Constrained optimization of the brushless DC motor using the salp swarm algorithm

• Autorzy: Knypiński Łukasz , Devarepalli Ramesh , Le Menach Yvonnick

Identyfikatory

DOI

10.24425/aee.2022.141684

• Języki publikacji: EN

Abstrakty

EN

This paper presents an algorithm and optimization procedure for the optimization of the outer rotor structure of the brushless DC (BLDC) motor. The optimization software was developed in the Delphi Tiburón development environment. The optimization procedure is based on the salp swarm algorithm. The effectiveness of the developed optimization procedurewas compared with genetic algorithm and particle swarmoptimization algorithm. The mathematical model of the device includes the electromagnetic field equations taking into account the non-linearity of the ferromagnetic material, equations of external supply circuits and equations of mechanical motion. The external penalty function was introduced into the optimization algorithm to take into account the non-linear constraint function.

Słowa kluczowe

EN

brushless DC motor; constrained optimization; finite element analysis; salp swarm algorithm

• Wydawca: Polish Academy of Sciences, Committee on Electrical Engineering
• Czasopismo: Archives of Electrical Engineering
• Rocznik: 2022
• Tom: Vol. 71, nr 3
• Strony: 775--787
• Opis fizyczny: Bibliogr. 24 poz., rys., tab., wz.

Twórcy

autor

Knypiński Łukasz

• Poznan University of Technology, Poland

• https://orcid.org/0000-0001-5741-9548

autor

Devarepalli Ramesh

• Department of EEE, Lendi Institute of Engineering and Technology Vizianagaram, India

