Parameter Identification of DC-DC Converters under Steady-State and Transient Conditions Based on White-Box Models

This paper proposes a white-box approach for identifying the parameters of DC-DC buck and boost switch mode power converters. It is based on discretizing the differential equations that describe the dynamic behavior of the converters. From the discretized equations and experimental data, the parameters of the converters are identified, thus obtaining both the values of the passive components and the transfer function coefficients of the controller. To this end, steady state and transient experimental signals are analyzed, including the input and output voltages and the inductor and output currents. To determine the accuracy of the proposed method, once the parameters are identified, a simulation with the identified parameters of the converter is run and compared with experimental signals. Such results show the accuracy and feasibility of the approach proposed in this work, which can be extended to other converters and electrical and electronic devices.

[1]  Wei Chen,et al.  A real-parameter genetic algorithm application in parameters identification for synchronous generator , 2009, 2009 IEEE International Conference on Intelligent Computing and Intelligent Systems.

[2]  Peng Xu,et al.  Transmission Line Parameter Identification Considering Non-Synchronized Time of Fault Recording Information , 2018, 2018 2nd IEEE Advanced Information Management,Communicates,Electronic and Automation Control Conference (IMCEC).

[3]  Harald Gietler,et al.  Low-complexity, high frequency parametric system identification method for switched-mode power converters , 2017, 2017 IEEE Applied Power Electronics Conference and Exposition (APEC).

[4]  Marco Sorrentino,et al.  A review on model-based diagnosis methodologies for PEMFCs , 2013 .

[5]  Rupert Gouws,et al.  Electrical Circuit Modelling of Double Layer Capacitors for Power Electronics and Energy Storage Applications: A Review , 2018, Electronics.

[6]  Jose A. Cobos,et al.  Behavioral modeling of multi-output DC-DC converters for large-signal simulation of distributed power systems , 2006 .

[7]  Van Ha Nguyen,et al.  Active EMI Reduction Using Chaotic Modulation in a Buck Converter with Relaxed Output LC Filter , 2018 .

[8]  Chunying Gong,et al.  Modified hybrid model of boost converters for parameter identification of passive components , 2017 .

[9]  Maher Al-Greer,et al.  Real-Time Parameter Estimation of DC–DC Converters Using a Self-Tuned Kalman Filter , 2017, IEEE Transactions on Power Electronics.

[10]  Maher Mohammed Fawzi Saber Algreer.  Microprocessor based signal processing techniques for system identification and adaptive control of DC-DC converters , 2012 .

[11]  Matthew Armstrong,et al.  Parameter Estimation of DC-DC Converters Using Recursive Algorithms with Adjustable Iteration Frequency , 2018, 2018 IEEE 19th Workshop on Control and Modeling for Power Electronics (COMPEL).

[12]  O. Nelles.  Nonlinear System Identification: From Classical Approaches to Neural Networks and Fuzzy Models , 2000 .

[13]  Kan Liu,et al.  Online Inductor Parameters Identification by Small-Signal Injection for Sensorless Predictive Current Controlled Boost Converter , 2017, IEEE Transactions on Industrial Informatics.

[14]  Qian Shen,et al.  A unified feature parameter extraction strategy based on system identification for the Buck converter with linear or nonlinear loads , 2016, IECON 2016 - 42nd Annual Conference of the IEEE Industrial Electronics Society.

[15]  A.M.R. Amaral,et al.  An unified method for estimating the parameters of non-isolated DC/DC converters using continuous time models , 2007, INTELEC 07 - 29th International Telecommunications Energy Conference.

[16]  A.M.R. Amaral,et al.  ESR Estimation Method for DC/DC Converters Through Simplified Regression Models , 2007, 2007 IEEE Industry Applications Annual Meeting.

[17]  Xiaodong Li,et al.  Improved Step Load Response of a Dual-Active-Bridge DC–DC Converter , 2018 .

[18]  D. Culler,et al.  Comparison of methods , 2000 .

[19]  H. Sira-Ramírez,et al.  Robust Nonlinear Adaptive Control of a “Boost” Converter via Algebraic Parameter Identification , 2014, IEEE Transactions on Industrial Electronics.

[20]  Lingling Fan,et al.  Least squares based estimation of synchronous generator states and parameters with phasor measurement units , 2012, 2012 North American Power Symposium (NAPS).

[21]  Virgilio Valdivia Guerrero.  Behavioral modelling and identification of power electronics converters and subsystems based on transient response , 2013 .