Physics Informed Neural Network-based High-frequency Modeling of Induction Motors

doi:10.23919/CJEE.2022.000036

Chinese Journal of Electrical Engineering ›› 2022, Vol. 8 ›› Issue (4): 30-38.doi: 10.23919/CJEE.2022.000036

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Physics Informed Neural Network-based High-frequency Modeling of Induction Motors

Zhenyu Zhao¹, Fei Fan^1,*, Quqin Sun², Huamin Jie¹, Zhou Shu¹, Wensong Wang¹, Kye Yak See¹

1. School of Electrical and Electronic Engineering,Nanyang Technological University, Singapore 639798, Singapore;
2. Science and Technology on Thermal Energy and Power Laboratory,Wuhan Second Ship Design and Research Institute, Wuhan 430000, China

Received:2022-10-20 Revised:2022-11-10 Accepted:2022-11-21 Online:2022-12-25 Published:2023-01-13
Contact: * E-mail: fanf0003@e.ntu.edu.sg
About author:Zhenyu Zhao (M'21) received the B.Eng. degree in Electrical and Electronic Engineering from Huazhong University of Science and Technology, Wuhan, China, in 2015, and the Ph.D. degree in Electrical and Electronic Engineering from Nanyang Technological University, Singapore, in 2021.
He is a Research Fellow at Nanyang Technological University. His research interests include electromagnetic interference, electromagnetic security, impedance measurements, and electromagnetic sensors. In these areas, he has authored and co-authored more than 50 refereed papers.
Dr. Zhao received 4 awards and 3 award finalists from IEEE, including the Best Student Paper Award at the Joint IEEE EMC & APEMC 2018, the Best Paper Award Finalist at the APEMC 2021, the Young Scientist Award and the Best Paper Award at the APEMC 2022. He was invited to participate in the Global Young Scientists Summit in 2019 and 2022. He has served as a Session Chair/Organizer and a TPC Member for many international conferences. Since 2022, he has been serving as an Executive Committee Member and the Secretary of the IEEE EMC Society, Singapore Chapter.
Fei Fan (M'19) received the B.Eng. degree in Electrical Engineering from Tianjin University, Tianjin, China, in 2014, and the M.Sc. in Power Engineering and Ph.D. degrees in Electrical Engineering from Nanyang Technological University (NTU), Singapore, in 2015 and 2020, respectively.
He is currently a Research Fellow in the School of Electrical and Electronic Engineering, NTU. His research interests include electromagnetic compatibility and electromagnetic interference measurement, in-circuit impedance extraction, and EMI filter design for motor drive systems.
Dr. Fan was a recipient of the Best Student Paper Award at the 2017 Asia-Pacific Symposium on Electromagnetic Compatibility (APEMC) and Progress in Electromagnetics Research Symposium (PIERS).
Quqin Sun received the B.Eng. and Ph.D. degrees in Electrical Engineering from Huazhong University of Science and Technology, Wuhan, China. in 2011 and 2016, respectively.
He worked as a Research Associate at the Institute of Fluid Physics of China Academy of Engineering Physics till 2018. From 2018 to 2021, he joined Nanyang Technological University, Singapore, as a Research Fellow. He is now an Engineer in Wuhan Second Ship Design and Research Institute. His research interests include high-field pulsed magnet design, electromagnetic launch, laser-ultrasonic non-destructive inspection, and motor condition monitoring.
Huamin Jie (S'22) received the B.Eng. degree in Electrical Engineering from Wuhan University, Wuhan, China, in 2019, and the M.Sc. degree in Power Engineering from Nanyang Technological University, Singapore, in 2020, respectively. He is currently working toward the Ph.D. degree with the School of Electrical and Electronic Engineering, Nanyang Technological University.
His research interests include impedance measurements, device modeling, electromagnetic interference (EMI), and EMI filter design.
Zhou Shu (M'21) received the B.Sc., M.Eng. and Ph.D. degrees in Integrated Circuit and System from Chongqing University, Chongqing, China, in 2015, 2017, and 2020, respectively.
In 2021, he joined Nanyang Technological University, Singapore, as a Research Fellow. His research interests include mixed-signal integrated circuit design for high-speed wireline links, power management units and low-power sensor interfaces, and testing and fault diagnosis for industrial applications.
Wensong Wang (M'18-SM'22) received the Ph.D. degree in Communication and Information Systems from Nanjing University of Aeronautics and Astronautics, Nanjing, China, in 2016.
From 2013 to 2015, he was a Visiting Scholar with the University of South Carolina, Columbia, USA. In 2017, he joined Nanyang Technological University, Singapore, as a Research Fellow, and now he is a Senior Research Fellow.
His research interests include MIMO antenna, antenna arrays, and advanced sensors.
Kye Yak See (M'86-SM'02) received the B.Eng. degree in Electrical Engineering from National University of Singapore, Singapore, in 1986, and the Ph.D. degree in Electrical Engineering from Imperial College London, UK, in 1997.
From 1986 to 1991, he was with Singapore Technologies Electronics, Singapore, as a Senior Engineer. From 1991 to 1994, he was a lead Design Engineer with ASTEC Custom Power, Singapore. Since 1997, he has been with Nanyang Technological University (NTU), Singapore, as a Faculty Member. He is currently an Associate Professor with the School of Electrical and Electronic Engineering, NTU. He holds concurrent appointment as Director of the Electromagnetic Effects Research Laboratory and Director of SMRT-NTU Smart Urban Rail Corporate Laboratory. His current research interests include electromagnetic compatibility (EMC), signal integrity, and real-time condition monitoring.
Dr. See is the Founding Chairs of the IEEE Electromagnetic Compatibility (EMC) Chapter, IEEE Aerospace and Electronic Systems, and the IEEE Geoscience and Remote Sensing Joint Chapter in Singapore. He was the General Chairs of 2015 Asia Pacific Conference on Synthetic Aperture Radar (APSAR 2015) and 2018 International Conference on Intelligent Rail Transportation (ICIRT 2018). Since January 2012, he has been the Technical Editor of the IEEE Electromagnetic Compatibility Magazine.

