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Genetic Algorithm-based Multi-objective Design Optimization of Radial Flux PMBLDC Motor

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Artificial Intelligence and Evolutionary Computations in Engineering Systems

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 668))

Abstract

Genetic algorithm (GA)-based multi-objective optimal design procedure of radial flux permanent magnet brushless DC (PMBLDC) motor is presented in this paper. Three objective functions are considered, i.e., efficiency, weight, and combination of both. The first two fitness functions are single-objective, and the third one is multi-objective. Multi-objective function is combinational function which incorporates both efficiency and weight of the motor into single fitness function. Design of motor is optimized using these three functions separately. Average flux density (B g), torque to rotor volume ratio (K trv), air gap length (l g), motor aspect ratio (A r), and motor split ratio (S r) are design variables to optimize. To validate optimized design obtained from the algorithm, finite element analysis is carried out.

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References

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Author information

Authors and Affiliations

  1. Institute of Technology, Nirma University, Ahmedabad, India

    Amit N. Patel

  2. Government Engineering College, Bhuj, India

    Bhavik N. Suthar

Authors
  1. Amit N. Patel
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  2. Bhavik N. Suthar
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Corresponding author

Correspondence to Amit N. Patel .

Editor information

Editors and Affiliations

  1. Electrical and Electronics Engineering, SRM Engineering College, Kattankulathur, Tamil Nadu, India

    Subhransu Sekhar Dash

  2. Department of Electrical and Electronics Engineering, Madanapalle Institute of Technology and Science, Madanapalle, Andhra Pradesh, India

    Paruchuri Chandra Babu Naidu

  3. Department of Electrical and Electronics Engineering, Gazi University, Ankara, Turkey

    Ramazan Bayindir

  4. Indian Statistical Institute, Kolkata, India

    Swagatam Das

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Patel, A.N., Suthar, B.N. (2018). Genetic Algorithm-based Multi-objective Design Optimization of Radial Flux PMBLDC Motor. In: Dash, S., Naidu, P., Bayindir, R., Das, S. (eds) Artificial Intelligence and Evolutionary Computations in Engineering Systems. Advances in Intelligent Systems and Computing, vol 668. Springer, Singapore. https://doi.org/10.1007/978-981-10-7868-2_53

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  • DOI: https://doi.org/10.1007/978-981-10-7868-2_53

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-7867-5

  • Online ISBN: 978-981-10-7868-2

  • eBook Packages: EngineeringEngineering (R0)

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