Design optimization of PM couplings using hybrid Particle Swarm Optimization-Simplex Method (PSO-SM) Algorithm

•A PSO-SM optimization technique has been proposed to optimize the design of the PM coupling drive.•The coupling performance is predicted using a layer model approach that compared with FEA for validation.•The proposed PSO-SM technique is compared to other published techniques like PSO, and GA-SM.•T...

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Published inElectric power systems research Vol. 116; pp. 29 - 35
Main Author El-Wakeel, Amged S.
Format Journal Article
LanguageEnglish
Published Amsterdam Elsevier B.V 01.11.2014
Elsevier
Subjects
Online AccessGet full text
ISSN0378-7796
1873-2046
DOI10.1016/j.epsr.2014.05.003

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Abstract •A PSO-SM optimization technique has been proposed to optimize the design of the PM coupling drive.•The coupling performance is predicted using a layer model approach that compared with FEA for validation.•The proposed PSO-SM technique is compared to other published techniques like PSO, and GA-SM.•The simulation showed that the proposed algorithm (PSO-SM) is the most efficient one. The aim of this paper is to explore the use of the proposed hybrid Particle Swarm Optimization-Simplex Method (PSO-SM) algorithm to optimize the design of PM couplings subject to several key design constraints. The proposed hybrid optimization algorithm is constructed based on combining two well-known optimization techniques: Particle Swarm Optimization (PSO) and Simplex Method (SM). The PSO has obvious capabilities in global search while the SM has exceptional advantages in local search. As a hybrid algorithm, the PSO-SM has the outstanding feature of combining the ability of global searching and local canvassing. On the other hand, Permanent Magnet (PM) drive couplings are used in power transmission in a wide range of industrial applications. A standard coupling design is used as a good starting point for the conventional Simplex Method and to define the performance constraints for the proposed hybrid optimization algorithm. New coupling designs are developed and optimized to demonstrate the superior capabilities of PSO-SM algorithm as a global optimization technique.
AbstractList •A PSO-SM optimization technique has been proposed to optimize the design of the PM coupling drive.•The coupling performance is predicted using a layer model approach that compared with FEA for validation.•The proposed PSO-SM technique is compared to other published techniques like PSO, and GA-SM.•The simulation showed that the proposed algorithm (PSO-SM) is the most efficient one. The aim of this paper is to explore the use of the proposed hybrid Particle Swarm Optimization-Simplex Method (PSO-SM) algorithm to optimize the design of PM couplings subject to several key design constraints. The proposed hybrid optimization algorithm is constructed based on combining two well-known optimization techniques: Particle Swarm Optimization (PSO) and Simplex Method (SM). The PSO has obvious capabilities in global search while the SM has exceptional advantages in local search. As a hybrid algorithm, the PSO-SM has the outstanding feature of combining the ability of global searching and local canvassing. On the other hand, Permanent Magnet (PM) drive couplings are used in power transmission in a wide range of industrial applications. A standard coupling design is used as a good starting point for the conventional Simplex Method and to define the performance constraints for the proposed hybrid optimization algorithm. New coupling designs are developed and optimized to demonstrate the superior capabilities of PSO-SM algorithm as a global optimization technique.
Author El-Wakeel, Amged S.
Author_xml – sequence: 1
  givenname: Amged S.
  surname: El-Wakeel
  fullname: El-Wakeel, Amged S.
