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Title: Online inductor parameters identification by small signal injection for sensorless predictive current controlled boost converter
Authors: Chen, Chen
Li, Linkai
Zhang, Qiao
Tong, Qiaoling
Liu, Kan
Lyu, Dian
Min, Run
Keywords: Inductors
Current control
Parameter estimation
Issue Date: 2017
Publisher: © IEEE
Citation: CHEN, C. ... et al., 2017. Online inductor parameters identification by small signal injection for sensorless predictive current controlled boost converter. IEEE Transactions on Industrial Informatics, 13(4), pp.1554-1564.
Abstract: In a sensorless predictive current controlled boost converter, parameterizing the inductor plays an important role in controller performance. In this paper, a solution for inductor parameters online identification is investigated. A small signal injection strategy is proposed to create a transient state, and convergence problem of inductance identification in steady state can be avoided. Then a charge balance current observer (CBCO), derived from capacitor current charging balance concept, is adopted to estimate the inductor current for inductance identification. Since inductance is not used in CBCO, current estimation is not affected by inductance identification error. Because of rank-deficient problem, instead of identifying inductor parasitic resistance solely, the inductor equivalent parasitic resistance is derived. By applying it into the conventional current observer for current control loop, the accuracy of current estimation can still be guaranteed since more parasitic effects are included. To improve the accuracy of inductance identification, a load identification method is investigated. Furthermore, the effect of the equivalent series resistance (ESR) of output capacitor on the proposed algorithm is analyzed. Finally, its effectiveness is verified by experimental results.
Description: Personal use is permitted, but republication/redistribution requires IEEE permission. See http://www.ieee.org/publications_standards/publications/rights/index.html for more information
Version: Accepted for publication
DOI: 10.1109/TII.2016.2647079
URI: https://dspace.lboro.ac.uk/2134/24260
Publisher Link: http://dx.doi.org/10.1109/TII.2016.2647079
ISSN: 1551-3203
Appears in Collections:Published Articles (Mechanical, Electrical and Manufacturing Engineering)

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