Abstract

Abstract: The high-frequency (HF) modeling of induction motors plays a key role in predicting the motor terminal overvoltage and conducted emissions in a motor drive system. In this study, a physics informed neural network-based HF modeling method, which has the merits of high accuracy, good versatility, and simple parameterization, is proposed. The proposed model of the induction motor consists of a three-phase equivalent circuit with eighteen circuit elements per phase to ensure model accuracy. The per phase circuit structure is symmetric concerning its phase-start and phase-end points. This symmetry enables the proposed model to be applicable for both star- and delta-connected induction motors without having to recalculate the circuit element values when changing the motor connection from star to delta and vice versa. Motor physics knowledge, namely per-phase impedances, are used in the artificial neural network to obtain the values of the circuit elements. The parameterization can be easily implemented within a few minutes using a common personal computer (PC). Case studies verify the effectiveness of the proposed HF modeling method.

Key words: Equivalent circuit, high-frequency (HF) modeling, induction motor, parameterization, physics informed neural network

Zhenyu Zhao, Fei Fan, Quqin Sun, Huamin Jie, Zhou Shu, Wensong Wang, Kye Yak See. Physics Informed Neural Network-based High-frequency Modeling of Induction Motors[J]. Chinese Journal of Electrical Engineering, 2022, 8(4): 30-38.

