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A parameter-averaging approach to converter system order reduction

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In this study, we propose a parameter-averaging-based modeling (PAM) method using the state-space theory for high-order power converters with multiple dynamic components, e.g., inductors and capacitors. With the proposed PAM… Click to show full abstract

In this study, we propose a parameter-averaging-based modeling (PAM) method using the state-space theory for high-order power converters with multiple dynamic components, e.g., inductors and capacitors. With the proposed PAM method, we aim to reduce the order of converter models, and thus diminish diminishing the computational burden when obtaining the steady-state operating point and transfer function. To demonstrate the procedure and functionality of the proposed order reduction method, a fifth-order power converter model is employed as an example, which is reduced to second order and first order in continuous conduction mode (CCM) and discontinuous conduction mode (DCM), respectively. Simulation studies prove that the reduced-order model is able to produce comparable system responses as the original model. The stimulation responses of the acquired transfer functions for reduced-order state spaces in CCM and DCM are further validated by hardware experimentation.

Keywords: order; parameter averaging; order reduction; converter

Journal Title: Electrical Engineering
Year Published: 2021

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