Research Article
BibTex RIS Cite

Çok Amaçlı Genetik Algoritma Yöntemi Kullanılarak Enine Laminasyonlu Senkron Relüktans Motor Optimizasyonu

Year 2022, Volume: 12 Issue: 2, 841 - 852, 15.12.2022
https://doi.org/10.31466/kfbd.1169294

Abstract

Senkron relüktans motor (SynRM), asenkron motor ile aynı gövde yapısına sahip olmasına rağmen rotor yapıları farklıdır. Rotorunda sargı, bakır veya alüminyum çubuklar bulundurmadığından rotor kayıpları azalmakta ve verimleri artmaktadır. Ancak SynRM’nin tork dalgalanması önemli bir problemdir ve motor performansını düşürmeden tork dalgalanmasının azaltılması elzemdir. Bu amaç doğrultusunda çalışmada, 4 KW gücündeki senkron relüktans motor dikkate alınmıştır. Motora ait tüm elektriksel ve mekaniksel veriler Ansys Maxwell programında tanımlanarak motorun analizi gerçekleştirilmiştir. Çok amaçlı genetik algoritma (MOGA) yöntemi kullanılarak motor performansı artışı için tanımlanan amaç fonksiyonları doğrultusunda optimizasyon çalışmaları gerçekleştirilmiştir. Rotor boyutlandırma parametreleri giriş değişkenleri, çıkış büyüklükleri ise çıkış gücü, verim, tork, tork dalgalanması, çıkıntı oranı olarak tanımlanmıştır. Bariyer sayısı sırasıyla 3, 4 ve 5 için beş amaç fonksiyonu MOGA ile sınanmıştır. Ele alınan amaç fonksiyonlarından elde edilen sonuçlar referans motor verileri ile karşılaştırılmıştır. Amaç fonksiyonu 1’in dışında diğer amaç fonksiyonları referans motorun verim, çıkış gücü, tork dalgalanması bakımından karşılayamamaktadır. 4 bariyerli amaç fonksiyonu 1’den elde edilen verimde değişim gözlenmezken çıkış gücünde % 0,31 artış, tork dalgalanmasında %31,71 azalma görülmüştür.

References

  • Arslan, S. (2016). Dalgıç Motorun Analitik, Sayısal, Performans Sonuçlarının Karşılaştırılması. Düzce Üniversitesi Bilim ve Teknoloji Dergisi, 4(2), 403-415.
  • Arslan Serdal, Akkaya Oy Sibel, Tören Murat (2016). Amorphous Nüveli Dalgıç Motorun ve Üç Fazlı Amorf Nüveli Transformatörün Demir Kayıplarının Sonlu Elemanlar Yöntemi ile İncelenmesi. 1. International Academıc Research Congress
  • Arslan, S., Gurdal, O., Akkaya Oy, S. (2020). Design and optimization of tubular linear permanent-magnet generator with performance improvement using response surface methodology and multi-objective genetic algorithm. Scientia Iranica, 27(6), 3053-3065.
  • Babetto, C., Bacco, G., & Bianchi, N. (2018). Synchronous reluctance machine optimization for high-speed applications. IEEE Transactions on Energy Conversion, 33(3), 1266-1273.
  • Bacco, G., & Bianchi, N. (2018). Design criteria of flux-barriers in synchronous reluctance machines. IEEE Transactions on Industry Applications, 55(3), 2490-2498.
  • Cupertino, F., Pellegrino, G., & Gerada, C. (2014). Design of synchronous reluctance motors with multiobjective optimization algorithms. IEEE Transactions on Industry Applications, 50(6), 3617-3627.
  • Heidari, H., Rassõlkin, A., Kallaste, A., Vaimann, T., Andriushchenko, E., Belahcen, A., & Lukichev, D. V. (2021). A review of synchronous reluctance motor-drive advancements. Sustainability, 13(2), 729.
  • Lovelace, E. C., Jahns, T. M., & Lang, J. H. (2002). A saturating lumped-parameter model for an interior PM synchronous machine. IEEE Transactions on Industry Applications, 38(3), 645-650.
  • Murata, T., & Ishibuchi, H. (1995, November). MOGA: multi-objective genetic algorithms. In IEEE international conference on evolutionary computation (Vol. 1, pp. 289-294). Piscataway, NJ, USA: IEEE.
  • Özçelik, N. G., (2016). IE4 verim sınıfı senkron relüktans motor tasarımı. Yüksek Lisans Tezi, İstanbul Teknik Üniversitesi, İstanbul.
  • Özdil, A., & Uzun, Y. (2021). Design and Analysis of a Rotor for a 22 kW Transversally Laminated Anisotropic Synchronous Reluctance Motor. Elektronika ir Elektrotechnika, 27(6), 17-24.
  • Palmieri, M., Perta, M., Cupertino, F., & Pellegrino, G. (2014, May). Effect of the numbers of slots and barriers on the optimal design of synchronous reluctance machines. In 2014 international conference on optimization of electrical and electronic equipment (OPTIM) (pp. 260-267). IEEE.
  • Sanada, M., Hiramoto, K., Morimoto, S., & Takeda, Y. (2004). Torque ripple improvement for synchronous reluctance motor using an asymmetric flux barrier arrangement. IEEE Transactions on Industry Applications, 40(4), 1076-1082.
  • Sizov, G. Y., Ionel, D. M., & Demerdash, N. A. (2011, May). Multi-objective optimization of PM AC machines using computationally efficient-FEA and differential evolution. In 2011 IEEE International Electric Machines & Drives Conference (IEMDC) (pp. 1528-1533). IEEE.
  • Solak, B., (2021). Senkron Relüktans Motorda Moment Dalgalanmasının Azaltılması. Yüksek Lisans Tezi, Yıldız Teknik Üniversitesi, İstanbul.
  • Tarımer, İ., Arslan, S., & Güven, M. E. (2012). Investigation for losses of M19 and amorphous core materials asynchronous motor by finite elements methods. Elektronika Ir Elektrotechnika, 18(9), 15-18.
  • Tawfiq, K. B., Ibrahim, M. N., El-Kholy, E. E., & Sergeant, P. (2021). Performance Improvement of Synchronous Reluctance Machines–A Review Research. IEEE Transactions on Magnetics.
  • Topaloglu, I., Mamur, H., Korkmaz, F., & Cakir, M. F. (2014, October). Design and optimization of surface mounted line start permanent magnet synchronous motor using electromagnetic design tool. In 2014 International Conference on Renewable Energy Research and Application (ICRERA) (pp. 87-90). IEEE.
  • Wang, K., Zhu, Z. Q., Ombach, G., Koch, M., Zhang, S., & Xu, J. (2015). Torque ripple reduction of synchronous reluctance machines: using asymmetric flux-barrier. COMPEL: The International Journal for Computation and Mathematics in Electrical and Electronic Engineering.
  • Zhang, Z. (2021, May). Advanced non-permanent-magnet reluctance machines for traction applications: A review. In 2021 IEEE 12th Energy Conversion Congress & Exposition-Asia (ECCE-Asia) (pp. 2052-2058). IEEE.