References

[1] S Amarir, K Al-Haddad.A modeling technique to analyze the impact of inverter supply voltage and cable length on industrial motor-drives.IEEE Trans. Power Electron., 2008, 23(2): 753-762.
[2] G Skibinski, R Kerkman, D Leggate, et al.Reflected wave modeling techniques for PWM AC motor drives. Proc. Appl. Power Electron. Conf. (APEC), February 15-19, 1998, Anaheim, CA, USA. IEEE, 1998: 1021-1029.
[3] M Ghassemi.Accelerated insulation aging due to fast, repetitive voltages: A review identifying challenges and future research needs. IEEE Trans.Dielectr. Electr. Insul., 2019, 26(5): 1558-1568.
[4] Z Yang, H Li, Z Yang, et al.Conducted electromagnetic interference analysis method for traction drive system in high speed trains. 2017 IEEE Transp. Electrific. Conf. Expo, Asia-Pacific, August 7-10, 2017, Harbin, China. IEEE, 2017: 1-5.
[5] Z Zhang, Y Hu, X Chen, et al.A review on conductive common-mode EMI suppression methods in inverter fed motor drives.IEEE Access, 2021, 9: 18345-18360.
[6] G Grandi, D Casadei, U Reggiani.Common- and differential-mode HF current components in AC motors supplied by voltage source inverters.IEEE Trans. Power Electron., 2004, 19(1): 16-24.
[7] Z Yang, H Li, C Feng, et al.Survey on electromagnetic interference analysis for traction converters in railway vehicles. Proc. IEEE Int. Power Electron. Conf., May 20-24, 2018, Niigata, Japan. IEEE, 2018: 2058-2065.
[8] L Ran, S Gokani, J Clare, et al.Conducted electromagnetic emissions in induction motor drive systems I: Time domain analysis and identification of dominant modes.IEEE Trans. Power Electron., 1998, 13(4): 757-767.
[9] M M Swamy, K Yamada, T Kume.Common mode current attenuation techniques for use with PWM drives.IEEE Trans. Power Electron., 2001, 16(2): 248-255.
[10] L Wang, C N Ho, F Canales, et al.High-frequency modeling of the long-cable-fed induction motor drive system using TLM approach for predicting overvoltage transients.IEEE Trans. Power Electron., 2010, 25(10): 2653-2664.
[11] G Suresh, A Toliyat, A Rendusara, et al.Predicting the transient effects of PWM voltage waveform on the stator windings of random wound induction motors.IEEE Trans. Power Electron., 1999, 14(1): 23-30.
[12] K Maki, H Funato, L Shao.Motor modeling for EMC simulation by 3-D electromagnetic field analysis. 2009 IEEE International Electric Machines and Drives Conf., May 3-6, 2009, Miami, FL, USA. IEEE, 2009: 103-108.
[13] V Mihaila, S Duchesne, D Roger.A simulation method to predict the turn-to-turn voltage spikes in a PWM fed motor winding.IEEE Trans. Dielectr. Electr. Insul., 2011, 18(5): 1609-1615.
[14] Y Ryu, M Yea, J Kim, et al.Stator impedance modeling platform for the electromagnetic compatibility aware design of 3.7-to 7.5-kW squirrel-cage induction motors.IEEE Trans. Ind. Electron., 2021, 68(11): 11255-11265.
[15] L Ran, S Gokani, J Clare, et al.Conducted electromagnetic emissions in induction motor drive systems part II: Frequency domain models.IEEE Trans. Power Electron., 1998, 13(4): 768-776.
[16] F Fan, K Y See, X Liu, et al.Systematic common-mode filter design for inverter-driven motor system based on in-circuit impedance extraction.IEEE Trans. Electromagn. Compat., 2020, 62(5): 1711-1722.
[17] F Costa, C Vollaire, R Meuret.Modeling of conducted common mode perturbations in variable-speed drive systems.IEEE Trans. Electromagn. Compat., 2005, 47(4): 1012-1021.
[18] A F Moreira, T A Lipo, G Venkataramanan, et al.High-frequency modeling for cable and induction motor overvoltage studies in long cable drives.IEEE Trans. Ind. Appl., 2002, 38(5):1297-1306.
[19] A Boglietti, A Cavagnino, M Lazzari.Experimental high-frequency parameter identification of AC electrical motors.IEEE Trans. Ind. Appl., 2007, 43(1): 23-29.
[20] J Sun, L Xing.Parameterization of three-phase electric machine models for EMI simulation.IEEE Trans. Power Electron., 2014, 29(1): 36-41.
[21] M S Toulabi, L Wang, L Bieber, et al.A universal high-frequency induction machine model and characterization method for arbitrary stator winding connections.IEEE Trans. Energy Convers., 2019, 34(3): 1164-1177.
[22] M Schinkel, S Weber, S Guttowski, et al.Efficient HF modeling and model parameterization of induction machines for time and frequency domain simulations. Proc. IEEE Appl. Power Electron. Conf. Expo. (APEC), March 19-23, 2006, Dallas, TX, USA. IEEE, 2006: 1-6.
[23] B Mirafzal, G Skibinski, R Tallam.Determination of parameters in the universal induction motor model.IEEE Trans. Ind. Appl., 2009, 45(1): 142-151.
[24] V Karakaşlı, F Gross, T Braun, et al.High-frequency modeling of delta- and star-connected induction motors.IEEE Trans. Electromagn. Compat., 2022, 64(4): 1533-1544.
[25] M Degano, P Zanchetta, L Empringham, et al.HF induction motor modeling using automated experimental impedance measurement matching.IEEE Trans. Ind. Electron., 2012, 59(10): 3789-3796.
[26] H Chen, S Ye.Modeling of common-mode impedance of an inverter-fed induction motor from online measurement.IEEE Trans. Electromagn. Compat., 2018, 60(5): 1581-1589.
[27] Z Zhao, F Fan, Q Sun, et al.High-frequency modeling of induction motor using multilayer perceptron. Proc. Asia- Pacific Int. Symp. Electro. Compat., September 1-4, 2022, Beijing, China. IEEE, 2022: 222-224.

Physics Informed Neural Network-based High-frequency Modeling of Induction Motors

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