Optimization of Electromechanical Energy Converters with a Solid Rotor Output Parameters in ANSYS RMxprt

Authors

  • Vladyslav Pliuhin O. M. Beketov National University of Urban Economy in Kharkiv
  • Oleksandr Petrenko O. M. Beketov National University of Urban Economy in Kharkiv
  • Yevgen Tsegelnyk O. M. Beketov National University of Urban Economy in Kharkiv
  • Oleksii Duniev National University of Life and Environmental Sciences of Ukraine
  • Andrii Yehorov National Technical University “Kharkiv Polytechnic Institute”
  • Illia Khudiakov O. M. Beketov National University of Urban Economy in Kharkiv

DOI:

https://doi.org/10.33042/2079-424X.2022.61.3.01

Keywords:

Electromechanical Energy Converter, Solid Rotor, ANSYS Maxwell, Optimetrics, Optimization, Cost Function

Abstract

The paper is devoted to finding the set value of the torque of an electromechanical energy converter with a solid rotor by solving an optimization problem in the Optimetrics module of the Ansys Maxwell software. A feature of the material described in the paper is the simultaneous optimization solution using the Sequential Nonlinear Programming (Gradient) algorithm and the solution of the field problem using the finite element method to determine the torque at each step of the iteration. The paper describes in detail the setting of the research tasks, the basic model of the electromechanical energy converter with a solid rotor in Ansys Maxwell 2D, the settings of the Optimetrics module, the task of the objective function and varied parameters, the convergence task with respect to the magnitude of the rotation torque, and the derivation and analysis of the results obtained during the optimization. The techniques described in this paper can be applied to any other type of electric machines.

Author Biographies

Vladyslav Pliuhin, O. M. Beketov National University of Urban Economy in Kharkiv

D.Sc., Professor, Department of Urban Power Supply and Consumption Systems

Oleksandr Petrenko, O. M. Beketov National University of Urban Economy in Kharkiv

D.Sc., Associate Professor, Department of Electric Transport

Yevgen Tsegelnyk, O. M. Beketov National University of Urban Economy in Kharkiv

Ph.D., Senior Researcher, Department of Automation and Computer-Integrated Technologies

Oleksii Duniev , National University of Life and Environmental Sciences of Ukraine

Ph.D., Associate Professor, Department of Electrical Machines

Andrii Yehorov, National Technical University “Kharkiv Polytechnic Institute”

Ph.D., Associate Professor, Department of Electrical Machines

Illia Khudiakov , O. M. Beketov National University of Urban Economy in Kharkiv

Postgraduate Student, Department of Urban Power Supply and Consumption Systems

References

Pliuhin, V., Sukhonos, M., Petrenko, A., & Ehorov, A. (2017). Implementation of genetic algorithm in electric machines optimization using Netbeans IDE and Java. Teka Komisji Motoryzacji i Energetyki Rolnictwa, 17(1), 5–14.

Pliuhin, V., Pan, M., Yesina, V., & Sukhonos, M. (2018). Using azure maching learning cloud technology for electric machines optimization. In 2018 International Scientific-Practical Conference Problems of Infocommunications. Science and Technology (PIC S&T) (pp. 55–58). IEEE. https://doi.org/10.1109/INFOCOMMST.2018.8632093

Ma, B., Zheng, J., Lei, G., Zhu, J., Jin, P., & Guo, Y. (2019). Topology optimization of ferromagnetic components in electrical machines. IEEE Transactions on Energy Conversion, 35(2), 786–798. https://doi.org/10.1109/TEC.2019.2960519

Sharifi, T., & Mirsalim, M. (2021). Optimal design of a synchronous reluctance motor using biogeography-based optimization. In 2021 29th Iranian Conference on Electrical Engineering (ICEE) (pp. 209–213). IEEE. https://doi.org/10.1109/ICEE52715.2021.9544319

Sadeghi, S., Hassanpour, A., & Saeedifard, M. (2022). Multi-objective design optimization of a dualsided permanent magnet linear motor for high-speed electric trains. In IECON 2022–48th Annual Conference of the IEEE Industrial Electronics Society (pp. 1-5). IEEE. https://doi.org/10.1109/IECON49645.2022.9968732