  email: A.S.El-Wakeel@ieee.org, dramgedelwakeel@gmail.com
  organization: Department of Electric Power and Energy, MTC, Cairo, Egypt
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Cites_doi 10.3923/ijscomp.2012.58.62
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Keywords Simplex Method
Hybrid optimization Techniques
Particle Swarm Optimization
Permanent Magnet Drive Coupling
Performance evaluation
Motor drives
Industrial application
Power transmission
Global optimum
Algorithm
Particle swarm optimization
Standards
Magnetic coupling
Simplex method
Starting
Permanent magnet machine
Permanent magnet
Language English
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References Haibing Hu, Lu, Xu (bib0040) 2005
Wang, Wang, Wu, Shi (bib0055) 2011
El-Wakeel (bib0060) 2004
Wallace, Jouanne, Smith (bib0120) 2001
Smith, Williamson, Benhama, Counter, Papadopoulos (bib0125) 1999
Smith, El-Wakeel, Wallace (bib0015) 2002
Chen (bib0070) 2007
Belsam, Ananth, RaviChandran (bib0080) 2012; 7
Zhang, Wan, Li, Feng (bib0130) 2013
El-Wakeel, Smith (bib0010) 2002
El-Wakeel, Smith (bib0020) 2002
Kennedy, Eberhart (bib0045) 1995
Ertan, Tohumcu (bib0005) 1988
Ghaffar, El-Wakeel, Eliwa, Mostafa (bib0075) 2011; 14
Neittaanmaki, Rudnicki, Savini (bib0085) 1996
Gaing (bib0035) 2004; 19
Eberhart, Shi (bib0065) 1998; 144
El-Telbany (bib0025) 2007; 7
El-Wakeel, Hassan, Kamel, Abdel-Hamed (bib0030) 2013; 4
Xiangdong Qian, Su, Chen (bib0100) 2012
Anna Wang, Shi, Zhao (bib0115) 2011
El-Wakeel (bib0105) 2003
Ru, Jian-hua, Shuai-qi (bib0095) 2010
Shi, Eberhart (bib0050) 1998
Ramamoorty (bib0090) 1988
(bib0110) 1997
Neittaanmaki (10.1016/j.epsr.2014.05.003_bib0085) 1996
Chen (10.1016/j.epsr.2014.05.003_bib0070) 2007
Eberhart (10.1016/j.epsr.2014.05.003_bib0065) 1998; 144
Gaing (10.1016/j.epsr.2014.05.003_bib0035) 2004; 19
Ertan (10.1016/j.epsr.2014.05.003_bib0005) 1988
Ghaffar (10.1016/j.epsr.2014.05.003_bib0075) 2011; 14
Shi (10.1016/j.epsr.2014.05.003_bib0050) 1998
Kennedy (10.1016/j.epsr.2014.05.003_bib0045) 1995
Ru (10.1016/j.epsr.2014.05.003_bib0095) 2010
El-Wakeel (10.1016/j.epsr.2014.05.003_bib0060) 2004
El-Wakeel (10.1016/j.epsr.2014.05.003_bib0105) 2003
Smith (10.1016/j.epsr.2014.05.003_bib0015) 2002
El-Wakeel (10.1016/j.epsr.2014.05.003_bib0020) 2002
Xiangdong Qian (10.1016/j.epsr.2014.05.003_bib0100) 2012
El-Wakeel (10.1016/j.epsr.2014.05.003_bib0010) 2002
Smith (10.1016/j.epsr.2014.05.003_bib0125) 1999
El-Telbany (10.1016/j.epsr.2014.05.003_bib0025) 2007; 7
El-Wakeel (10.1016/j.epsr.2014.05.003_bib0030) 2013; 4
Wang (10.1016/j.epsr.2014.05.003_bib0055) 2011
Belsam (10.1016/j.epsr.2014.05.003_bib0080) 2012; 7
Haibing Hu (10.1016/j.epsr.2014.05.003_bib0040) 2005
Zhang (10.1016/j.epsr.2014.05.003_bib0130) 2013
(10.1016/j.epsr.2014.05.003_bib0110) 1997
Wallace (10.1016/j.epsr.2014.05.003_bib0120) 2001
Ramamoorty (10.1016/j.epsr.2014.05.003_bib0090) 1988
Anna Wang (10.1016/j.epsr.2014.05.003_bib0115) 2011
References_xml – year: 2005
  ident: bib0040
  article-title: Optimal PID controller design in PMSM servo system via particle swarm optimization
  publication-title: Presented at the Annual conference of IEEE on Industrial Electronic Society, 6–10 November
– year: 2012
  ident: bib0100
  article-title: A hybrid particle swarm optimization (PSO)-simplex algorithm for damage identification of delaminated beams
  publication-title: Math. Probl. Eng.
– year: 1997
  ident: bib0110
  article-title: The Future of power Transmission is Here!-Rex MagnetLink Coupling
– year: 1996
  ident: bib0085
  article-title: Inverse Problems and Optimal Design in Electricity and Magnetism
– volume: 14
  year: 2011
  ident: bib0075
  article-title: Optimal position Control of permanent magnet DC motor (PMDC)
  publication-title: Proc. ASAT
– volume: 7
  year: 2007
  ident: bib0025
  article-title: Employing particle swarm optimizer and genetic algorithms for optimal tuning of PID controllers: a comparative study
  publication-title: ICGST-ACSE J.
