Comparative analysis between recursive least squares state space (RLSS) and nonlinear least squares (NLS) methods for parameter identification in buck converters applied to solar energy systems

The lifespan of a converter depends on component reliability. In non-redundant designs like buck converters, a single component failure can shut down the circuit. Capacitors are more prone to failure than inductors or semiconductors. Monitoring parameters such as equivalent series resistance, rather than manual data, better assesses a converter’s useful life. This article compares two parameter estimation methods: recursive state space and non-linear least squares, with R² values and residuals analysis ensuring reliable results that closely correlate with real converter values.