Low-complexity, high frequency parametric system identification method for switched-mode power converters

Gietler, Harald; Unterrieder, Christoph; Berger, Andreas; Priewasser, Robert; Lunglmayr, Michael

doi:10.1109/apec.2017.7930974

Cited by 9 publications

(15 citation statements)

References 14 publications

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“…A continuous time model based method is presented in [25], where a polynomial interpolation is applied to calculate the time derivatives involved, together with the least squares algorithm to estimate the passive and parasitic parameters of the converter. The closed loop parameters are estimated in [26] by means of state space models, taking into account the parasitic elements of the DC-DC converter. In [27] the behavior of the converter is approximated by means of a transfer function that is identified using a discrete-time model of the DC-DC converter.…”

Section: Non-linear Least Squares Optimization For Parametric Identifmentioning

confidence: 99%

Nonlinear Least Squares Optimization for Parametric Identification of DC–DC Converters

Rojas-Dueñas

Riba

Moreno-Eguilaz

2021

IEEE Trans. Power Electron.

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Switching mode power converters are being extensively applied in different power conversion systems. Parameter identification comprises a set of techniques focused on extracting the relevant parameters of the converters in order to generate accurate discrete simulation models or to design enhanced condition diagnosis schemes. This paper applies a noninvasive optimization approach based on the non-linear least squares algorithm to determine the model parameters of different commercially available DC-DC power converters (buck, boost and buck-boost) from experimental data, including the parameters related to passive, parasitic and control loop elements. The proposed approach is based on a non-invasive on-line acquisition of the input/output voltages and currents under both steady state and transient conditions. The proposed method can also be applied to many other applications requiring precise and efficient parameter identification, including rectifiers, filters, or power supplies among others.

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Section: Non-linear Least Squares Optimization For Parametric Identifmentioning

confidence: 99%

Nonlinear Least Squares Optimization for Parametric Identification of DC–DC Converters

Rojas-Dueñas

Riba

Moreno-Eguilaz

2021

IEEE Trans. Power Electron.

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“…Similarly to (16), the equations governing the dynamic behavior during the OFF state can be expressed as in (20).…”

Section: Boost Converter Parameter Identificationmentioning

confidence: 99%

“…According to the technical literature, different strategies can be applied for parameter identification in SMPCs. Gietler et al [16] identified the values of the passive components of a buck converter from the time-discrete transfer function of such electronic device using state space models. Ahmeid et al [2] proposed to identify the whole transfer function of a buck converter by means of a Kalman Filter.…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2018

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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.

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“…In the technical literature, different approaches are found to identify the parameters of power converters. In [8], the closed loop parameters are estimated using state space models, which consider the parasitic elements of the converter. In [9], a novel based approach based on continuous time models is developed, and a polynomial interpolation method, together with the least squares algorithm are applied to estimate the parameters of the converter, such as the inductor, capacitor and the parasitic elements, but not the closed loop parameters.…”

Section: Black-box Modelmentioning

confidence: 99%

DC-DC Buck Converter Parameter Identification Based on a White-Box Approach

Balakrishnan

Moreno-Ezuilaz

Riba

et al. 2018

2018 IEEE 18th International Power Electronics and Motion Control Conference (PEMC)

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This paper proposes to use a white-box approach to identify the parameters of an electronic DC-DC buck converter. It discretizes the differential equations governing the dynamic of such system, which are used to identify the parameters of the electronic components of the converter and the control loop. The proposed method is used to calculate the system parameters from the open loop and closed loop outputs, that is, the steady state and transient state stages of the output signals. The approach is validated by comparing simulation results from PSIM models of the converter with experimental data obtained from a commercial non-synchronous buck converter. Both simulation and experimental results show the feasibility and accuracy of the proposed approach in identifying the parameters of the converter, thus being feasible to obtain a full representation of such power converter. I.

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Low-complexity, high frequency parametric system identification method for switched-mode power converters

Cited by 9 publications

References 14 publications

Nonlinear Least Squares Optimization for Parametric Identification of DC–DC Converters

Nonlinear Least Squares Optimization for Parametric Identification of DC–DC Converters

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

DC-DC Buck Converter Parameter Identification Based on a White-Box Approach

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