– year: 2010
  ident: bib0095
  article-title: Hybrid particle swarm optimization-simplex algorithm for inverse problem
  publication-title: Presented at the Control and Decision Conference (CCDC), IEEE
– volume: 19
  year: 2004
  ident: bib0035
  article-title: A particle swarm optimization approach for optimum design of PID controller in AVR system
  publication-title: IEEE Trans. Energy Convers.
– year: 2002
  ident: bib0015
  article-title: Formal design optimization of PM drive couplings
  publication-title: IEEE Conference Record of the Industry Applications Conference, 37th IAS Annual Meeting
– year: 2011
  ident: bib0115
  article-title: Study on nonlinear regression modeling methods of the permanent magnet drive
  publication-title: Presented at the International Conference on Electronics and Optoelectronics (ICEOE 2011)
– year: 2001
  ident: bib0120
  article-title: Performance prediction and test of adjustable permanent-magnet load transmission systems
  publication-title: IEEE-IAS Annual Meeting, October
– year: 2007
  ident: bib0070
  article-title: Particle swarm optimization for PID controllers with robust testing
  publication-title: Presented at the International Conference on Machine Learning and Cybernetics, 19–22 August
– year: 2004
  ident: bib0060
  article-title: Design optimization of electric machines
  publication-title: Presented at the Proceedings of ICEENG‘04, the 4th International Conference on Electrical Engineering
– year: 2003
  ident: bib0105
  article-title: Design optimisation for fault tolerant switched reluctance motors
– start-page: 69
  year: 1998
  end-page: 73
  ident: bib0050
  article-title: A Modified Particle Swarm Optimizer
  publication-title: IEEE int. Conf. Evolutionary Computation
– volume: 144
  start-page: 611
  year: 1998
  end-page: 616
  ident: bib0065
  article-title: Comparison between genetic algorithms and particle swarm optimization
  publication-title: Evolutionary Programming VII
– year: 2002
  ident: bib0020
  article-title: Genetic design of a switched reluctance motor based on minimum outer volume
  publication-title: Proceedings of ICEENG 2002, the 3rd International Conference on Electrical Engineering, Cairo, Egypt, 14–16 May
– volume: 4
  start-page: 53
  year: 2013
  end-page: 64
  ident: bib0030
  article-title: Optimum tuning of pid controller for a permanent magnet brushless DC motor
  publication-title: Int. J. Electr. Eng. Technol. (IJEET)
– year: 2013
  ident: bib0130
  article-title: Optimized design research on adjustable-speed permanent magnet coupling
  publication-title: Presented at the IEEE International Conference on Industrial Technology (ICIT)
– year: 1995
  ident: bib0045
  article-title: Particle swarm optimization
  publication-title: Presented at the IEEE International Conf. in Neural Networks
– year: 1988
  ident: bib0005
  article-title: A method for optimum design of switched reluctance machines
  publication-title: Proceedings of ICEM’88, International Conference on Electrical Machines, Pisa, Italy, 12–14 September
– year: 2011
  ident: bib0055
  article-title: Structural optimization of the permanent magnet drive based on artificial neural network and particle swarm optimization
  publication-title: Presented at the Third International Conference on Intelligent Human-Machine Systems and Cybernetics, IEEE
– year: 1999
  ident: bib0125
  article-title: Magnetic drive couplings
  publication-title: Presented at the Ninth international Conference on Electrical Machines and Drives, Conference Publication No. 468, 0 IEE
– year: 1988
  ident: bib0090
  article-title: Computer-Aided Design of Electrical Equipment
– volume: 7
  start-page: 58
  year: 2012
  end-page: 62
  ident: bib0080
  article-title: Soft computing based design of PID controller for a linear brushless DC
  publication-title: Motor Int. J. Soft Comput.
– year: 2002
  ident: bib0010
  article-title: Optimal design of switched reluctance motors using genetic algorithms
  publication-title: Proceedings of ICEM 2002, International Conference on Electrical Machines, Bruges, Belgium, 26–28 August
– year: 2013
  ident: 10.1016/j.epsr.2014.05.003_bib0130
  article-title: Optimized design research on adjustable-speed permanent magnet coupling
– year: 1997
  ident: 10.1016/j.epsr.2014.05.003_bib0110
– year: 2005
  ident: 10.1016/j.epsr.2014.05.003_bib0040
  article-title: Optimal PID controller design in PMSM servo system via particle swarm optimization
– year: 2004
  ident: 10.1016/j.epsr.2014.05.003_bib0060
  article-title: Design optimization of electric machines
– year: 2007
  ident: 10.1016/j.epsr.2014.05.003_bib0070
  article-title: Particle swarm optimization for PID controllers with robust testing
– volume: 7
  start-page: 58
  year: 2012
  ident: 10.1016/j.epsr.2014.05.003_bib0080
  article-title: Soft computing based design of PID controller for a linear brushless DC
  publication-title: Motor Int. J. Soft Comput.
