%0 Journal Article %A Chen, Chen %A Li, Linkai %A Zhang, Qiao %A Tong, Qiaoling %A Liu, Kan %A Lyu, Dian %A Min, Run %D 2017 %T Online inductor parameters identification by small signal injection for sensorless predictive current controlled boost converter %U https://repository.lboro.ac.uk/articles/journal_contribution/Online_inductor_parameters_identification_by_small_signal_injection_for_sensorless_predictive_current_controlled_boost_converter/9564164 %2 https://repository.lboro.ac.uk/ndownloader/files/17196503 %K Inductors %K Inductance %K Observers %K Resistance %K Current control %K Parameter estimation %K Mechanical Engineering not elsewhere classified %X 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. %I Loughborough University