Load Estimation of Single-Phase Diode Bridge Rectifier Using Kalman Filter
- 6 Downloads
These days most electronic loads are nonlinear. Electronic equipment such as audio devices, personal computers and electronic ballasts for discharge lamps are the example of nonlinear loads. These electronic loads are works in DC voltage. As the energy distribution system is performed in AC voltage, the AC voltage need to change into DC voltage. The single-phase rectifier performed the conversion of AC voltage to DC voltage in low power applications. The main drawback of these rectifiers is that they generate significant harmonic distortion. Components aging, power system efficiency lessen and excessive heat of equipments are the effects of harmonics in power system. Thus, the self-resonance, non-dielectric and hysteresis existed in the power system affected system designer to choose the passive components for the simulation. This paper portrays the study and development of an estimation method for the values of the electrical parts in the majority of the electronic equipment accessible in the market. It is conceivable to identify the values of equivalent capacitance, resistance and inductance that associated with the rectifier through this method. Simulation results validate the better accuracy of the proposed method when contrasted to the measurement-based method. The proposed method using Kalman filter to this rectifier topology enabled the expansion for future works to think about their harmonic effect on the power quality (PQ) of power distribution systems.
KeywordsKalman filter Parameter estimation Single-phase rectifier
The authors would like to thank MOE to support this research under grant RDU160145, FRGS/1/2016/TK04/UMP/02/17. Thanks to UMP for the assistance and support on this research.
- 1.Czarnecki LS, Staroszczyk Z (1996) On-line measurement of equivalent parameters for harmonic frequencies of a power distribution system and load. IEEE Trans Instrum Meas 45(2):467–472Google Scholar
- 2.Marino P, Mungiguerra V, Russo F, Vasca F (1996) Parameter and state estimation for induction motors via interlaced least squares algorithm and Kalman filter. In: PESC record. 27th annual IEEE power electronics specialists conference, vol 2, pp 1235–1241Google Scholar
- 3.Souza RRN, Coutinho DF, Dos Reis FS, Ribeiro FS (2008) Estimation of parameterized nonlinear loads: a time-domain approach. In: 2008 IEEE power electronics specialists conference, pp 4617–4623Google Scholar
- 6.Wang Z, Yong J (2013) Investigation on the capacitive characteristics of single-phase diode-bridge converter based loads. In: 2013 IEEE PES Asia-Pacific power and energy engineering conference (APPEEC), pp 1–4Google Scholar
- 7.Gautam AK, Majumdar S (2018) Parameter estimation of diode circuit using extended Kalman filter. Int J Electr Comput Energ Electron Commun Eng 12:604–610Google Scholar
- 9.Gautam AK, Majumdar S (2018) Parameter estimation of RC circuits using Extended Kalman Filter. Int J Adv Manag Technol Eng Sci 8(1):83–91Google Scholar
- 10.Bansal R, Majumdar S (2017) Implementation of extended Kalman filter on stochastic model of LPF. Int J Adv Manag Technol Eng Sci 7(12):120–130Google Scholar
- 11.Yim S, Seok J, Lee J (2012) State estimation of the nonlinear suspension system based on nonlinear Kalman filter. In: 2012 12th international conference on control, automation and systems, pp 720–725Google Scholar
- 15.Gupta S, Nimesh V, John V (2016) Diode bridge rectifier with improved power quality using capacitive network. In: 2016 IEEE international conference on power electronics, drives and energy systems (PEDES), pp 1–6Google Scholar
- 16.Wang P, Liu C, Guo L (2013) Modeling and simulation of full-bridge series resonant converter based on generalized state space averaging BT. In: Proceedings of the 2nd international conference on computer science and electronics engineeringGoogle Scholar