The evolution of power architectures in domains such as IoT, smart homes, and electric vehicles has driven the adoption of higher supply voltages to improve energy efficiency and minimize distribution losses. Consequently, there is a growing demand for wide-input-range DC-DC converters that can deliver stable and efficient regulation, particularly under light-load conditions in decentralized systems. In this context, accurately evaluating and quantifying power losses has become a critical design consideration. This work presents a comprehensive analytical methodology for estimating power losses and efficiency in the power stage of two step-down DC-DC converter topologies: a half-bridge converter and a resonant converter. The analysis is supported by explicit equations, providing insight into the dominant loss mechanisms. The proposed model is validated through circuit-level simulations, demonstrating good agreement with theoretical predictions.
Comparative Study of High-Voltage High-Conversion-Ratio Step-Down DC-DC Converters for Light Load Applications
Malcovati R.
;Moisello E.;Aprile A.;Bonizzoni E.
2025-01-01
Abstract
The evolution of power architectures in domains such as IoT, smart homes, and electric vehicles has driven the adoption of higher supply voltages to improve energy efficiency and minimize distribution losses. Consequently, there is a growing demand for wide-input-range DC-DC converters that can deliver stable and efficient regulation, particularly under light-load conditions in decentralized systems. In this context, accurately evaluating and quantifying power losses has become a critical design consideration. This work presents a comprehensive analytical methodology for estimating power losses and efficiency in the power stage of two step-down DC-DC converter topologies: a half-bridge converter and a resonant converter. The analysis is supported by explicit equations, providing insight into the dominant loss mechanisms. The proposed model is validated through circuit-level simulations, demonstrating good agreement with theoretical predictions.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
