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

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