Performance prediction of switched reluctance generator with time average and small signal models

Abstract

This paper presents the complete mathematical model and predicts the performance of switched reluctance generator with time average and small signal models. The complete mathematical model is developed in three stages. First, a switching model is developed based on quasi-linear inductance profile. Next, based on the switching behaviour, a time average model is obtained to measure the difference between the excitation and generation time in each switching cycle. Finally, to track control voltage and current wave shapes, a small signal model is designed. The effectiveness of the complete multilevel model combining electrical machine, power converter, load and control with programming language is demonstrated through simulations. A PI controller is used for controlling the voltage of the generator. The results presented show that the controller exhibits accurate tracking control of load voltage under different operating conditions. This demonstrates that the proposed model is able to perform an accurate control of the generated output voltage even in transient situations. The simulation is performed to choose the control parameters and study the performance of switched reluctance generator prior to its actual implementation. Initial experimental results are presented using NI-Data acquisition card to control the output power according to load requirements.

Keywords

generator / reluctance / switching model / small signal model / time average model

References

[1] Miller T J E. Switched Reluctance Motor and their Control. Oxford: Magna Physics Publishing and Clarendon Press, 1993

[2] Krishnan R. Switched Reluctance Motor Drives—Modelling, Simulation, Analysis, Design and Applications. CRC Press, 2001

[3] Yifan T, Joseph A, Kline S. Modelling and design optimization of switched reluctance machine by boundary element analysis and simulation. IEEE Transactions on Energy Conversion, 1996, 11(4): 673-680

[4] Essah D N, Scott S. A basis function approach to the nonlinear average value modeling of switched reluctance machines. IEEE Transactions on Energy Conversion, 2006, 21(1): 60-68

[5] Besmi M R, Babaei M, Bahramgirit M. An analytical algorithm for modeling and obtaining flux density waveforms in various sections of switched reluctance machines. In: Proceedings of 3rd IET 3rd International Conference on PEMD. Dublin, Ireland, 2006, 662-665

[6] Xue X D, Cheng K W E, Ho S L, Sutanto D. Precise Analytical modelling magnetic characteristics of switched reluctance motor drive using two-dimensional least squares. IEEE Transactions on Magnetics, 2004, 40(2): 734-737

[7] Khalil A, Husain I. A Fourier series generalized geometry-based analytical model of switched reluctance machines. IEEE Transactions on Industry Applications, 2007, 43(3): 673-684

[8] Jie X, Chang L X. Modeling of switched reluctance motor based on Pi-Sigma neural network. In: Proceedings of IEEE international symposium on Industrial electronics, Vigo, Spain, 2007, 1258-1263

[9] Sahoo S K, Dasgupta S, Panda S K, Xu J X. A Lyapunov function-based robust direct torque controller for switched reluctance motor drive system. IEEE Transactions on Power Electronics, 2012, 27(2): 555-564

[10] Skvarenina T L, Zuk O W, Krause P C. Simulation and analysis of a switched reluctance generator more electric aircraft power system using a graphical user interface. In: Proceedings of 31st Inter society Energy Conversion Engineering Conference, Hawaii, 1997, 580-584

[11] Torrey D A. Switched reluctance generators and their control. IEEE Transactions on Industrial Electronics, 2002, 49(1): 3-14

[12] Chen H, Ji L. Design of switched reluctance generator system based on the software package for windows. In: Proceedings of the 6th International Conference on Advances in Power System Control, Operation and Management, Honk Kong, 2003, 384-388

[13] Ichinokura O, Kikuchi T, Nakamura K, Watanabe T, Guo H J. Dynamic simulation model of switched reluctance generator. IEEE Transactions on Magnetics, 2003, 39(5): 3253-3255

[14] Pan Z P, Jin Y, Zhang H. Study on switched reluctance generator. Journal of Zhejiang University. Science, 2004, 5(5): 594-602

[15] Martinez A, Laloya E, Vicuña J, Pérez F, Pollán T, Martín B, Sánchez B, Lladó J. Simulation model of an AC autonomous switched reluctance generator. In: Proceedings of EUROCON 2007, Warsaw, Poland, 2007, 1674-1678

[16] Turker C G, Kuyumcu F E. The modelling and the simulation of the switched reluctance generator. In: 34th Annual Conference of IEEE Industrial Electronics, Florida, USA, 2008, 1421-1426

[17] Liptak M, Hrabovcova V, Rafajdus P. Equivalent circuit of switched reluctance generator based on DC series generator. Journal of Electrical Engineering, 2008, 59(1): 23-28

[18] Abelardo M, Oyarbide E, Vicuna J, Perez F, Laloya E, Martin-del-Brio B, Pollan T, Sanchez B, Llado J. Use of an AC self-excited switched reluctance generator as a battery charger. In: Proceedings of the 13th Power Electronics and Motion Control Conference. Poznan, Poland, 2008, 845-849

[19] Hao C, Jason J G. Implementation of the three-phase switched reluctance machine system for motors and generators. IEEE Transactions on Mechatronics, 2010, 15(3): 421-432

[20] Jyoti K, Umamaheswari B, Arumugam R. Simulation of power and control circuit for switched reluctance generator. In: 34th National System Conference, NITK, Surathkal,Mangalore, India, 2010, 33-38

[21] Godinho P M C, Calado M R A, Mariano S J P S. Design and numerical analysis of a new linear generator for wave energy conversion (ICCEP). In: Proceedings of 2011 International Conference on Clean Electrical Power. Ischia, Italy, 2011, 525-529

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