Istenes, G., & Horváth, Z. (2022). Multi-objective optimization of electric motors with a kriging surrogate model. In 2022 22nd International Symposium on Electrical Apparatus and Technologies (SIELA) (pp. 1–4). IEEE. https://doi.org/10.1109/SIELA54794.2022.9845694

Cosdu, M., Hacan, A., & Tekgun, B. (2020). Design optimization of an outer rotor PMSM for a drive cycle using an improved mode algorithm for a lightweight racing vehicle. In 2020 6th International Conference on Electric Power and Energy Conversion Systems (EPECS) (pp. 58–63). IEEE. https://doi.org/10.1109/EPECS48981.2020.9304956

COMSOL Multiphysics. https://comsol.com/

JMAG-Designer. https://jmag-international.com/

ANSYS Inc. (2012). ANSYS Maxwell 3D v.15 – Electromagnetic and Electromechanical Analysis: User’s Guide. ANSYS Inc.

Martyanov, A.S., & Neustroyev, N.I. (2014). AN-SYS Maxwell Software for electromagnetic field calculations. Eastern European Scientific Journal, 5, 206–210. https://doi.org/10.12851/EESJ201410C05ART03

Bal, S., Demirdelen, T., & Tümay, M. (2019). Threephase distribution transformer modeling and electromagnetic transient analysis using ANSYS Maxwell. In 2019 3rd International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT) (pp. 1–4). IEEE. https://doi.org/10.1109/ISMSIT.2019.8932953

Kassa, M.T., & Changqing, D. (2021). Design optimazation and simulation of PMSM based on Maxwell and Twin Builder for EVs. In 2021 8th International Conference on Electrical and Electronics Engineering (ICEEE) (pp. 99–103). IEEE. https://doi.org/10.1109/ICEEE52452.2021.9415922

Fiala, V., Dvořák, P., & Pechánek, R. (2022). Practical approach to multi-objective optimization in ANSYS

softwares. In 2022 20th International Conference on Mechatronics-Mechatronika (ME) (pp. 1–6). IEEE. https://doi.org/10.1109/ME54704.2022.9983056

Schwarz, P., & Moeckel, A. (2019). Electric machine design automation with Python and Ansys Maxwell. In IKMT 2019-Innovative small Drives and Micro-Motor Systems; 12. ETG/GMM-Symposium (pp. 1–7). VDE.

Xia, Z., Qahouq, J., & Kotru, S. (2021). 3-D physical model for on-chip power inductor design with evaluation of airgap variation effect. In 2021 IEEE Applied Power Electronics Conference and Exposition (APEC) (pp. 1725–1729). IEEE. https://doi.org/10.1109/APEC42165.2021.9487062

Shao, J., Wen, Y., & Wang, G. (2020). Magnetic field analysis of linear motor for high-speed maglev train. In 2020 IEEE MTT-S International Conference on Numerical Electromagnetic and Multiphysics Modeling and Optimization (NEMO) (pp. 1-4). IEEE. https://doi.org/10.1109/NEMO49486.2020.9343409

Shao, H., Zhong, C., Habetler, T.G., & Li, S. (2019). Multi-objective design optimization of synchronous reluctance machines based on the analytical model and the evolutionary algorithms. In 2019 North American Power Symposium (NAPS) (pp. 1–6). IEEE. https://doi.org/10.1109/NAPS46351.2019.9000252

Dal, Ö., Yıldırım, M., & Kürüm, H. (2019). Optimization of permanent magnet synchronous motor design by using PSO. In 2019 4th International Conference on Power Electronics and their Applications (ICPEA) (pp. 1–6). IEEE. https://doi.org/10.1109/ICPEA1.2019.8911192

Jin, Y., Wang, A., Wang, T., Sun, J., & Wang, M. (2018). Optimal design of loss of permanent magnet synchronous motor based on particle swarm optimization. In 2018 IEEE Student Conference on Electric Machines and Systems (pp. 1–4). IEEE. https://doi.org/10.1109/SCEMS.2018.8624873

Marwaha, S. (2021). Mitigation of cogging torque for the optimal design of BLDC motor. In 2021 IEEE 2nd International Conference on Electrical Power and Energy Systems (ICEPES) (pp. 1–5). IEEE. https://doi.org/10.1109/ICEPES52894.2021.9699544

