Boost converters are used in photovoltaic systems for maximum power point tracking. Their performance depends on the environmental conditions under which the converter operates. This article aims to optimize the losses, volume, and weight of the converter in a multi-objective optimization applied using the NSGA-II metaheuristic, considering the operating points of the photovoltaic panel for specific temperature and real irradiance values from a given location. As a second objective, this article verifies whether the converter obtained in one location will be capable of operating in another location within the working operation ranges of the components present in the converter.

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.