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Experimental validation of an analytical transient model for saturated boosting gain in DC–DC converters with variable duty cycle.
- Source :
- Discover Applied Sciences; Jul2024, Vol. 6 Issue 7, p1-12, 12p
- Publication Year :
- 2024
-
Abstract
- This paper presents an innovative approach to characterize the boosting gain saturation phenomenon in DC–DC converters with variable duty cycles, a crucial component in energy management applications such as renewable energy systems and IoT devices. While existing literature predominantly relies on steady-state models to explain boosting gain behaviour, this study reveals discrepancies between theoretical predictions and experimental observations, particularly at high duty cycles. The research introduces an analytical model to accurately capture the boosting gain dynamics of a boost chopper converter, addressing the limitations of traditional steady-state analyses. Through experimental validation and numerical simulations using CAD tools, a significant boosting gain saturation of approximately 2.2 is empirically observed, highlighting the necessity for a transient model approach. By providing a comprehensive understanding of the boosting ratio constraints in practical boost converters, this work contributes to advancing the analytical modelling techniques in the field. The mathematical model’s validation through rigorous experimental measurements and simulation analyses underscores its reliability and applicability in real-world scenarios. The structured organization of the paper elucidates the development and verification process, culminating in insightful conclusions that underscore the significance of transient modelling in enhancing the performance and efficiency of DC–DC converters.Article Highlights: Novel transient model enhances DC–DC converter performance. Boosting gain saturation validated through experiments. Insights on boosting ratio constraints for practical applications [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 30049261
- Volume :
- 6
- Issue :
- 7
- Database :
- Complementary Index
- Journal :
- Discover Applied Sciences
- Publication Type :
- Academic Journal
- Accession number :
- 178367756
- Full Text :
- https://doi.org/10.1007/s42452-024-05997-w