Rastogi, S., Kumar, R., & Singh, S. (2016). Design, analysis and optimization of permanent magnet synchronous generator. In 2016 IEEE International Conference on Power Electronics, Drives and Energy Systems (PEDES) (pp. 1–5). IEEE. https://doi.org/10.1109/PEDES.2016.7914417

Liu, H., Brokaw, W., Harms, J., Wu, W., Epstein, M., Chalfant, T., … & Wu, T. (2012). Design and optimization of permanent magnet switch reluctance machine for renewable energy application. In 2012 XXth International Conference on Electrical Machines (pp. 612–617). IEEE. https://doi.org/10.1109/ICElMach.2012.6349933

Mariam, M.G., Khang, L.T., Aliza, C.A., & Kaiji, S. (2015). Force optimization of a linear motion type electrostatic microactuator using finite element method (FEM) analysis for high thrust performances. In 2015 10th Asian Control Conference (ASCC) (pp. 1–4). IEEE. https://doi.org/10.1109/ASCC.2015.7244870

Borchardt, N., & Kasper, R. (2017). Analytical magnetic circuit design optimization of electrical machines with air gap winding using a Halbach array. In 2017 IEEE International Electric Machines and Drives Conference (IEMDC) (pp. 1–7). IEEE. https://doi.org/10.1109/IEMDC.2017.8001995

Lolova, I., Barta, J., Bramerdorfer, G., & Silber, S. (2020). Topology optimization of line-start synchronous reluctance machine. In 2020 19th International Conference on Mechatronics-Mechatronika (ME) (pp. 1–7). IEEE. https://doi.org/10.1109/ME49197.2020.9286643

Ropoteanu, C., Svasta, P., & Buşu, I. (2015). Highfrequency power loss investigation of a planar ferrite core transformer. In 2015 IEEE 21st International Symposium for Design and Technology in Electronic Packaging (pp. 61–64). IEEE. https://doi.org/10.1109/SIITME.2015.7342296

Sorn, D., & Chen, Y. (2018). Design optimization of permanent magnet brushless direct current motor using radial basis function neural network. In 2018 IEEE 7th Data Driven Control and Learning Systems Conference (pp. 38–43). IEEE. https://doi.org/10.1109/DDCLS.2018.8515983

Zhang, X., Zhang, Y., Zhang, Z., & Li, M. (2020). Mode conversion and structure optimization of quadrature coils for electric vehicles wireless power transfer. IEEE Transactions on Energy Conversion, 35(2), 575–590. https://doi.org/10.1109/TEC.2020.2972584

Pliuhin, V., Plankovskyy, S., Zablodskiy, M., Biletskyi, I., Tsegelnyk, Y., & Kombarov, V. (2023). Novel features of special purpose induction electrical machines object-oriented design. In D.D. Cioboată (ed.) International Conference on Reliable Systems Engineering (ICoRSE) - 2022. LNNS, vol. 534 (pp 265–283). Springer https://doi.org/10.1007/978-3-031-15944-2_25

Pliuhin, V., Zablodskiy, M., Sukhonos, M., Tsegelnyk, Y., Piddubna, L. (2023). Determination of massive rotary electric machines parameters in ANSYS RMxprt and ANSYS Maxwell. In O. Arsenyeva, T. Romanova, M. Sukhonos, Y. Tsegelnyk (eds.) Smart Technologies in Urban Engineering. LNNS, vol. 536 (pp 189–201). Springer. https://doi.org/10.1007/978-3-031-20141-7_18

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Published

2022-12-30

How to Cite

Pliuhin, V., Petrenko, O., Tsegelnyk, Y., Duniev , O., Yehorov, A., & Khudiakov , I. (2022). Optimization of Electromechanical Energy Converters with a Solid Rotor Output Parameters in ANSYS RMxprt. Lighting Engineering & Power Engineering, 61(3), 74–85. https://doi.org/10.33042/2079-424X.2022.61.3.01

Issue

Vol. 61 No. 3 (2022): Lighting Engineering & Power Engineering

Section

Power Engineering

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