Parameter Estimation of Diode Circuit Using Extended Kalman Filter
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Parameter Estimation of Diode Circuit Using Extended Kalman Filter

Authors: Amit Kumar Gautam, Sudipta Majumdar

Abstract:

This paper presents parameter estimation of a single-phase rectifier using extended Kalman filter (EKF). The state space model has been obtained using Kirchhoff’s current law (KCL) and Kirchhoff’s voltage law (KVL). The capacitor voltage and diode current of the circuit have been estimated using EKF. Simulation results validate the better accuracy of the proposed method as compared to the least mean square method (LMS). Further, EKF has the advantage that it can be used for nonlinear systems.

Keywords: Extended Kalman filter, parameter estimation, single phase rectifier, state space modelling.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1474559

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[1] Y. Son and J.I. Ha, ”Discontinuous grid current control of motor drive system with single-phase diode rectifier and small DC-link capacitor,” IEEE Transactions on Power Electronics, vol. 32, no. 2, pp. 1324-1334, 2017.
[2] Y. Son and J. I. Ha, ”Direct power control of a three-phase inverter for grid input current shaping of a single-phase diode rectifier with a small DC-link capacitor,” IEEE Transactions on Power Electronics, vol. 30, no. 7, pp. 3794-3803, 2015.
[3] W. J. Lee, Y. Son and J. I. Ha, ”Single-phase active power filtering method using diode-rectifier-fed motor drive,” IEEE Transactions on Industry Applications, vol. 51, no. 3, pp. 2227-2236, 2015.
[4] S. Gupta, V. Nimesh and V. John, ”Diode bridge rectifier with improved power quality using capacitive network,” IEEE International Conference on Power Electronics, Drives and Energy Systems (PEDES), pp. 1-6, 2016.
[5] P. Wang, C. Liu and L. Guo, ”Modeling and simulation of full-bridge series resonant converter based on generalized state space averaging,” In Applied Mechanics and Materials, vol. 347, pp. 1828-1832, 2013.
[6] W. C. Yeh, C. L. Huang, P. Lin, Z. Chen, Y. Jiang and B. Sun, ”Simplex simplified swarm optimisation for the efficient optimisation of parameter identification for solar cell models,” IET Renewable Power Generation, vol. 12, no. 1, pp. 45-51, 2017.
[7] U. Jadli, P. Thakur and R. D. Shukla. ”A new parameter estimation method of solar photovoltaic,” IEEE Journal of Photovoltaics, vol. 8, no. 1, pp. 239-247, 2018.
[8] M. J. Zadeh and S. H. Fathi, ”A new approach for photovoltaic arrays modeling and maximum power point estimation in real operating conditions,” IEEE Transactions on Industrial Electronics, vol. 64, no. 12, pp. 9334-9343, 2017.
[9] L. W. Xu and K. Y. Qian, ”A fast method for lifetime estimation of blue light-emitting diode chips based on nonradiative recombination defects,” IEEE Photonics Journal, vol. 9, no. 4, pp. 1-9, 2017.
[10] E. I. Batzelis, G. E. Kampitsis and S. A. Papathanassiou, ”Power reserves control for PV systems with real-time MPP estimation via curve fitting,” IEEE Transactions on Sustainable Energy, vol. 8, no. 3, pp. 1269-1280, 2017.
[11] F. Attivissimo, A. Di Nisio, M. Savino and M. Spadavecchia, ”Uncertainty analysis in photovoltaic cell parameter estimation,” IEEE Transactions on Instrumentation and Measurement, vol. 61, no. 5, pp. 1334-1342, 2012.
[12] D. W. Kim, H. Oh, B. D. Youn and D. Kwon, ”Bivariate lifetime model for organic light-emitting diodes,” IEEE Transactions on Industrial Electronics, vol. 64, no. 3, pp. 2325-2334, 2017.
[13] S. Dusmez, S. H. Ali, M. Heydarzadeh, A. S. Kamath, H. Duran and B. Akin, ”Aging precursor identification and lifetime estimation for thermally aged discrete package silicon power switches,” IEEE Transactions on Industry Applications, vol. 53, no. 1, pp. 251-60, 2017.
[14] H. T. Chen, X. F. Zhou, J. Y. Cai and S. Lin, ”Estimation carrier concentration of light-emitting diode via electricalthermal characteristics,” IEEE Transactions on Electron Devices, vol. 62, no. 7, pp. 2257-2262, 2015.
[15] V. Savuskan, I. Brouk, M. Javitt, Y. Nemirovsky, ”An estimation of single photon avalanche diode (SPAD) photon detection efficiency (PDE) nonuniformity,” IEEE Sensors Journal, vol. 13, no. 5, pp. 1637-1640, 2013.
[16] W. A Ali, D. A. Mohamed and A. H. Hassan, ”Performance analysis of least mean square sample matrix inversion algorithm for smart antenna system,” In Antennas and Propagation Conference (LAPC) IEEE, pp. 624-629, 2013.
[17] D. Z. Feng, Z. Bao and L. C. Jiao, ”Total least mean squares algorithm,” IEEE Transactions on Signal Processing, vol. 46, no. 8, pp. 2122-2130, 1998.
[18] A. K. Pradhan, A. Routray and A. Basak, ”Power system frequency estimation using least mean square technique” IEEE transactions on power delivery, vol. 20, no. 3, pp. 1812-1816, 2005.
[19] W. Edmonson, J. Principe, K. Srinivasan and C. Wang, ”A global least mean square algorithm for adaptive IIR filtering,” IEEE Transactions on Circuits and Systems II: Analog and Digital Signal Processing, vol. 45, no. 3, pp. 379-384, 1998.
[20] I. Lakkis and D. McLernon, ”Least mean squares algorithm for fractionally spaced blind channel estimation,” IEE Proceedings-Vision, Image and Signal Processing, vol. 146, no. 4, pp. 181-184, 1999.
[21] A. Flammini, D. Marioli, E. Sisinni and A. Taroni, ”Least mean square method for LVDT signal processing,” IEEE Transactions on Instrumentation and Measurement, vol. 56, no. 6, pp. 2294-2300, 2007.
[22] A. Tarighat and A. H. Sayed, ”Least mean-phase adaptive filters with application to communications systems,” IEEE Signal Processing Letters, vol. 11, no. 2, pp. 220-223, 2004.
[23] A. K. Gautam and S. Majumdar, ”Parameter estimation of RC circuits using extended Kalman filter,” International Journal of Advanced in Management, Technology and Engineering Sciences, vol. 8, no. 1, pp. 83-91, 2018.
[24] R. Bansal and S. Majumdar, ”Implementation of extended Kalman filter on stochastic model of LPF,” International Journal of Advanced in Management, Technology and Engineering Sciences, vol. 7, no. 12, 2017.
[25] P. Stano, Z. Lendek, J. Braaksma, R. Babuska, C. de Keizer and J. Arnold. ”Parametric bayesian filters for nonlinear stochastic dynamical systems: a survey,” IEEE transactions on cybernetics, vol. 43, no. 6, pp. 1607-1624, 2013.