Optimization of Transverse-Laminated Synchronous Reluctance Motor by Using Multi-Purpose Genetic Algorithm Method

Year 2022, Volume: 12 Issue: 2, 841 - 852, 15.12.2022
https://doi.org/10.31466/kfbd.1169294

Abstract

Although the synchronous reluctance motor (SynRM) has the same body structure as the induction motor, the rotor structures are different. Since the rotor does not contain any copper or aluminum rods in the winding, rotor losses are reduced and efficiency is increased. However, SynRM's torque ripple is a major problem and reducing torque ripple without degrading engine performance is essential. For this purpose, 4 kW synchronous reluctance motor was considered in the study. All electrical and mechanical data of the motor were defined in the Ansys Maxwell program and the analysis of the motor was carried out. Optimization studies were carried out using the multi-objective genetic algorithm (MOGA) method in line with the defined objective functions to increase the engine performance. Rotor sizing parameters are defined as input variables and output sizes as output power, efficiency, torque, torque ripple, saliency ratio. Five objective functions were tested with MOGA for barrier numbers 3, 4 and 5, respectively. The results obtained from the considered objective functions were compared with the reference motor data. Except for objective function 1, other objective functions cannot meet the reference motor in terms of efficiency, output power, torque fluctuation. While no change was observed in the efficiency obtained from the 4-barrier objective function 1, an increase of 0.31% in output power and a decrease of 31.71% in torque fluctuation were observed.

