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Optimization of electric vehicle design problems using improved electric eel foraging optimization algorithm

  • Pranav Mehta

    Mr. Pranav Mehta is an Assistant Professor at the Department of Mechanical Engineering, Dharmsinh Desai University, Nadiad-387001, Gujarat, India. He is currently a Ph.D. research scholar with the Dharmsinh Desai University, Nadiad, Gujarat, India. His major research interests are metaheuristics techniques, multiobjective optimization, solar–thermal technologies, and renewable energy.

         , Betül Sultan Yildiz

    Dr. Betül Sultan Yildiz is an Associate professor in the Department of Mechanical Engineering at Bursa Uludağ University, Bursa, Turkey. Her research interests are mechanical design, structural optimization methods, and meta-heuristic optimization algorithms.

         , Sadiq M. Sait

    Dr. Sadiq M. Sait received his Bachelor’s degree in Electronics Engineering from Bangalore University, India, in 1981, and his Master’s and Ph.D. degrees in Electrical Engineering from the King Fahd University of Petroleum and Minerals (KFUPM), Dhahran, in 1983 and 1987, respectively. He is currently a Professor of Computer Engineering and Director of the Center for Communications and IT Research, KFUPM, Dhahran, Saudi Arabia.

         and Ali Riza Yıldız

    Dr. Ali Riza Yıldız is a Professor in the Department of Mechanical Engineering, Bursa Uludağ University, Bursa, Turkey. His research interests are the finite element analysis of structural components, lightweight design, vehicle design, vehicle crashworthiness, shape and topology optimization of vehicle components, meta-heuristic optimization techniques, and additive manufacturing.

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Published/Copyright: July 5, 2024
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Materials Testing
From the journal Materials Testing Volume 66 Issue 8

Abstract

This paper introduces a novel approach, the Modified Electric Eel Foraging Optimization (EELFO) algorithm, which integrates artificial neural networks (ANNs) with metaheuristic algorithms for solving multidisciplinary design problems efficiently. Inspired by the foraging behavior of electric eels, the algorithm incorporates four key phases: interactions, resting, hunting, and migrating. Mathematical formulations for each phase are provided, enabling the algorithm to explore and exploit solution spaces effectively. The algorithm’s performance is evaluated on various real-world optimization problems, including weight optimization of engineering components, economic optimization of pressure handling vessels, and cost optimization of welded beams. Comparative analyses demonstrate the superiority of the MEELFO algorithm in achieving optimal solutions with minimal deviations and computational effort compared to existing metaheuristic methods.

Keywords: electric vehicle component design; electric eel foraging optimization algorithm; optimization; artificial neural network; design
Corresponding author: Ali Riza Yıldız, Department of Mechanical Engineering, Bursa Uludag University, Görükle Bursa, 16059, Türkiye, E-mail:

About the authors

Pranav Mehta

Mr. Pranav Mehta is an Assistant Professor at the Department of Mechanical Engineering, Dharmsinh Desai University, Nadiad-387001, Gujarat, India. He is currently a Ph.D. research scholar with the Dharmsinh Desai University, Nadiad, Gujarat, India. His major research interests are metaheuristics techniques, multiobjective optimization, solar–thermal technologies, and renewable energy.

Betül Sultan Yildiz

Dr. Betül Sultan Yildiz is an Associate professor in the Department of Mechanical Engineering at Bursa Uludağ University, Bursa, Turkey. Her research interests are mechanical design, structural optimization methods, and meta-heuristic optimization algorithms.

Sadiq M. Sait

Dr. Sadiq M. Sait received his Bachelor’s degree in Electronics Engineering from Bangalore University, India, in 1981, and his Master’s and Ph.D. degrees in Electrical Engineering from the King Fahd University of Petroleum and Minerals (KFUPM), Dhahran, in 1983 and 1987, respectively. He is currently a Professor of Computer Engineering and Director of the Center for Communications and IT Research, KFUPM, Dhahran, Saudi Arabia.

