IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v14y2020i1p115-d469507.html
   My bibliography  Save this article

Application of Genetic Algorithm Elements to Modelling of Rotation Processes in Motion Transmission Including a Long Shaft

Author

Listed:
  • Andriy Chaban

    (Faculty of Transport, Electrical Engineering and Computer Science, Kazimierz Pulaski University of Technology and Humanities, Malczewskiego 29, 26-600 Radom, Poland)

  • Marek Lis

    (Faculty of Electrical Engineering, Czestochowa University of Technology, Al. Armii Krajowej 17, 42-201 Czestochowa, Poland)

  • Andrzej Szafraniec

    (Faculty of Transport, Electrical Engineering and Computer Science, Kazimierz Pulaski University of Technology and Humanities, Malczewskiego 29, 26-600 Radom, Poland)

  • Radoslaw Jedynak

    (Faculty of Transport, Electrical Engineering and Computer Science, Kazimierz Pulaski University of Technology and Humanities, Malczewskiego 29, 26-600 Radom, Poland)

Abstract

Genetic algorithms are used to parameter identification of the model of oscillatory processes in complicated motion transmission of electric drives containing long elastic shafts as systems of distributed mechanical parameters. Shaft equations are generated on the basis of a modified Hamilton–Ostrogradski principle, which serves as the foundation to analyse the lumped parameter system and distributed parameter system. They serve to compute basic functions of analytical mechanics of velocity continuum and rotational angles of shaft elements. It is demonstrated that the application of the distributed parameter method to multi-mass rotational systems, that contain long elastic elements and complicated control systems, is not always possible. The genetic algorithm is applied to determine the coefficients of approximation the system of Rotational Transmission with Elastic Shaft by equivalent differential equations. The fitness function is determined as least-square error. The obtained results confirm that application of the genetic algorithms allow one to replace the use of a complicated distributed parameter model of mechanical system by a considerably simpler model, and to eliminate sophisticated calculation procedures and identification of boundary conditions for wave motion equations of long elastic elements.