References

  • Arslan, S. (2016). Dalgıç Motorun Analitik, Sayısal, Performans Sonuçlarının Karşılaştırılması. Düzce Üniversitesi Bilim ve Teknoloji Dergisi, 4(2), 403-415.
  • Arslan Serdal, Akkaya Oy Sibel, Tören Murat (2016). Amorphous Nüveli Dalgıç Motorun ve Üç Fazlı Amorf Nüveli Transformatörün Demir Kayıplarının Sonlu Elemanlar Yöntemi ile İncelenmesi. 1. International Academıc Research Congress
  • Arslan, S., Gurdal, O., Akkaya Oy, S. (2020). Design and optimization of tubular linear permanent-magnet generator with performance improvement using response surface methodology and multi-objective genetic algorithm. Scientia Iranica, 27(6), 3053-3065.
  • Babetto, C., Bacco, G., & Bianchi, N. (2018). Synchronous reluctance machine optimization for high-speed applications. IEEE Transactions on Energy Conversion, 33(3), 1266-1273.
  • Bacco, G., & Bianchi, N. (2018). Design criteria of flux-barriers in synchronous reluctance machines. IEEE Transactions on Industry Applications, 55(3), 2490-2498.
  • Cupertino, F., Pellegrino, G., & Gerada, C. (2014). Design of synchronous reluctance motors with multiobjective optimization algorithms. IEEE Transactions on Industry Applications, 50(6), 3617-3627.
  • Heidari, H., Rassõlkin, A., Kallaste, A., Vaimann, T., Andriushchenko, E., Belahcen, A., & Lukichev, D. V. (2021). A review of synchronous reluctance motor-drive advancements. Sustainability, 13(2), 729.
  • Lovelace, E. C., Jahns, T. M., & Lang, J. H. (2002). A saturating lumped-parameter model for an interior PM synchronous machine. IEEE Transactions on Industry Applications, 38(3), 645-650.
  • Murata, T., & Ishibuchi, H. (1995, November). MOGA: multi-objective genetic algorithms. In IEEE international conference on evolutionary computation (Vol. 1, pp. 289-294). Piscataway, NJ, USA: IEEE.
  • Özçelik, N. G., (2016). IE4 verim sınıfı senkron relüktans motor tasarımı. Yüksek Lisans Tezi, İstanbul Teknik Üniversitesi, İstanbul.
  • Özdil, A., & Uzun, Y. (2021). Design and Analysis of a Rotor for a 22 kW Transversally Laminated Anisotropic Synchronous Reluctance Motor. Elektronika ir Elektrotechnika, 27(6), 17-24.
  • Palmieri, M., Perta, M., Cupertino, F., & Pellegrino, G. (2014, May). Effect of the numbers of slots and barriers on the optimal design of synchronous reluctance machines. In 2014 international conference on optimization of electrical and electronic equipment (OPTIM) (pp. 260-267). IEEE.
  • Sanada, M., Hiramoto, K., Morimoto, S., & Takeda, Y. (2004). Torque ripple improvement for synchronous reluctance motor using an asymmetric flux barrier arrangement. IEEE Transactions on Industry Applications, 40(4), 1076-1082.
  • Sizov, G. Y., Ionel, D. M., & Demerdash, N. A. (2011, May). Multi-objective optimization of PM AC machines using computationally efficient-FEA and differential evolution. In 2011 IEEE International Electric Machines & Drives Conference (IEMDC) (pp. 1528-1533). IEEE.
  • Solak, B., (2021). Senkron Relüktans Motorda Moment Dalgalanmasının Azaltılması. Yüksek Lisans Tezi, Yıldız Teknik Üniversitesi, İstanbul.
  • Tarımer, İ., Arslan, S., & Güven, M. E. (2012). Investigation for losses of M19 and amorphous core materials asynchronous motor by finite elements methods. Elektronika Ir Elektrotechnika, 18(9), 15-18.
  • Tawfiq, K. B., Ibrahim, M. N., El-Kholy, E. E., & Sergeant, P. (2021). Performance Improvement of Synchronous Reluctance Machines–A Review Research. IEEE Transactions on Magnetics.
  • Topaloglu, I., Mamur, H., Korkmaz, F., & Cakir, M. F. (2014, October). Design and optimization of surface mounted line start permanent magnet synchronous motor using electromagnetic design tool. In 2014 International Conference on Renewable Energy Research and Application (ICRERA) (pp. 87-90). IEEE.
  • Wang, K., Zhu, Z. Q., Ombach, G., Koch, M., Zhang, S., & Xu, J. (2015). Torque ripple reduction of synchronous reluctance machines: using asymmetric flux-barrier. COMPEL: The International Journal for Computation and Mathematics in Electrical and Electronic Engineering.
  • Zhang, Z. (2021, May). Advanced non-permanent-magnet reluctance machines for traction applications: A review. In 2021 IEEE 12th Energy Conversion Congress & Exposition-Asia (ECCE-Asia) (pp. 2052-2058). IEEE.
There are 20 citations in total.

Details

Primary Language Turkish
Subjects Engineering
Journal Section Articles
Authors

Hasan Çamcı 0000-0002-0193-9509

Onur Özdal Mengi

Serdal Arslan

Publication Date December 15, 2022
Published in Issue Year 2022 Volume: 12 Issue: 2

Cite

APA Çamcı, H., Mengi, O. Ö., & Arslan, S. (2022). Çok Amaçlı Genetik Algoritma Yöntemi Kullanılarak Enine Laminasyonlu Senkron Relüktans Motor Optimizasyonu. Karadeniz Fen Bilimleri Dergisi, 12(2), 841-852. https://doi.org/10.31466/kfbd.1169294