• https://orcid.org/0000-0003-4246-7728

autor

Le Menach Yvonnick

• Lille University, France

• https://orcid.org/0000-0001-8689-6685

Bibliografia

• [1] Seong Oh B., Cho J., Choi B., Wone Choi H., Soo Kim M., Lee G., Application of Heuristic Algorithms for Design Optimization of Industrial Heat Pump, International Journal of Refrigeration, vol. 134, pp. 1–15 (2022), DOI: 10.1016/j.ijrefrig.2021.11.002.
• [2] Mutluer M., Sahman A., Cunkas M., Heuristic optimization based on penalty approach for surface permanent magnet synchronous machines, Arabian Journal for Science and Engineering, vol. 45, pp. 6751–6767 (2020), DOI: 10.1007/s13369-020-04689-y.
• [3] Knypiński Ł., Pawełkoszek K., Le Menach Y., Optimization of low-power line-start PM motor using gray wolf metaheuristic algorithm, Energies, vol. 13, no. 1186 (2020), DOI: 10.3390/en13051186.
• [4] Barański M., Szeląg W., Łyskawiński W., Experimental and Simulation Studies of Partial Demagnetization Process of Permanent Magnets in Electric Motors, IEEE Transactions on Energy Conversion, vol. 36, no. 4, pp. 3137–3145 (2021), DOI: 10.1109/TEC.2021.3082903.
• [5] Pettes-Duler M., Roboam X., Sareni B., Lefevre Y., Llibre J.F., Fénot M., Multidisciplinary Design Optimization of the Actuation System of a Hybrid Electric Aircraft Powertrain, Electronics, vol. 10, no. 1297 (2021), DOI: 10.3390/electronics10111297.
• [6] Marault J., Tounzi A., Gillon F., Hecquet M., Use of current sheet coupled to an analytical tool to analyze by FEM the harmonic content of armature winding ditribution, COMPEL, vol. 39, no. 6, pp. 1329–1344 (2020), DOI: 10.1108/COMPEL-01-2020-0052.
• [7] Wardach M., Paplicki P., Palka R., A Hybrid Excited Machine with Flux Barriers and Magnetic Bridges, Energies, vol. 11, no. 676, pp. 1–8 (2018), DOI: 10.3390/en11030676.
• [8] Fleurot E., Franck Scuiller F., Jean-Frédéric Charpentier J.F., Analytical Models for Fast and Accurate Calculation of Electromagnetic Performances of Segmented Permanent Magnet Synchronous Machines with Large Angular Gap, Applied Sciences, vol. 11. no. 459, pp. 1–9 (2021), DOI: 10.3390/app11010459.
• [9] Ullah W., Khan F., Umair M., Lumped parameter magnetic equivalent circuit model for design of segmented PM consequent pole flux switching machine, Engineering Computations, vol. 38, no. 2, pp. 572–585 (2021), DOI: 10.1108/EC-04-2020-0201.
• [10] Knypiński Ł., Constrained optimization of line-start PM motor based on the gray wolf optimizer, Ekspolatacja i Niezawodność – Maintaince nad Reliability, vol. 23, no. 1, pp. 1–10 (2021), DOI: 10.17531/ein.2021.1.1.
• [11] Arsyad H., Suyuti A., Mawar Said S., Syam Akil Y., Multi-objective dynamic economic dispatch using Fruit Fly Optimization method, Archives of Electrical Engineering, vol. 70, no 2, pp. 351–366 (2021), DOI: 10.24425/aee.2021.136989.
• [12] Wang S., Jia H., Peng X., Modified salp swarm algorithm based multilevel thresholding for color image segmentation, Mathematical Biosciences and Engineering, vol. 17, no. 1, pp. 700–724 (2020), DOI: 10.3934/mbe.2020036.
• [13] Mirjalili S., Gandomi A.H., Zahra Mirjalili S., Saremi S., Faris H., Mohammad Mirjalili S., Salp Swarm Algorithm: A bio-inspired optimizer for engineering design problems, Advances in Engineering Software, vol. 114, pp. 163–191 (2017), DOI: 10.1016/j.advengsoft.2017.07.002.
• [14] Madina L.P., Kremerb P., Wiebea P.H., Purcellc J.E., Horgana E.H., Nemaziec D.A., Periodic swarms of the salp Salpa aspera in the Slope Water off the NE United States: Biovolume, vertical migration, grazing, and vertical flux, Deep Sea Research Part I: Oceanographic, vol. 53, no 5, pp. 804–819 (2006), DOI: 10.1016/j.dsr.2005.12.018.
• [15] Mahmood M.A., Al-Anbarri K.A., Optimum unit commitment solution of a power system based on slap swarm algorithm, Journal of Engineering and Sustainable Development, pp. 1–13 (2021), DOI: 10.31272/jeasd.conf.2.1.12.
• [16] Devarapalli R., Bhattacharyya B., Sinha N.K., An intelligent EGWO-SCA-CS algorithm for PSS parameter tuning under system uncertainties, International Journal of Intelligent Systems, vol. 35, no. 10, pp. 1520–1569 (2020), DOI: 10.1002/int.22263.
• [17] Knypiński Ł., Performance analysis of selected metaheuristic optimization algorithms applied in the solution of an unconstrained task, COMPEL (2022), DOI: 10.1108/COMPEL-07-2021-0254.
• [18] https://www.sfu.ca/~ssurjano/goldpr.html, accessed January 2022.
• [19] Jędryczka C., Sujka P., Szeląg W., The influence magnetic hysteresis on magnetorheological fluid clutch operation, COMPEL, vol. 28, no. 3, pp. 711–721 (2009), DOI: 10.1108/03321640910940963.
• [20] Knypiński Ł., Nowak L., Fidel-circuit simulation of the dynamics of the outer rotor permanent magnet brushless DC motor, COMPEL, vol. 30, no. 2, pp 929–440 (2011), DOI: 10.1108/03321641111110898.
• [21] Pourjafari M., Fallah Choolabi E., Jafar Bolan M., Optimum Design of BrushLess DC Motor with Minimum Torque Pulsation using FEM and PSO, Amirkabir International Journal of Electrical and Electronics Engineering, vol. 44, no. 2, pp. 59–70 (2012), DOI: 10.22060/eej.2012.360.
• [22] Knypiński Ł., Kuroczycki S., Marquez F.P.G., Minimization of Torque Ripple in the Brushless DC Motor Using Constrained Cuckoo Search Algorithm, Electronics, vol. 10, no. 18, pp. 2299-1–2299-20 (2021), DOI: 10.3390/electronics10182299.
• [23] Ge J., Xu W., Liu Y., Xiong F., Novel Equivalent Circuit Model Applicable to All Operation Modes for Brushless Doubly-Fed Induction Machines, IEEE Transactions on Industrial Electronics (2022), DOI: 10.1109/TIE.2022.3144567.
• [24] De Gregoriis D., Naets F., Kindt P., Application of a-priori hyper-reduction to the nonlinear dynamic finite element simulation of a rolling car tire, Journal of Computational and Nonlinear Dynamics, vol. 14; no. 11, pp. 111009-1–111009-13 (2019), DOI: 10.1115/1.4043892.

Uwagi

Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).