Suggested Citation

  • Andriy Chaban & Marek Lis & Andrzej Szafraniec & Radoslaw Jedynak, 2020. "Application of Genetic Algorithm Elements to Modelling of Rotation Processes in Motion Transmission Including a Long Shaft," Energies, MDPI, vol. 14(1), pages 1-17, December.
  • Handle: RePEc:gam:jeners:v:14:y:2020:i:1:p:115-:d:469507
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/14/1/115/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/14/1/115/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Chwastek, Krzysztof & Szczyglowski, Jan, 2006. "Identification of a hysteresis model parameters with genetic algorithms," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 71(3), pages 206-211.
    2. Wei Chen & Jiaojiao Liang & Tingna Shi, 2018. "Speed Synchronous Control of Multiple Permanent Magnet Synchronous Motors Based on an Improved Cross-Coupling Structure," Energies, MDPI, vol. 11(2), pages 1-16, January.
    3. Kanaan, Hadi Youssef & Al-Haddad, Kamal & Roy, Gilles, 2003. "Analysis of the electromechanical vibrations in induction motor drives due to the imperfections of the mechanical transmission system," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 63(3), pages 421-433.
    4. Gang Lei & Jianguo Zhu & Youguang Guo & Chengcheng Liu & Bo Ma, 2017. "A Review of Design Optimization Methods for Electrical Machines," Energies, MDPI, vol. 10(12), pages 1-31, November.
    5. Xianglin Li & K. T. Chau & Yubin Wang, 2016. "Modeling of a Field-Modulated Permanent-Magnet Machine," Energies, MDPI, vol. 9(12), pages 1-15, December.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Jacek Kabziński & Przemysław Mosiołek, 2021. "Integrated, Multi-Approach, Adaptive Control of Two-Mass Drive with Nonlinear Damping and Stiffness," Energies, MDPI, vol. 14(17), pages 1-23, September.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Andriy Chaban & Zbigniew Łukasik & Andrzej Popenda & Andrzej Szafraniec, 2021. "Mathematical Modelling of Transient Processes in an Asynchronous Drive with a Long Shaft Including Cardan Joints," Energies, MDPI, vol. 14(18), pages 1-17, September.
    2. Nicolas Bernard & Linh Dang & Luc Moreau & Salvy Bourguet, 2022. "A Pre-Sizing Method for Salient Pole Synchronous Reluctance Machines with Loss Minimization Control for a Small Urban Electrical Vehicle Considering the Driving Cycle," Energies, MDPI, vol. 15(23), pages 1-19, December.
    3. Liqin Wu & Hao Chen & Tingyue Yu & Chengzhi Sun & Lin Wang & Xuerong Ye & Guofu Zhai, 2023. "Robust Design Optimization of the Cogging Torque for a PMSM Based on Manufacturing Uncertainties Analysis and Approximate Modeling," Energies, MDPI, vol. 16(2), pages 1-24, January.
    4. Sebastian Berhausen & Tomasz Jarek, 2021. "Method of Limiting Shaft Voltages in AC Electric Machines," Energies, MDPI, vol. 14(11), pages 1-19, June.
    5. Chengcheng Liu & Jiawei Lu & Youhua Wang & Gang Lei & Jianguo Zhu & Youguang Guo, 2018. "Design Issues for Claw Pole Machines with Soft Magnetic Composite Cores," Energies, MDPI, vol. 11(8), pages 1-15, August.
    6. Yan Xu & Tingna Shi & Yan Yan & Xin Gu, 2019. "Dual-Vector Predictive Torque Control of Permanent Magnet Synchronous Motors Based on a Candidate Vector Table," Energies, MDPI, vol. 12(1), pages 1-15, January.
    7. Md Sydur Rahman & Grace Firsta Lukman & Pham Trung Hieu & Kwang-Il Jeong & Jin-Woo Ahn, 2021. "Optimization and Characteristics Analysis of High Torque Density 12/8 Switched Reluctance Motor Using Metaheuristic Gray Wolf Optimization Algorithm," Energies, MDPI, vol. 14(7), pages 1-17, April.
    8. Haipeng Liu & Xin Jin & Nicola Bianchi & Gerd Bramerdorfer & Pengzhong Hu & Chengning Zhang & Yongxi Yang, 2022. "A Permanent Magnet Assembling Approach to Mitigate the Cogging Torque for Permanent Magnet Machines Considering Manufacturing Uncertainties," Energies, MDPI, vol. 15(6), pages 1-19, March.
    9. João F. P. Fernandes & Pedro P. C. Bhagubai & Paulo J. C. Branco, 2022. "Recent Developments in Electrical Machine Design for the Electrification of Industrial and Transportation Systems," Energies, MDPI, vol. 15(17), pages 1-13, September.
    10. Yujun Shi & Linni Jian, 2018. "A Novel Dual-Permanent-Magnet-Excited Machine with Flux Strengthening Effect for Low-Speed Large-Torque Applications," Energies, MDPI, vol. 11(1), pages 1-17, January.
    11. Carosi, Daniele & Zama, Fabiana & Morri, Alessandro & Ceschini, Lorella, 2024. "Linearising anhysteretic magnetisation curves: A novel algorithm for finding simulation parameters and magnetic moments," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 221(C), pages 210-221.
    12. Henda Zorgani Agrebi & Naourez Benhadj & Mohamed Chaieb & Farooq Sher & Roua Amami & Rafik Neji & Neil Mansfield, 2021. "Integrated Optimal Design of Permanent Magnet Synchronous Generator for Smart Wind Turbine Using Genetic Algorithm," Energies, MDPI, vol. 14(15), pages 1-20, July.
    13. Sajjad Ahmadi & Thierry Lubin & Abolfazl Vahedi & Nasser Taghavi, 2021. "Sensitivity-Based Optimization of Interior Permanent Magnet Synchronous Motor for Torque Characteristic Enhancement," Energies, MDPI, vol. 14(8), pages 1-15, April.
    14. Xueping Xu & Qinkai Han & Fulei Chu, 2018. "Review of Electromagnetic Vibration in Electrical Machines," Energies, MDPI, vol. 11(7), pages 1-33, July.
    15. Edison Gundabattini & Arkadiusz Mystkowski & Adam Idzkowski & Raja Singh R. & Darius Gnanaraj Solomon, 2021. "Thermal Mapping of a High-Speed Electric Motor Used for Traction Applications and Analysis of Various Cooling Methods—A Review," Energies, MDPI, vol. 14(5), pages 1-32, March.
    16. Chengcheng Liu & Gang Lei & Bo Ma & Youguang Guo & Jianguo Zhu, 2018. "Robust Design of a Low-Cost Permanent Magnet Motor with Soft Magnetic Composite Cores Considering the Manufacturing Process and Tolerances," Energies, MDPI, vol. 11(8), pages 1-17, August.
    17. Yichang Zhong & Shoudao Huang & Derong Luo, 2018. "Stabilization and Speed Control of a Permanent Magnet Synchronous Motor with Dual-Rotating Rotors," Energies, MDPI, vol. 11(10), pages 1-15, October.
    18. Wei Chen & Jiaojiao Liang & Tingna Shi, 2018. "Speed Synchronous Control of Multiple Permanent Magnet Synchronous Motors Based on an Improved Cross-Coupling Structure," Energies, MDPI, vol. 11(2), pages 1-16, January.
    19. Niklas Umland & Kora Winkler & David Inkermann, 2023. "Multidisciplinary Design Automation of Electric Motors—Systematic Literature Review and Methodological Framework," Energies, MDPI, vol. 16(20), pages 1-39, October.
    20. Noman Ullah & Abdul Basit & Faisal Khan & Wasiq Ullah & Mohsin Shahzad & Atif Zahid, 2018. "Enhancing Capabilities of Double Sided Linear Flux Switching Permanent Magnet Machines," Energies, MDPI, vol. 11(10), pages 1-21, October.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:14:y:2020:i:1:p:115-:d:469507. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.