Ali Riza Yıldız

Dr. Ali Riza Yıldız is a Professor in the Department of Mechanical Engineering, Bursa Uludağ University, Bursa, Turkey. His research interests are the finite element analysis of structural components, lightweight design, vehicle design, vehicle crashworthiness, shape and topology optimization of vehicle components, meta-heuristic optimization techniques, and additive manufacturing.

  1. Research ethics: Not applicable.

  2. Author contributions: The authors have accepted responsibility for the entire content of this manuscript and approved its submission.

  3. Competing interests: The authors state no conflict of interest.

  4. Research funding: None declared.

  5. Data availability: Not applicable.

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Published Online: 2024-07-05
Published in Print: 2024-08-27

© 2024 Walter de Gruyter GmbH, Berlin/Boston

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  1. Frontmatter
  2. An improved white shark optimizer algorithm used to optimize the structural parameters of the oil pad in the hydrostatic bearing
  3. Microstructure and oxidation of a Ni–Al based intermetallic coating formation on a Monel-400 alloy
  4. Friction, wear, and hardness properties of hybrid vehicle brake pads and effects on brake disc roughness
  5. Development of sinter linings for high-speed trains
  6. Wear resistance optimized by heat treatment of an in-situ TiC strengthened AlCoCrFeNi laser cladding coating
  7. Mechanical analysis of hybrid structured aircraft wing ribs with different geometric gaps
  8. Thermo-mechanical characteristics of spent coffee grounds reinforced bio-composites
  9. Compositional zoning and evolution of symplectite coronas in jadeitite
  10. Effect of niobium addition on the microstructure and wear properties of mechanical alloyed Cu–Al–Ni shape memory alloy
  11. Optimization of electric vehicle design problems using improved electric eel foraging optimization algorithm
  12. Effects of infill pattern and compression axis on the compressive strength of the 3D-printed cubic samples
  13. Microstructure and tribological properties of aluminum matrix composites reinforced with ZnO–hBN nanocomposite particles
  14. Marathon runner algorithm: theory and application in mathematical, mechanical and structural optimization problems
  15. Parameter identification of Yoshida–Uemori combined hardening model by using a variable step size firefly algorithm
  16. Identification of the tip mass parameters in a beam-tip mass system using response surface methodology
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https://doi.org/10.1515/mt-2024-0098
Keywords for this article
electric vehicle component design; electric eel foraging optimization algorithm; optimization; artificial neural network; design

Articles in the same Issue

  1. Frontmatter
  2. An improved white shark optimizer algorithm used to optimize the structural parameters of the oil pad in the hydrostatic bearing
  3. Microstructure and oxidation of a Ni–Al based intermetallic coating formation on a Monel-400 alloy
  4. Friction, wear, and hardness properties of hybrid vehicle brake pads and effects on brake disc roughness
  5. Development of sinter linings for high-speed trains
  6. Wear resistance optimized by heat treatment of an in-situ TiC strengthened AlCoCrFeNi laser cladding coating
  7. Mechanical analysis of hybrid structured aircraft wing ribs with different geometric gaps
  8. Thermo-mechanical characteristics of spent coffee grounds reinforced bio-composites
  9. Compositional zoning and evolution of symplectite coronas in jadeitite
  10. Effect of niobium addition on the microstructure and wear properties of mechanical alloyed Cu–Al–Ni shape memory alloy
  11. Optimization of electric vehicle design problems using improved electric eel foraging optimization algorithm
  12. Effects of infill pattern and compression axis on the compressive strength of the 3D-printed cubic samples
  13. Microstructure and tribological properties of aluminum matrix composites reinforced with ZnO–hBN nanocomposite particles
  14. Marathon runner algorithm: theory and application in mathematical, mechanical and structural optimization problems
  15. Parameter identification of Yoshida–Uemori combined hardening model by using a variable step size firefly algorithm
  16. Identification of the tip mass parameters in a beam-tip mass system using response surface methodology
  17. Production and characterization of waste walnut shell powder that can be used as a sustainable eco-friendly reinforcement in biocomposites
  18. Anticorrosion performance of a zinc-rich cycloaliphatic epoxy resin coating containing CeO2 nanoparticle
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