China's High-Speed Rail Technology pp 561-576 | Cite as
A Combined Simulation of High-Speed Train Permanent Magnet Traction System Using Dynamic Reluctance Mesh Model and Simulink
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Abstract
This paper presents a combined dynamic parameter model (DPM) of a high-speed train permanent magnet traction system using a dynamic reluctance mesh model and MATLAB Simulink. First, the dynamic reluctance model of the permanent magnet synchronous motor is introduced. Then the combined models of the traction system under i d = 0 and maximum torque per ampere control are built. Simulations using both constant parameter models and DPM models are carried out. The speed and torque characteristics are obtained. The results confirm that the DPM model provides higher accuracy without much sacrifice of time consumption or computation resource.
Keywords
Permanent magnet traction system Dynamic reluctance mesh model Dynamic parameter model (DPM) High-speed train Maximum torque per ampere controlReferences
- Araujo, D. M., Coulomb, J. L., Chadebec, O., et al. (2014). A hybrid boundary element method-reluctance network method for open boundary 3-d nonlinear problems. IEEE Transactions on Magnetics, 50(2), 77–80. doi: 10.1109/TMAG.2013.2281759.CrossRefGoogle Scholar
- Carpenter, C. J. (1968). Magnetic equivalent circuits. Proceedings of the Institution of Electrical Engineers, 115(10), 1503–1511.CrossRefGoogle Scholar
- Dogan, H., Garbuio, L., Nguyen-Xuan, H., et al. (2013). Multistatic reluctance network modeling for the design of permanent-magnet synchronous machines. IEEE Transactions on Magnetics, 49(5), 2347–2350. doi: 10.1109/TMAG.2013.2243426.CrossRefGoogle Scholar
- Lee, K. K. (2012). The evolution and outlook of core technologies for high-speed railway in China. 1st international workshop on high-speed and intercity railways, 2:495–507. doi: 10.1007/978-3-642-27963-8_45.
- Lu, Q. F., Wang, B., Huang, X. Y., et al. (2011). Simulation software for CRH2 and CRH3 traction driver systems based on Simulink and VC. Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering), 12(12), 945–949. doi: 10.1631/jzus.A11GT006.CrossRefGoogle Scholar
- Matsuoka, K. (2007). Development trend of the permanent magnet synchronous motor for railway traction. IEEJ Transactions on Electrical and Electronic Engineering, 2(2), 154–161. doi: 10.1002/tee.20121.CrossRefGoogle Scholar
- Mermet-Guyennet, M. (2010). New power technologies for traction drives. International symposium on power electronics, electrical drives, automation and motion, Pisa, Italy, pp. 719–723.Google Scholar
- Nguyen-Xuan, H., Dogan, H., Perez, S., et al. (2014). Efficient reluctance network formulation for electrical machine design using optimization. IEEE Transactions on Magnetics, 50(2), 869–872. doi: 10.1109/TMAG.2013.2282407.CrossRefGoogle Scholar
- Ostovic, V. (1986). A method for evaluation of transient and steady state performance in saturated squirrel cage induction machines. IEEE Transactions on Energy Conversion, 1(3), 190–197.CrossRefGoogle Scholar
- Ostovic, V. (1988). A simplified approach to magnetic equivalent-circuit modeling of induction machines. IEEE Transactions on Industry Applications, 24(2), 308–316.CrossRefGoogle Scholar
- Ostovic, V. (1989). A novel method for evaluation of transient states in saturated electric machines. IEEE Transactions on Industry Applications, 25(1), 96–100.CrossRefGoogle Scholar
- Sewell, P., Bradley, K. J., Clare, J. C., et al. (1999). Efficient dynamic models for induction machines. International Journal of Numerical Modelling: Electronic Networks, Devices and Fields, 12(6), 449–464. doi: 10.1002/(sici)1099-1204(199911/12)12:6<449:aid-jnm365>3.0.co;2-w.CrossRefMATHGoogle Scholar
- Tang, R. Y. (1997). Modern permanent magnet machines: theory and design (p. 473). Beijing, China: China Machine Pres. (in Chinese).Google Scholar
- Ugalde, G., Almandoz, G., Poza, J., et al. (2009). Computation of iron losses in permanent magnet machines by multi-domain simulations. In: 13th European Conference on Power Electronics and Applications, Barcelona (pp. 1–10).Google Scholar
- Wang, X. H. (2011). Permanent magnet machines (p. 327). Beijing, China: China Electric Power Press. (in Chinese).Google Scholar
- Yao, L. (2006). Magnetic field modelling of machine and multiple machine systems using dynamic reluctance mesh modelling. PhD Thesis, University of Nottingham, Nottingham, UK.Google Scholar
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