarajan, G., S., S. and M., S. (2017), "Design optimization of ferrite assisted synchronous reluctance motor using multi-objective differential evolution algorithm", COMPEL - The international journal for computation and mathematics in electrical and electronic engineering, Vol. 36 No. 1, pp. 219-239. https://doi.org/10.1108/COMPEL-06-2016-0253

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Emerald Publishing Limited

Copyright © 2017, Emerald Publishing Limited

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