Vol. 9 No. 1 (2022)
Articles
Bond Graph Modeling, Simulation, and Control of Permanent Magnet Linear Synchronous Motor: PMLSM Motor Based EVs Applications
Published
December 31, 2022
https://doi.org/10.17667/riim.2022.1/3.View
Keywords
How to Cite
Selected stlye: APA
Babangida, A., Husi, G., & Szemes, P. (2022). Bond Graph Modeling, Simulation, and Control of Permanent Magnet Linear Synchronous Motor: PMLSM Motor Based EVs Applications. Recent Innovations in Mechatronics, 9(1). https://doi.org/10.17667/riim.2022.1/3.
Abstract
The high-performance feature of the Permanent Magnet Linear Synchronous Motor (PMLSM) makes it a reliable and valuable motor for use in the automotive industry, especially for electric vehicle (EVs) applications. This research proposes a bond graph approach in modeling the PMLSM as a multi-domain dynamical system.
However, A time-based simulation was performed using 20-sim software to simulate the dynamical behavior of the motor. An equivalent model of the motor was first obtained and then modeled and simulated using 20-sim software. The model of the PMLSM drive system was modeled separately and incorporated with PMLSM Motor equivalent model to form a global model.
Moreover, the motor drive system response was studied based on the sensor resolutions and the inverter switching frequency. The block diagram and the transfer function methods validated the bond graph model obtained. Two classical PIs such as continuous and discrete were implemented on the motor response to control the velocity of the motor.
References
International Conference on Magnetically Levitated Systems and Linear Drives, 2002, no. January 2002.
M. C. Sanchez and J. M. Larrahondo, “Permanent magnet synchronous linear motor for an urban transport electric vehicle,” Proc. - EMS 2015 UKSim-AMSS 9th IEEE Eur. Model. Symp. Comput. Model. Simul., pp. 301–306, 2016, DOI: 10.1109/EMS.2015.52.
T. Li, Y. Liu, and L. Sun, “Global Model of PMLSM Drive System Using Bond,” Electr. Power Syst. Comput., pp. 615–622, 2011.
R. Zrafi, S. Ghedira, and K. Besbes, “A bond graph approach for the modeling and simulation of a buck converter,” J. Low Power Electron. Appl., vol. 8, no. 1, 2018, DOI: 10.3390/jlpea8010002.
A. Vaz, S. S. Dhami, and S. Trivedi, “Bond graph modeling and simulation of three-phase PM BLDC motor,” in 14th National Conference on Machines and Mechanisms, NaCoMM 2009, 2020, pp. 1–6.
C. Batlle and A. Dòria-Cerezo, “Bond graph models of electromechanical systems. The AC generator case,” IEEE Int. Symp. Ind. Electron., pp. 1064–1069, 2008, DOI: 10.1109/ISIE.2008.4677192.
A. Grava, T. Maghiar, C. Grava, and Ş. Vasile, “The bond-graph analysis for the DC motor with permanent magnets,” 2017, no. July 2003.
A. M. Mughal, “A Theoretical Framework for Modeling and Simulation with Optimal Control System of Voluntary Biomechanical Movements A Theoretical Framework for Modeling and Simulation with Optimal Control System of Voluntary Biomechanical Movements by Asif Mahmood Mugha.”
J. T. Machado, “Bond graph and memristor approach to DNA analysis,” Nonlinear Dyn., vol. 88, no. 2, pp. 1051–1057, 2017, DOI: 10.1007/s11071-016-3294-z.
M. Zoheb and A. Mahmood, “Bond Graph Modeling and PID Controller Stabilization of Single Link Mechanical Model,” 1938, no. October.
A. M. Mughal and K. Iqbal, “Modelling and analysis physiological motor control using a bond graph,” in IFAC Proceedings Volumes (IFAC-PapersOnline), 2006, vol. 6, no. PART 1, pp. 393–398, DOI: 10.3182/20060920-3-fr-2912.00071.
S. H. Abbasi and A. Mahmood, “Bond graph modeling of a customized anthropomorphic prosthetic hand with LQR control synthesis,” in Proceedings of 2017 International Multi-Topic Conference, INMIC 2017, 2018, vol. 2018-Janua, no. November, pp. 1–6, DOI: 10.1109/INMIC.2017.8289466.
R. Tapia-Sánchez, “Electrical Power Analysis Using the Scattering Bond Graph,” J. Eng. (United Kingdom), vol. 2015, 2015, DOI: 10.1155/2015/501747.
A. K. Samantaray, K. Medjaher, B. O. Bouamama, M. Staroswiecki, and G. Dauphin-Tanguy, “Component-Based Modelling of Thermofluid Systems for Sensor Placement and Fault Detection,” Simulation, vol. 80, no. 7–8, pp. 381–398, 2004, DOI: 10.1177/0037549704046339.
W. Borutzky, “Bond graph modeling and simulation of mechatronic systems an introduction into the methodology,” in 20th European Conference on Modelling and Simulation: Modelling Methodologies and Simulation Key Technologies in Academia and Industry, ECMS 2006, 2006, pp. 17–28, DOI: 10.7148/2006-0017.
P. J. Gawthrop and G. P. Bevan, “A tutorial introduction for control engineers,” IEEE Control Syst., vol. 27, no. 2, pp. 24–45, 2007, DOI: 10.1109/MCS.2007.338279.
F. Azhar, H. Wakiwaka, K. Tashiro, and M. Nirei, “Design and performance index comparison of the permanent magnet linear motor,” Prog. Electromagn. Res. M, vol. 43, no. November, pp. 101–108, 2015, DOI: 10.2528/PIERM15071204.
N. A. Mohd Nasir, F. A. bin Abdul Shukor, R. N. Firdaus, H. Wakiwaka, K. Tashiro, and M. Nirei, “Design of the permanent magnet linear synchronous motor for high thrust and low cogging force performance,” Prog. Electromagn. Res. M, vol. 63, no. January, pp. 83–92, 2018, DOI: 10.2528/pierm17101907.
K. Divakar and N. R. Reddy, “Vector controlled PMLSM using simplified Space vector pulse width modulation,” vol. 2, no. 3, pp. 1105–1110, 2012.
T. Li, Q. Yang, and B. Peng, “Research on Permanent Magnet Linear Synchronous Motor Control System Simulation,” in AASRI Procedia, 2012, vol. 3, pp. 262–269, DOI: 10.1016/j.aasri.2012.11.043.
W. Te Su and C. M. Liaw, “Adaptive positioning control for an LPMSM drive based on the adapted inverse model and robust disturbance observer,” IEEE Trans. Power Electron., vol. 21, no. 2, pp. 505–517, 2006, DOI: 10.1109/TPEL.2005.869729.