  doi: 10.3923/ijscomp.2012.58.62
– year: 2011
  ident: 10.1016/j.epsr.2014.05.003_bib0055
  article-title: Structural optimization of the permanent magnet drive based on artificial neural network and particle swarm optimization
– year: 2010
  ident: 10.1016/j.epsr.2014.05.003_bib0095
  article-title: Hybrid particle swarm optimization-simplex algorithm for inverse problem
– year: 1996
  ident: 10.1016/j.epsr.2014.05.003_bib0085
– year: 1999
  ident: 10.1016/j.epsr.2014.05.003_bib0125
  article-title: Magnetic drive couplings
– volume: 4
  start-page: 53
  year: 2013
  ident: 10.1016/j.epsr.2014.05.003_bib0030
  article-title: Optimum tuning of pid controller for a permanent magnet brushless DC motor
  publication-title: Int. J. Electr. Eng. Technol. (IJEET)
– volume: 14
  year: 2011
  ident: 10.1016/j.epsr.2014.05.003_bib0075
  article-title: Optimal position Control of permanent magnet DC motor (PMDC)
  publication-title: Proc. ASAT
– volume: 144
  start-page: 611
  year: 1998
  ident: 10.1016/j.epsr.2014.05.003_bib0065
  article-title: Comparison between genetic algorithms and particle swarm optimization
– year: 2001
  ident: 10.1016/j.epsr.2014.05.003_bib0120
  article-title: Performance prediction and test of adjustable permanent-magnet load transmission systems
– year: 2012
  ident: 10.1016/j.epsr.2014.05.003_bib0100
  article-title: A hybrid particle swarm optimization (PSO)-simplex algorithm for damage identification of delaminated beams
  publication-title: Math. Probl. Eng.
– year: 2002
  ident: 10.1016/j.epsr.2014.05.003_bib0010
  article-title: Optimal design of switched reluctance motors using genetic algorithms
– year: 2003
  ident: 10.1016/j.epsr.2014.05.003_bib0105
– year: 2011
  ident: 10.1016/j.epsr.2014.05.003_bib0115
  article-title: Study on nonlinear regression modeling methods of the permanent magnet drive
– year: 1988
  ident: 10.1016/j.epsr.2014.05.003_bib0005
  article-title: A method for optimum design of switched reluctance machines
– year: 2002
  ident: 10.1016/j.epsr.2014.05.003_bib0015
  article-title: Formal design optimization of PM drive couplings
– year: 1995
  ident: 10.1016/j.epsr.2014.05.003_bib0045
  article-title: Particle swarm optimization
– start-page: 69
  year: 1998
  ident: 10.1016/j.epsr.2014.05.003_bib0050
  article-title: A Modified Particle Swarm Optimizer
– volume: 7
  issue: November
  year: 2007
  ident: 10.1016/j.epsr.2014.05.003_bib0025
  article-title: Employing particle swarm optimizer and genetic algorithms for optimal tuning of PID controllers: a comparative study
  publication-title: ICGST-ACSE J.
– year: 1988
  ident: 10.1016/j.epsr.2014.05.003_bib0090
– volume: 19
  issue: June (2)
  year: 2004
  ident: 10.1016/j.epsr.2014.05.003_bib0035
  article-title: A particle swarm optimization approach for optimum design of PID controller in AVR system
  publication-title: IEEE Trans. Energy Convers.
– year: 2002
  ident: 10.1016/j.epsr.2014.05.003_bib0020
  article-title: Genetic design of a switched reluctance motor based on minimum outer volume
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Snippet •A PSO-SM optimization technique has been proposed to optimize the design of the PM coupling drive.•The coupling performance is predicted using a layer model...
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elsevier
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StartPage 29
SubjectTerms Applied sciences
Electrical engineering. Electrical power engineering
Electrical machines
Exact sciences and technology
Hybrid optimization Techniques
Miscellaneous
Particle Swarm Optimization
Permanent Magnet Drive Coupling
Regulation and control
Simplex Method
Title Design optimization of PM couplings using hybrid Particle Swarm Optimization-Simplex Method (PSO-SM) Algorithm
URI https://dx.doi.org/10.1016/j.epsr.2014.05.003
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